Man-Machine-Environment System Engineering

These proceedings showcase the best papers selected from more than 500 submissions, and introduce readers to the hottest research topics and the latest developmental trends in the theory and application of MMESE. The integrated and advanced science research topic Man-Machine-Environment System Engineering (MMESE) was first established in China by Professor Shengzhao Long in 1981, with direct support from one of the greatest modern Chinese scientists, Xuesen Qian. In a letter to Long from October 22nd, 1993, Qian wrote: “You have created a very important modern science and technology in China!” MMESE primarily focuses on the relationship between Man, Machine and Environment, studying the optimum combination of man-machine-environment systems. In this system, “Man” refers to working people as the subject in the workplace (e.g. operators, decision-makers); “Machine” is the general name for any object controlled by Man (including tools, machinery, computers, systems and technologies), and “Environment” describes the specific working conditions under which Man and Machine interact (e.g. temperature, noise, vibration, hazardous gases etc.). The three main goals of optimizing man-machine-environment systems are to ensure safety, efficiency and economy. These proceedings present interdisciplinary studies on essential concepts and methods from physiology, psychology, system engineering, computer science, environmental science, management, education, and other related disciplines. As such, they offer a valuable resource for all researchers and professionals whose work involves interdisciplinary areas touching on MMESE subjects.

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Lecture Notes in Electrical Engineering 527

Shengzhao Long Balbir S. Dhillon Editors

Man-MachineEnvironment System Engineering Proceedings of the 18th International Conference on MMESE

Lecture Notes in Electrical Engineering Volume 527

Board of Series editors Leopoldo Angrisani, Napoli, Italy Marco Arteaga, Coyoacán, México Bijaya Ketan Panigrahi, New Delhi, India Samarjit Chakraborty, München, Germany Jiming Chen, Hangzhou, P.R. China Shanben Chen, Shanghai, China Tan Kay Chen, Singapore, Singapore Rüdiger Dillmann, Karlsruhe, Germany Haibin Duan, Beijing, China Gianluigi Ferrari, Parma, Italy Manuel Ferre, Madrid, Spain Sandra Hirche, München, Germany Faryar Jabbari, Irvine, USA Limin Jia, Beijing, China Janusz Kacprzyk, Warsaw, Poland Alaa Khamis, New Cairo City, Egypt Torsten Kroeger, Stanford, USA Qilian Liang, Arlington, USA Tan Cher Ming, Singapore, Singapore Wolfgang Minker, Ulm, Germany Pradeep Misra, Dayton, USA Sebastian Möller, Berlin, Germany Subhas Mukhopadhyay, Palmerston North, New Zealand Cun-Zheng Ning, Tempe, USA Toyoaki Nishida, Kyoto, Japan Federica Pascucci, Roma, Italy Yong Qin, Beijing, China Gan Woon Seng, Singapore, Singapore Germano Veiga, Porto, Portugal Haitao Wu, Beijing, China Junjie James Zhang, Charlotte, USA

** Indexing: The books of this series are submitted to ISI Proceedings, EI-Compendex, SCOPUS, MetaPress, Springerlink ** Lecture Notes in Electrical Engineering (LNEE) is a book series which reports the latest research and developments in Electrical Engineering, namely:

• • • • • •

Communication, Networks, and Information Theory Computer Engineering Signal, Image, Speech and Information Processing Circuits and Systems Bioengineering Engineering

The audience for the books in LNEE consists of advanced level students, researchers, and industry professionals working at the forefront of their fields. Much like Springer’s other Lecture Notes series, LNEE will be distributed through Springer’s print and electronic publishing channels. For general information about this series, comments or suggestions, please use the contact address under “service for this series”. To submit a proposal or request further information, please contact the appropriate Springer Publishing Editors: Asia: China, Jasmine Duo, Assistant Editor ([email protected]) (Engineering) India, Swati Meherishi, Senior Editor ([email protected]) (Engineering) Japan, Takeyuki Yonezawa, Editorial Director ([email protected]) (Physical Sciences & Engineering) South Korea, Smith (Ahram) Chae, Associate Editor ([email protected]) (Physical Sciences & Engineering) Southeast Asia, Ramesh Premnath, Editor ([email protected]) (Electrical Engineering) South Asia, Aninda Bose, Editor ([email protected]) (Electrical Engineering) Europe: Leontina Di Cecco, Editor ([email protected]) (Applied Sciences and Engineering; Bio-Inspired Robotics, Medical Robotics, Bioengineering; Computational Methods & Models in Science, Medicine and Technology; Soft Computing; Philosophy of Modern Science and Technologies; Mechanical Engineering; Ocean and Naval Engineering; Water Management & Technology) Christoph Baumann ([email protected]) (Heat and Mass Transfer, Signal Processing and Telecommunications, and Solid and Fluid Mechanics, and Engineering Materials) North America: Michael Luby, Editor ([email protected]) (Mechanics; Materials)

More information about this series at http://www.springer.com/series/7818

Shengzhao Long Balbir S. Dhillon •

Editors

Man-Machine-Environment System Engineering Proceedings of the 18th International Conference on MMESE

123

Editors Shengzhao Long Astronuat Research and Training Center of China Beijing, China

Balbir S. Dhillon University of Ottawa Ottawa, ON, Canada

ISSN 1876-1100 ISSN 1876-1119 (electronic) Lecture Notes in Electrical Engineering ISBN 978-981-13-2480-2 ISBN 978-981-13-2481-9 (eBook) https://doi.org/10.1007/978-981-13-2481-9 Library of Congress Control Number: 2018953711 © Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Grandness Scientist Xuesen Qian’s Sky-high Estimation for the Man-MachineEnvironment System Engineering

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Grandness Scientist Xuesen Qian’s Congratulatory Letter to the 20th Anniversary Commemorative Conference of Man-Machine-Environment System Engineering Foundation

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Preface

In 1981, under the directing of the great scientist Xuesen Qian, an integrated frontier science—Man-Machine-Environment System Engineering (MMESE)— came into being in China. Xuesen Qian gave high praise to this emerging science. In the letter to Shengzhao Long, he pointed out, “You are creating this very important modern science and technology in China!” on October 22, 1993. In the congratulation letter to the commemoration meeting of 20th anniversary of establishing the Man-Machine-Environment System Engineering, the great scientist Xuesen Qian stated, “You have made active development and exploration in this new emerging science of MMESE, and obtained encouraging achievements. I am sincerely pleased and hope you can do even more to make prosper development in the theory and application of MMESE, and make positive contribution to the progress of science and technology in China, and even in the whole world” in June 26, 2001. October 22, which is the day that the great scientist Xuesen Qian gave high praise to MMESE, was determined to be Foundation Commemoration Day of MMESE by the 2nd conference of the 5th MMESE Committee on October 22, 2010. On this very special day, the great scientists Xuesen Qian pointed out in the letter to Shengzhao Long, “You are creating this very important modern science and technology in China!” The 18th International Conference on MMESE will be held in Nanjing, China, on October 20–22 of this year; hence, we will dedicate Man-Machine-Environment System Engineering: Proceedings of the 18th International Conference on MMESE to our readers. Man-Machine-Environment System Engineering: Proceedings of the 18th International Conference on MMESE is the academic showcases of the 18th International Conference on MMESE joint held by MMESE Committee of China and Beijing KeCui Academe of MMESE in Nanjing, China. The Man-MachineEnvironment System Engineering: Proceedings of the 18th International Conference on MMESE consists of 83 more excellent papers selected from more than 400 papers. Due to limitations on space, some excellent papers have been left out, and we feel deeply sorry for that. Crudeness in contents and possible ix

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Preface

incorrectness are inevitable due to the somewhat pressing editing time, and we hope you kindly point them out promptly, and your valuable comments and suggestions are also welcomed. Man-Machine-Environment System Engineering: Proceedings of the 18th International Conference on MMESE will be published by Springer-Verlag, German. Springer-Verlag is also responsible for the related matters on index of Index to EI, so that the world can know the research quality and development trend of MMESE theory and application. Therefore, the publication of Man-MachineEnvironment System Engineering: Proceedings of the 18th International Conference on MMESE will greatly promote the vigorous development of MMESE in the world and realize the grand object of “making positive contribution to the progress of science and technology in China, and even in the whole world” proposed by Xuesen Qian. We would like to express our sincere thanks to Springer-Verlag, German, for their full support and help of during the publishing process. Beijing, China July 2018

Prof. Shengzhao Long

Program and Technical Committee Information

General Chairman Professor Shengzhao Long, Astronaut Research and Training Center of China Program Committee Chairman Professor Balbir S. Dhillon, University of Ottawa, Canada Technical Committee Chairman Professor Enrong Mao, College of Engineering, China Agricultural University, China Program and Technical Committee Members Professor Yanping Chen, University of Management and Technology, USA Professor Hongfeng Gao, University of California, USA Professor Michael Greenspan, Queen’s University, Canada Professor Birsen Donmez, University of Toronto, Canada Professor Xiangshi Ren, Kochi University of Technology, Japan Professor Kinhuat Low, Nanyang Technological University, Singapore Professor Baiqiao Huang, System Engineering Research Institute of China State Shipbuilding Corporation, China Professor Baoqing Xia, Weapon Industrial Hygiene Research Institute, China Professor Chenming Li, The Quartermaster Research Institute of Engineering and Technology, China Professor Fang Xie, China North Vehicle Research Institute, China Professor Guangtao Ma, Shenyang Jianzhu University, China Professor Haoting Liu, University of Science and Technology Beijing, China Professor Hongjun Xue, Northwestern Polytechnical University, China Professor Lijing Wang, Beijing University of Aeronautics and Astronautics, China Professor Long Ye, Beijing Jiaotong University, China Senior Engineer, Qichao Zhao, Beijing King Far Technology Co., Ltd., China

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Program and Technical Committee Information

Professor Qing Liu, Jinggangshan University, China Professor Weijun Chen, Shanghai Maritime University, China Professor Xiaochao Guo, Institute of Aviation Medicine, Air Force, China Professor Yongqing Hou, China Academy of Space Technology, China Professor Yanqi Wang, Weapon Industrial Hygiene Research Institute, China Professor Yinying Huang, Agricultural Bank of China, China Professor Yuhong Shen, The Quartermaster Research Institute of Engineering and Technology, China

Contents

Part I

Research on the Man Character

Study on Pilot Personality Selection with an SVM-Based Classifier . . . . Jicheng Sun, Xiao Xiao, Shan Cheng, Chao Shen, Jin Ma and Wendong Hu

3

Eye Tracking for Assessment of Mental Workload and Evaluation of RVD Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yu Tian, Shaoyao Zhang, Chunhui Wang, Qu Yan and Shanguang Chen

11

The Contrastive Analysis of Three Models About Human Energy Expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chenming Li, Tianhao Wang and Yuhong Shen

19

Development of a Three-Dimensional Finite Element Model of Spine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tianhao Wang, Chenming Li and Yan Wang

27

The Study of Evaluation Technologies for Human Energy Metabolism Based on Physiological Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tianhao Wang, Chenming Li and Yan Wang

33

School Emergencies and College Student Psychological Crisis Intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yu Luo, Yunde Sun, Xia Chen, Chunlei Ren and Xuechen Yao

41

Effect of Physical Fatigue on Cognitive Ability of Workers in Furniture CNC Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Na Yu and Peiwen Wu

49

Study on Fatigue of Workers in the Row Drilling Operation of Furniture Manufacturing Based on Operational Energy Efficiency Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Na Yu, Jing Guo, Lian Hong, Peiwen Wu and Jing Li

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Contents

Evaluation of Workload, Arousal, Fatigue, and Attention on Time-Series Vigilance Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deqian Zhang, Wenjiao Cheng and Hezhi Yang Deep Thinking on Talents Cultivation in the Field of Civil–Military Integration Under the Domain of Science, Technology, and Equipment of National Defense . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jinxin Li, Peng Gong, Yunqiang Xiang, Guiqi Liu and Wenying Xing A Study on the Skill of Plotting Air Condition by Hand of the Cartographer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hongyan Ou, Zhibing Pang, Hailiang Li, Zhijun Li, Hao Liu and Deyang Zhang Two-Step Subjective Rating Technique of Pilot Evaluation in Q–Q Test for Aircraft Cockpit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaochao Guo, Qingfeng Liu, Duanqin Xiong and Yanyan Wang A Method and Realization of Constructing Chinese Standard Digital Human Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xibin Kao, Lijing Ji, Yanqi Wang, Baoqing Xia, Jun He, Qiaoli Yang, Wei Kong and Shun Chen Part II

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79

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Research on the Machine Character

Structure Design and Motion Simulation of a Microprocessor-Controlled Prosthetic Knee . . . . . . . . . . . . . . . . . . . . . . 107 Wujing Cao, Hongliu Yu, Weiliang Zhao, Qiaoling Meng and Wenming Chen Rethinking the Characteristics and Expression of Modern Office Building Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Zhen Li and Fang Liu Study on the Cable-Controlled Household Upper Limb Rehabilitation Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Xiaohai Huang, Hongliu Yu, Yinxin Xu, Xinwei Li, Weisheng Zhang and Wujing Cao Design and Kinematics Analysis of a Lower Limb Exoskeleton Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Xiaodong Wei, Hongliu Yu, Qingyun Meng and Bingshan Hu Task-Based Trajectory Planning for an Exoskeleton Upper Limb Rehabilitation Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Qiaoling Meng, Haicun Shao, Lulu Wang and Hongliu Yu

Contents

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A Novel Method for Designing and Implementing a Training Device for Hand Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Duojin Wang and Hongliu Yu The Unfolding of a Clock Based on the Arduino Control . . . . . . . . . . . 165 Yanli Zhou, Xiaolei Tan, Jiejie Zhang and Feng Sha Toilet System Design in Public High-End Places . . . . . . . . . . . . . . . . . . 175 Zhixuan Lin, Canqun He and Muhan Zhang Research on the Design of FMD Desktop 3D Printer Based on a User-Centered Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Hang Yin and Yi Pan Construction and Application of Digital Slide Network Teaching System in Histology Courses . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Wenying Xing, Chang Mei and Ruo Feng Analysis of Key Technologies and Performances of Fire-Control Radar of Low Probability of Intercept . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Yan Zhu, Wei Yu, Hao Sun, Kun Li and Jiang Luo The Application of Jack Software in the Size Study of the Exhaust Hood on a Welding Torch . . . . . . . . . . . . . . . . . . . . . . . 209 Jianwu Chen, Zhenfang Chen, Bin Yang, Shasha Liang, Delei Zhao, Jinhui Tao and Xun Xu Design of a Central-Driven Upper Limb Rehabilitation Robot in Respect of Human Safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Bingshan Hu, Fei Zhang and Hongliu Yu A Low-Cost Solution of Eye Movement Data Acquisition Based on Computer Vision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 Haoshu Gu and Junming Du Research on Intermittent Failure Mechanism of the Electrical Connector of the Missile Launch Vehicle . . . . . . . . . . . . . . . . . . . . . . . . 239 Guanqian Deng, Guiyou Hao, Yingjie Lv and Ying Zhou Research on Children’s Functional Shoes’ Design Based on Ergonomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Haijiao Sun Part III

Research on the Environment Character

Development and Validity of Chinese Hazard Perception Test . . . . . . . . 257 Long Sun, Shuang Li and Ruosong Chang

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Contents

A Kind of Extravehicular Lighting Environment Analysis Method of Shenzhou Spacecraft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263 Haoting Liu, Shuo Yang, Weidong Dong, Shunliang Pan and Jin Yang Image Quality Evaluation Metric of Brightness Contrast . . . . . . . . . . . . 271 Haoting Liu, Fenggang Xu, Shuo Yang, Weidong Dong and Shunliang Pan Short-Term Public Transportation Passenger Flow Forecasting Method Based on Multi-source Data and Shepard Interpolating Prediction Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 Wenzhou Jin, Peng Li, Weitiao Wu and Lanhui Wei The Color Choices of Chinese Pilots for Aircraft Cabin Interior . . . . . . 295 Jian Du, Chunmei Gui, Xiaochao Guo, Yanyan Wang, Qinglin Zhou, Yu Bai, Guowei Shi and Duanqin Xiong Part IV

Research on the Man-Machine Relationship

Comparative Study on Cab’s H Point Design Model Based on Human Factors Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Jiangli He, Chenxuan Yang, Tong Zhu, Xiaoyong Wang and Yueqi Hu Human–Machine Analysis of Bus Station Identification System in Changzhou . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 Canqun He, Jinting Hu and Xiaolei Tan Research About UI Color Preference for Mobile Terminal Based on the User’s Visual Thinking and Perception . . . . . . . . . . . . . . . . . . . . 323 Jing Jin and Huaqing Shen Interface Ergonomics Evaluation Methods and Applied Research for Fighter Cockpit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Haijing Song and Xiaofang Xu Study on the Optimization Design Method of Human–Machine Interface of Vehicle Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 Nan Men, Zhibing Pang, Fenghua Wang, Honglei Li, Pengdong Zhang and Quanliang Yin Ergonomics Evaluation of Large Screen Display in Cockpit Based on Eye-Tracking Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 Yanyan Wang, Qingfeng Liu, Wanli Lou, Duanqin Xiong, Yu Bai, Jian Du and Xiaochao Guo Position of Heading Information Presented in HUD for Aircraft Cockpit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 Xiaochao Guo, Yanyan Wang, Qingfeng Liu and Duanqin Xiong

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Human–Computer Interaction Design Testing Based on Decision-Making Process Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365 Baiqiao Huang, Pengyi Zhang and Chuan Wang Contact Position Relation Between Car Bumpers and Lower Limbs of Pedestrians Involved in Crashes . . . . . . . . . . . . . . . . . . . . . . . 373 Quan Yuan, Song Chen, Chuanzhou Qin and Haojie Yang Part V

Research on the Man-Environment Relationship

Effect of Tight-Fitting Sportswear Compression on Sports Fatigue . . . . 383 Yuxiu Yan, Xuan Li, Ke Liu, Zimin Jin and Jing Jin Study on the Effects of Noise on Crew’s Mental Workload in Information Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Kaixuan Zhao, Weiping Liu, Binhe Fu and Junfeng Nie Study About the Effects of Noise on Crew’s Thinking Ability . . . . . . . . 401 Kaixuan Zhao, Weiping Liu, Binhe Fu and Bo Yang Research on Protective Performance of Basketball Knee Pads Based on 3D Motion Capture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409 Yuxiu Yan, Quan Wang, Zimin Jin and Jianwei Tao Study on 5-km Armed Cross-Country Training in the Plateau Hypoxic Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 Shuai Mu, Ming Kong, Huifang Wang and Hai Chang The Influence of Short-Time Head-Down Tilt Simulated Weightlessness on Performance of Motion Direction Judgment . . . . . . . 425 Duming Wang, Qipei Han and Yu Tian The Development of Military Helmet for Bare-Handed Combat . . . . . . 433 Xiaobin Yang Study on Human Adaptability in Urban Underground Space Combat Environment Under Special Circumstances . . . . . . . . . . . . . . . 441 Wang Wang and Hangdong Wang Study on the Influence of Interior Decoration of Ship Cabin on Crew’s Visual Work Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449 Hangtao Cheng, Chuan Wang and Zhe Wang Part VI

Research on the Machine-Environment Relationship

The Shock Resistance Research of Light Seamless Knitted Fabric . . . . . 457 Yuanyuan Wang, Zimin Jin and Yuanyuan Qi

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Contents

Calculation and Analysis of FCR Burn-Through Range with Noise Jamming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463 Wei Yu, Hong He, Xiaonian Wang, Boqi Wang, Kun Li and Jiang Luo Research on Noise Measurement of a Self-propelled Weapon System and Its Noise-Reduction Measures . . . . . . . . . . . . . . . . . . . . . . . 471 Pengdong Zhang, Zhibing Pang, Xuechen Yao, Changsheng Wang, Yong Kang and Nan Men Part VII

Research on the Overall Performance of Man-Machine-Environment System

Design on the Virtual Maintenance Training System of Some-Type Equipment Based on the Virtual Reality . . . . . . . . . . . . . . . . . . . . . . . . 479 Zuohui Bao, Yong Wang, Zuobin Yang, Chunfeng Zhu and Cheng Jin Analysis of the Risk Assessment of Subway Stampede . . . . . . . . . . . . . . 489 Qiquan Wang, Jiaxin Wu, Li Li and Jingjing Shao Research on Emergency Evacuation Simulation of Old Dormitory Building Based on Pathfinder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 Yan Li, Yan Zhang and Jianpin Jiang Analysis of Risk Dissemination in Supply Chain Based on Knowledge Dissemination Network Model . . . . . . . . . . . . . . . . . . . . 509 Yan Li, Zixin Su and Jianping Jiang Research on Reality-Based Training and Management Issues in Air Defense Forces Troops by Governing the Military Under the Rule of Law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519 Peng Gong, Yunqiang Xiang, Guiqi Liu, Zhenguo Mei and Ye Tao The Dialectical Thinking on Leadership of the Commanders and the Fighting Capability of Troops Under the Target of Building a Strong Military . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 Zaochen Liu, Peng Gong, Doudou Shan, Ye Tao and Shenzhen Zheng Analysis on the Effect of Safety Culture Construction Factors . . . . . . . . 535 Zhenguo Mei, Chang Mei, Peng Gong, Ye Tao and Wenying Xing On Academic Evaluation Index System of Weaponry Subject . . . . . . . . 543 Hai Chang, Bingjun Zhang, Zengjun Ji and Shuai Mu Analysis and Monitoring on Training Intensity of Single Unit Based on Oximeter RAD-57 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551 Cheng Jin, Di Liu, Genhua Qi, Zhibing Pang, Haitao Zhao and Zhaofeng Luo

Contents

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Research on Field Rescue Based on Expedient Material . . . . . . . . . . . . 559 Zhingbing Pang, Huawei Li, Mingming Sui, Kunyuan Hu, Zhaofeng Luo and Shuai Mu Research on the Training of Air Observation Post Operator . . . . . . . . . 567 Haitao Zhao, Genhua Qi, Zhibing Pang, Cheng Jin, Honglei Li and Hongyan Ou Application of Crisis Intervention After Aircraft Mishap . . . . . . . . . . . . 575 Qingfeng Liu, Xiaochao Guo, Fei Peng, Wanli Lou, Duanqin Xiong, Lei Yang, Yu Bai and Yanyan Wang Missile Maintenance Management Using Data Flow Analysis and Discrete Event Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583 Fang Liu, Jinshi Xiao, Jun Huang, Qiang Zou and Haoting Liu Key Chain Buffer Setting Method for Uncertainty of Project Duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 593 Fenglin Zhang and Xingming Gao Flight Test Risk Mechanism with Man-Machine-Environment System of Civil Aircraft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 601 Yuanyuan Guo, Youchao Sun and Longbiao Li Residual Risk Assessment of Civil Aircraft for Airworthiness Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 611 Yuanyuan Guo, Youchao Sun and Longbiao Li Airworthiness Safety Construction of Civil Aircraft Based on Operational Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 619 Yuanyuan Guo, Youchao Sun and Longbiao Li Experimental Study on Simulated Flight Performance with Monochrome and Colorful Display for See-Through Displays . . . . . . . . 627 Duanqin Xiong, Qing He, Xiaochao Guo, Yu Bai, Yanyan Wang, Fei Peng, Jian Du and Qingfeng Liu Application of the Grey Clustering Evaluation Model in Risk Level Assessment of Merchant Ships . . . . . . . . . . . . . . . . . . . . . . . . . . . 637 Feng Li and Hong Yi Research on Metacognitive Training Method of Six-Degree-of-Freedom Observation and Control . . . . . . . . . . . . . . . . . . 647 Jie Li, Jiayi Cai, Weifen Huang, Liwei Zhang, Jing Zhao, Yanlei Wang, Xiang Zhang and Qianxiang Zhou Intermittent Failure Combing Analysis and Prevention of a Certain Type of Missile Weaponry . . . . . . . . . . . . . . . . . . . . . . . . . 657 Guanqian Deng, Guiyou Hao, Yingjie Lv and Ying Zhou

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Contents

High Altitude Oxygen Production and Implementation of Special Vehicle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663 Haiyan Niu, Liang Tian, Yaofeng He and Jianquan Ding Study on Test Specification for Vibration Control of Heavy Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671 Heping Wang, Mei Zhang and Xiaoyu Zhong The Multiple Classification Method of Signal Recognition for Spacecraft Based on SAE Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . 679 Wei Lan, Yixin Liu, Zhang Qi, Shimin Song, Chun He, Lijing Wang and Ke Li Part VIII

Theory and Application Research

Evaluation on the Design of Man-Machine-Environment System of Interactive Experience Space in Library . . . . . . . . . . . . . . . . . . . . . . 693 Kunzhu Zhang, Liyan Tan and Yang Liu The Dilemma Generated by Automated Driving Considered from Ethical Aspect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 703 Tianrui Qin, Quan Yuan and Wenjie Lu Application of Man-Machine-Environment System Engineering in Shipboard Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 711 Baiqiao Huang and Pengyi Zhang Space design of Display Console on Ship-Based Man-Machine-Environment System Engineering . . . . . . . . . . . . . . . . . . 721 Jingyu Song and Baiqiao Huang

About the Editors

Prof. Shengzhao Long is the Founder of the Man-Machine-Environment System Engineering (MMESE), the Chairman of the Man-Machine-Environment System Engineering (MMESE) Committee of China, the Chairman of the Beijing KeCui Academy of Man-Machine-Environment System Engineering (MMESE), and the Former Director of Ergonomics Lab of Astronaut Research and Training Center of China. On October 1992, he is honored by the National Government Specific Allowance. He graduated from the Shanghai Science and Technology University in 1965, China. In 1981, directing under famous Scientist Xuesen Qian, he founded the MMESE theory. In 1982, he proposed and developed human fuzzy control model using fuzzy mathematics. From August of 1986 to August of 1987, he conducted research in man–machine system as a Visiting Scholar at Tufts University, Massachusetts, USA. In 1993, he organized Man-Machine-Environment System Engineering (MMESE) Committee of China. He has published “Foundation of theory and application of Man-Machine-Environment System Engineering” (2004) and “Man-Machine-Environment System Engineering” (1987). He also edited “Proceedings of the 1st–17th Conference on Man-Machine-Environment System Engineering” (1993–2017). e-mail: [email protected] Dr. Balbir S. Dhillon is a Professor of Engineering Management in the Department of Mechanical Engineering at the University of Ottawa, Canada. He has served as a Chairman/Director of Mechanical Engineering Department/ Engineering Management Program for over 10 years at the same institution. He has published over 345 (i.e., 201 journals + 144 conference proceedings) articles on reliability, safety, engineering management, etc. He is or has been on the editorial boards of nine international scientific journals. In addition, he has written 34 books on various aspects of reliability, design, safety, quality, and engineering management published by Wiley (1981), Van Nostrand (1982), Butterworth (1983), Marcel Dekker (1984), Pergamon (1986), etc. His books are being used in over 85 countries, and many of them are translated into languages such as German, Russian,

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and Chinese. He has served as General Chairman of two international conferences on reliability and quality control held in Los Angeles and Paris in 1987. He has served as a consultant to various organizations and bodies and has many years of experience in the industrial sector. At the University of Ottawa, he has been teaching reliability, quality, engineering management, design, and related areas for over 29 years and he has also lectured in over 50 countries, including keynote addresses at various international scientific conferences held in North America, Europe, Asia, and Africa. In March 2004, he was a Distinguished Speaker at the Conf./Workshop on Surgical Errors (sponsored by White House Health and Safety Committee and Pentagon), held at the Capitol Hill (One Constitution Avenue, Washington, D.C.). He attended the University of Wales where he received a B.S. in electrical and electronic engineering and an M.S. in mechanical engineering. He received a Ph.D. in industrial engineering from the University of Windsor. e-mail: [email protected]

Part I

Research on the Man Character

Study on Pilot Personality Selection with an SVM-Based Classifier Jicheng Sun, Xiao Xiao, Shan Cheng, Chao Shen, Jin Ma and Wendong Hu

Abstract Purpose This paper intends to explore the feasibility of using statistical learning methods for learning and analyzing the data obtained from physiological tests and to offer novel ideas for the pilot selection and evaluation by investigating the personality traits of aviation professionals based on the results of the aforesaid exploration. Method A total of 1478 testees, including 342 pilots and 1136 non-pilots, are chosen randomly from an airline company and are randomly classified into a training group and a test group before performing Cattell’s 16 personality factor test. The 16 factors in the test are learnt by a support vector machine (SVM), and the learning results are analyzed. Results Five factors are used as eigenvectors for the classification. The classifier that is constructed based on linear SVM achieves a 78% average accuracy in the cross-validation. Conclusion The SVM-based classifier has high reliability and effectiveness. Keywords Civil aviation pilot SVM 16PF



 Personality selection and evaluation

1 Introduction People have developed a unified and generalized understanding of pilot competencies and compiled a set of criteria for pilot selection [1, 2]. These criteria focus on the psychological traits of candidates, and the pilots are selected based on the results of a psychological test [3, 4]. In China, Cattell’s 16 personality factor test (16PF) is widely used in the preliminary screening of civil aviation pilots. Study obtains the standard score of the 16 factors for the participants and analyzes the

J. Sun (&)  X. Xiao  S. Cheng  C. Shen  J. Ma  W. Hu Medical Equipment Teaching and Research Section, School of Aerospace Medicine, The Fourth Military Medical University, Xi’an 710032, Shaanxi, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_1

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personality traits of these participants. However, the study does not indicate whether a candidate’s suitability for a flight career can be judged based on his/her personality traits. Support vector machine (SVM) is known to have the best generalization ability. This method is established based on limited sample information and by following Vapnik–Chervonenkis dimension theory and the structural risk minimization principle, thereby making SVM a key machine learning technique [5]. SVM can also effectively address the small sample size problem that cannot be addressed by a neural network, and some studies have also validated its advantages in evaluating nonlinear problems. Therefore, SVM is a very scientific and reasonable method that provides an effective decision support for the psychological selection of pilots and for assessing the appropriateness of using 16PF factors in the evaluation of pilot candidates. People can also distinguish the personality traits of pilots from those of non-pilots by establishing an SVM classifier.

2 Data Collection 2.1

Testees

The data are collected from a person–time psychological test involving 1478 staff members from 2 domestic airlines. All testees are physically healthy without any organic diseases or mental disorders. Among these testees, 898 are males and 580 are females, while 342 are pilots and 1136 are non-pilots (safety officers, flight attendants, and ground staff). This study excludes data on flying cadets to enhance the representativeness of the pilot data.

2.2

Test Tool and Data Collection

The data are tested by 16PF of the tablet polygraph, and the testees are required to perform the test in a quiet environment without external disturbances [6]. This study employs the Chinese version of 16PF revised by the office, and the adult standard is adopted as the norm.

3 Evaluation of Pilot Personality Traits Based on SVM 3.1

Process of SVM-Based Evaluation

The personality traits of pilots are evaluated based on SVM as follows. First, the author collects and preprocesses the data, selects the traits based on a literature

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review, and performs a data analysis. Second, the selected factors are used as eigenvectors, while a candidate’s classification as a pilot or non-pilot is used as the target vector. Third, these vectors are imported into the SVM and are randomly divided into the training set and test set for multiple cross-validation. Fourth, one kernel function, one insensitive loss function, and the corresponding error test standard are selected. While cross-validating the samples, the adaptive performance of SVM is optimized through constant adjustment, and a stable SVM model is eventually obtained. Fifth, the objects for evaluation are inputted into the trained model, and the evaluation results are eventually obtained.

3.2

Preliminary Data Analysis and Selection of Personality Traits

The open-source libraries, pandas and sklearn of python, are adopted for the scrubbing and standardization of the data obtained from the test. These data are classified into pilot (0) and non-pilot (1). To guide the selection of a kernel function and personality traits during the construction of a classifier, the descriptive statistical analysis of the processed data reveals that emotional stability, apprehension, vigilance, and tension follow a skewed distribution, while the other factors follow a normal distribution. No clear correlation is found between any two factors. The correlation among the 16 factors and their correlation with the pilot/ non-pilot classification are shown in Fig. 1. The color intensity indicates the degree of correlation; that is, red represents a positive correlation, while blue represents a negative correlation. The analysis reveals that the 16 factors are not strongly correlated with the pilot/ non-pilot classification and that no single factor can provide rich information for the prediction of pilot or non-pilot. Emotional stability has a relatively strong negative correlation with apprehension, vigilance, and tension as well as a relatively strong positive correlation with rule consciousness. Apprehension has a relatively strong positive correlation with tension, while liveliness has a relatively strong positive correlation with social boldness. These findings indicate that some factors can provide redundant information during the construction of a classifier. Therefore, part of these factors shall be removed during the feature selection. The f_classif of the single variable feature selection in the sklearn.feature_selection model is adopted for the variance analysis of the pilot/non-pilot factors and for calculating the F value and p value. The p value of all factors is translated into −log (p value), divided by the maximum −log (p value), and used as an indicator for measuring factor discrimination. Table 1 presents the results of the variance analysis for these factors. The p values indicate significant differences in the warmth, reasoning, emotional stability, rule consciousness, sensitivity, vigilance, abstractedness, apprehension,

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Fig. 1 Correlation matrix of the 16 factors. Note The color map uses red to indicate positive correlation and blue to indicate negative. While the deeper the color is, the high the correlation is (Color figure online)

self-reliance, perfectionism, and tension between the pilot and non-pilot. Following the literature and our correlation analysis [7], we select emotional stability, sensitivity, abstractedness, self-reliance, and perfectionism as the features.

3.3

Construction of an SVM-Based Method for Evaluating Pilot Personality Traits

We use SVM for the construction of a classifier because this technique attempts to predict a category, our data have already been classified, and our sample size exceeds 1000. We adopt the SVC of the open-source machine learning library sklearn for the construction of a classifier and perform cross-validation by iteratively and randomly dividing our data into training and test sets. The sample size for the training set has increased from 1 to 90% during the cross-validation. The learning curves for training score and validation score are illustrated based on the cross-validation results for each classifier in order to check the classifier effect and to compare several classifiers. During the SVM optimization, the regularization of the classifier is automatically adjusted by the machine learning algorithm when the kernel function is fixed.

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Table 1 ANOVA for 16 factors between pilot and non-pilot Factors

F value

p value

−log (p value)/max (−log (p value))

Warmth 25.57 10%) of experienced drivers. Experienced drivers had shorter response latencies than novice drivers in 35 video clips (Cronbach’s a = 0.92). The other 10 video clips that cannot effectively discriminate between drivers groups were eliminated.

3.2

Response Latency and Demographic Factors

Novice drivers (M = 2.33, SD = 0.45), on average, responded significantly slower to the hazards than did experienced drivers (M = 2.93, SD = 0.33), F (1, 93) = 57.78, p < 0.001, ŋ2 = 0.376. An analysis of covariance was further conducted to examine the effect of driving experience on the response latencies, using gender, age, and years of education as covariant. The main effect of driving experience was significant, F (1, 93) = 56.44, p < 0.001, ŋ2 = 0.378; the effect of gender was not significant

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(1, 93) = 0.14, p > 0.05; the effect of age was significant, F (1, 93) = 7.21, p < 0.01, ŋ2 = 0.072; the effect of years of education was significant, F (1, 93) = 4.91, p < 0.05, ŋ2 = 0.050. The result showed that the test was useful in distinguishing drivers with varying driving experience and age.

3.3

Prediction of Driver Groups

A binary logistic regression model revealed that individual differences in response latency were a significant predictor of driver groups, X2 = 42.82, p < 0.001, Cox and Snell R2 = 0.354, Nagelkerke R2 = 0.476. The overall classification accuracy of the test is 80.6%. Specifically, the classification accuracy of the test is 86% for novice drivers and 73.2% for experienced drivers. That is, drivers’ response latencies to the hazards in the test, in most time, can predict their driver groups, regardless of their age or driving experience. Furthermore, drivers, who had traffic violations, responded significantly faster to the hazards compared to those who had not have violations, t (96) = 2.22, p < 0.05, Cohen’s d = 0.52. Also, drivers, who had traffic accidents, responded significantly faster to the hazards compared to those who had not have accidents, t (96) = 2.40, p < 0.05, d = 0.79. These results provided evidence for the validity of the test.

4 Discussions The present study developed a Chinese hazard perception test using video clips shooting from drivers’ perspective. Our results showed that the test was a reliable, valid and highly useful tool for assessing drivers’ hazard perception ability. The selection of video clips followed the five principles suggested by Wetton and his colleagues [5]. First, all the video clips contained natural driving scenes, representing situations that Chinese drivers should properly address to ensure their driving safety. It should be noted that the video clips did not contain situations that the camera car was reversing or a car was overtaking the camera car from behind. Second, several evaluations were made by driving experts to ensure the test can and only measure the structure of hazard perception. Those clips that cannot measure the structure of hazard perception well or measure other psychological structure were eliminated from the very beginning of the development of the test. Third, the instruction clearly defined what kind of hazardous situations that drivers needed to respond to, by illustrating what constituted a hazardous situation and the proper responses to the hazards. Four, due to the using of custom software, the test could distinguish cheaters by analyzing whether the mouse click fell within the hazard window when a response was made. Finally, each clip can effectively discriminate between driver groups, thus leading the predictive validity of the test was good.

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The test can predict driver groups well based on the result of the test-taker, suggesting that the reliability of the test was good. However, we found that those clips that contained either abrupt-onset hazards or hazards happened on the adjacent driving lanes (i.e., hazards were not in the course of the camera car) were less sensitive to driving experience. This suggested that the experience-related differences in response latencies depended on the hazard types in the clips. Although abrupt-onset hazards cannot differentiate driver groups, these hazards should be ignored in studies. Finally, we found that drivers, who had traffic violations or accidents in the passing year of driving, responded to the hazards significantly faster than did drivers who had not have traffic violations or accidents. One possible explanation was that most of the novice drivers have not driven long enough to have traffic violations or accidents. Another explanation may be that due to the small size of the sample, we did not make a distinction between safe drivers and unsafe drivers, the latter referred to the drivers that had always committed traffic accidents and their driving license had been suspended. Moreover, we found that several demographic factors, such as driving experience and age, influenced drivers’ response latencies to the hazards. These findings enhanced our confidence that the test is suitable for driver assessment and training in China. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Liaoning Normal University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Wetton MA, Horswill MS, Hatherly C et al (2010) The development and validation of two complementary measures of drivers’ hazard perception ability [J]. Accid Anal Prev 42 (4):1232–1239 2. Pelz DC, Krupat E (1974) Caution profile and driving record of undergraduate males [J]. Accid Anal Prev 6(1):45–58 3. Horswill MS (2016) Hazard perception in driving [J]. Curr Dir Psychol Sci 25(6):425–430 4. Sun L, Chang R, Li S (2018) Effects of driving experience and hazard type on young drivers’ hazard perception [J]. Lect Notes Electr Eng 456:11–16 5. Wetton MA, Hill A, Horswill MS (2011) The development and validation of a hazard perception test for use in driver licensing [J]. Accid Anal Prev 43(5):1759–1770 6. Lim PC, Sheppard E, Crundall D (2013) Cross-cultural effects on drivers’ hazard perception [J]. Transp Res Part F Traffic Psychol Behav 21:194–206 7. Sun L, Chang R (2016) Effects of self-assessed ability and driving experience on hazard perception [J]. J Psychol Sci 39(6):1346–1352 8. Scialfa CT, Deschênes MC, Ference J et al (2011) A hazard perception test for novice drivers [J]. Accid Anal Prev 43(1):204–208

A Kind of Extravehicular Lighting Environment Analysis Method of Shenzhou Spacecraft Haoting Liu, Shuo Yang, Weidong Dong, Shunliang Pan and Jin Yang

Abstract A kind of extravehicular lighting environment analysis (ELEA) method of Shenzhou spacecraft is proposed. This study is useful when evaluating the working security of the extravehicular activity. First, a fine 3D model of Shenzhou spacecraft is built. Second, the complete space flight process of Shenzhou spacecraft is simulated. In that simulation, the orbital elements, the spatial position with sun and the flight attitude of Shenzhou spacecraft can all be calculated. Third, the extravehicular lighting environment is analysed. The radiation power and the illumination in the Shenzhou spacecraft can be estimated. Many experiment results have verified the correctness of proposed method.



Keywords Extravehicular activity Space lighting Radiation power Illumination estimation



 Shenzhou spacecraft

1 Introduction The extravehicular activity [1] is one of the most important tasks in the manned spaceflight mission. The extravehicular activity needs the astronaut to walk out of the spacecraft and implement some servicing tasks. During that process, many measurements have been done to protect the security of astronauts or assist the H. Liu (&) School of Automation and Electrical Engineering, University of Science and Technology Beijing, 100083 Beijing, China e-mail: [email protected] H. Liu Beijing Engineering Research Center of Industrial Spectrum Imaging, Beijing 100083, China S. Yang  W. Dong  S. Pan Institute of Manned Space System Engineering, Beijing 100094, China J. Yang Astronaut Research & Training Center of China, Beijing 100094, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_31

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in-orbit operation of them. For example, the astronauts need to wear the extravehicular space suit [2] to protect themselves from the rigorous vacuum and microgravity environment [3]; they also need to use the umbilical cable [4] to monitor their physiological state; and some tools, such as the pliers, the saw or the wrench, are used to help them accomplish the maintenance task of spacecraft. Currently, we think the research of security support technology of astronaut is still insufficient for the development plan of the China space station. Because the vision is the most important information source for astronauts when they implement the extravehicular activity; the careful lighting environment analysis and control [5] in orbit should be performed. As a kind of low-orbit spacecraft, the Shenzhou spacecraft will experience lots of sunshine regions and shadow regions during one natural flight day [6] which means the space lighting environment will change very fast and complex. As a result, the lighting environment will surely influence the working efficiency [7] or even the security state of astronaut. In this paper, a kind of extravehicular lighting environment analysis (ELEA) method of Shenzhou spacecraft is proposed. First, a fine 3D model of Shenzhou spacecraft is built. The surface details of the Shenzhou spacecraft body are modelled carefully. Second, the flight process in orbit of Shenzhou spacecraft is simulated. Its orbital elements [8], its spatial position with sun and its flight attitude can all be computed. Third, the extravehicular lighting environment is analysed. An illumination simulation method was proposed in [9]; and as a kind of supplementary, the radiation power [10] and the illumination [11] of sun in the spacecraft body can be estimated in this paper.

2 Space Flight Simulation Method Figure 1 shows a kind of 3D model of the Shenzhou spacecraft. From Fig. 1, it can be seen that the Shenzhou spacecraft at least includes the orbital module, the re-entry module, the service module, and the solar panels. When performing the spacecraft maintenance task, the astronauts always need to check the working states of the solar panels or some communication antennas and sensors which are fixed in

Fig. 1 3D model of Shenzhou spaceflight

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Table 1 Orbital elements’ examples of Shenzhou spacecraft The orbital elements

Eccentricity (–)

Semimajor axis (km)

Inclination (°)

Longitude of the ascending node (°)

Argument of periapsis (°)

True anomaly (°)

Value

0.00048

6638.5

42.4

26.3

321.7

163.9

the surface of spacecraft. During that process, the extravehicular lighting environment will change quickly because of the fast spatial position change between the sun and the spacecraft. The attitude tuning and the perturbation [12] will also affect the lighting condition of the spacecraft body. The flight trajectory of Shenzhou spacecraft can be simulated by lots of commercial software. Its orbital elements and its spatial position with sun can all be simulated. For example, one of orbital elements of Shenzhou spacecraft can be shown in Table 1. The spacecraft attitude of Shenzhou spacecraft can also be computed when performing some simulation measurements. For example, when the spacecraft enter the sunshine region, the solar plane will be controlled to point to the sun; thus, one of its control angles can be tuned with respect to a kind of arcsin function in [13].

3 ELEA Calculation Model In this paper, both the radiation power and the illumination of sun are calculated for the Shenzhou spacecraft model. For the sake of simplicity, other environment lighting influences, such as the earth, the moon and other stars will not be considered.

3.1

The Radiation Power Estimation Method

Without loss of generality, let us regard each observation region in spacecraft as a small plane. First, a Cartesian coordinate is built in the spacecraft. The origin of coordinate locates in the centre of the spacecraft; the x-axis follows the flight direction, the z-axis points to the geocentre, and the y-axis can be generated accords with the right-hand principle. Second, the sun radiation power can be estimated by (1) and (3) or (2) and (3). Equation (1) can compute the radiation power of curved surface, while (2) is a simplified version of (1) which can only calculate the radiation power of plane. Here, the parameter (a, b, c) and hs can be calculated by the flight trajectory simulation software; and the observation area can be computed by the 3D model of Shenzhou spacecraft. Finally, the sun radiation power of each observation plane can be estimated in the spacecraft.

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ZZ WP1 ¼

ðu;vÞ2D

Is 

cos uðu; vÞ þ jcos uðu; vÞj dudv 2

WP2 ¼ RS  A  ðcos hs þ jcos hs jÞ=2 h i.  2 cos hs ¼ 1  ðcos a  dx Þ2 þ cos b  dy þ ðcos c  dz Þ2 2

ð1Þ ð2Þ ð3Þ

where Rs is the solar constant, Rs = 1353 W/m2; A is the observation area; (dx, dy, dz) is the normal vector of observation point, and dx, dy, dz2[0, 1], d2x + d2y + d2z = 1; (a, b, c) is the angle between the sunlight and the coordinate axes x, y and z.

3.2

The Illumination Estimation Method

The illumination means the light flux in the unit area. It can indicate the illuminated degree of an object. In contrast to the emission concept, it represents the received light flux in a certain area. Because the distance between the sun and the spacecraft is large, the sun can be looked on as a point light source; then the illumination estimation can be computed (4). In this paper, only the typical positions in the spacecraft need the computation of radiation power and illumination; the typical positions can be the solar plane or the communication antennas, etc. For the sake of simplicity, if the observation area is a curved surface, one or more than one tangent plane will be used to piece together the computed region.    WI2 ¼ Is L2 cos u

ð4Þ

where Is is the total light flux of sun, Is= 3.5661028 lm; L is the distance between the sun and the spacecraft, L  1.49597871011 m; / is the angle between the sunlight direction and the normal of the observation plane.

4 Experiment Results and Discussions A series of simulation experiment are carried out to test the proposed ELEA method. The 3D model and the space flight simulation are implemented by a commercial software. The simulation program of ELEA is implemented by C and MATLAB in our PC (2.4 GHz CPU and 3 GB RAM).

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The Simulation Results

Figure 2 shows six typical observation positions in the Shenzhou spacecraft. They are selected to participate the ELEA because all kinds of faults always happen in these parts. In Fig. 2, (a) is the image of the Shenzhou spacecraft; (b) presents the enlarged images of the typical observation positions. From Fig. 2b, it can be seen that these typical positions include the observation points in the front cabin door, the hung window, the sensor 1, the sensor 2, the solar plane and the attitude control engine from top to bottom and left to right. Both the radiation power and the illumination of sun are analysed in this paper. The related simulations are implemented only in the sunlight region. Comparing with the distance between the sun and the earth, the distance between the sun and the Shenzhou spacecraft located in different orbits can be approximated as the same [14], thus only the attitude of spacecraft will influence the computation results seriously. Figure 3 shows one of related computation results of Fig. 2. From Fig. 3, it can be seen that the radiation power and the illumination will vary a lot in different positions of Shenzhou spacecraft. Thus, it is necessary to analyse and control the lighting situations in orbit in order to improve the security of extravehicular activity.

Fig. 2 Selection results of typical observation positions in the Shenzhou spaceflight

Fig. 3 Some simulation results of typical observation positions in the Shenzhou spaceflight. In (a) is the simulation results of radiation power, where the observation area is 0.01 m2; (b) is the simulation results of illumination

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Discussions

The lighting environment analysis is necessary for the extravehicular activity of Shenzhou spacecraft. As a kind of low-orbit spacecraft, the flight period of each circle is only about 90 min. During that process, the lighting change is fast and complex. The attitude tuning and the orbit perturbation will also affect the lighting condition in the spacecraft body. The familiar problems include the glare, the low illuminance, the non-uniform lighting region, and the light-fast-change-caused flicker. In other cases, if some man-made light is casted into the working platform, the improper light colour, such as yellow light or the red light, will also arise lots of visual discomfort problem [15] which is harm to the extravehicular activity definitely. To conquer these problems above, on the one hand the ELEA should be made; on the other hand, the intelligent lighting device can be developed to assist the astronaut to accomplish the extravehicular activity. The ELEA should consider the radiation effect of sun, including the radiation power and the illuminance. It should also involve the subjective feeling of human eyes; thus, the subjective luminance should be considered. In future, the light model of computer graphics [16] can be used here. Other radiation light sources, such as the earth, the moon, can also be analysed. The intelligent lighting system can cast light with the change of environment. Its function is to guarantee the lighting effect of observation region to be stable.

5 Conclusion A kind of extravehicular lighting environment analysis method of Shenzhou spacecraft is proposed. This method is designed for the security analysis of extravehicular activity. First, a 3D model of Shenzhou spacecraft is built. Second, the flight process of Shenzhou spacecraft is simulated. The orbital elements, the spatial potion with sun and the flight attitude of Shenzhou spacecraft are all computed. Third, the extravehicular lighting environment is analysed. The radiation power and the illumination in the typical position of Shenzhou spacecraft are estimated. In future, the analysis results of lighting environment will be used to assist the in-orbit operation of astronaut. Acknowledgements This work is supported by the National Nature Science Foundation of China under Grant No. 61501016 and the open project of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect under Grant No. SKLIPR1713.

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References 1. Miller MJ, McGuire KM, Feigh KM (2015) Information flow model of human extravehicular activity operations. In: IEEEAC, pp 1–15 2. Hill TR, Johnson BJ (2010) EVA space suit architecture: low earth orbit vs. moon vs. mars. IEEEAC, pp 1–28 3. Yoshida K (2009) Achievements in space robotics. IEEE Robot Autom Mag 14:20–28 4. Zhang Z, He Z, Zhao R, Chen Y (2017) Mechanical process design on umbilical cable of spacesuit. Elec Proc Tech 38:289–290 5. Liu H, Zhou Q, Yang J, Jiang J, Liu Z, Li J (2017) Intelligent luminance control of lighting systems based on imaging sensor feedback. Sensors 17:321-1–321-24 6. Liu H, Yang J, Wang W, He Z, Yu W (2015) Illumination effect estimation based on image quality assessment. In: ICMMESE, pp 285–293 7. Xing J, Zhang Y, Li J, Feng Y (2012) Sequential scheduling in space missions, In: CyberC, pp 298–303 8. Yang Y, Zhang H, Feng Z, Luo Y (2006) Selection of the best initial orbital elements of satellite based on fuzzy integration evaluation method. J Syst Eng Electron 17:566–570 9. Liu X, Chao J, He N (2011) Study on the illumination simulation method for visual simulation of the space flight training simulator. J Astronaut 32:2622–2627 10. Xiang S, Zhang T (2007) Calculation of solar direct radiation on the satellite external surface using STK. Infrared Tech 29:508–511 11. Xu H (2016) Handbook of lighting design, 3rd edn. China Electric Power Press, Beijing 12. Liu X, Guo Y, Lu P (2014) Robust attitude coordination control for satellite formation with matched perturbations and measurement noises. In: ACC, pp 3893–3898 13. Tao Y, Pan C, T Y (2007) A method to improve sunshine efficiency of solar array. Aerosp Shanghai 5:23–26 14. Brozovic M, Showalter MR, Jacobson RA, Buie MW (2015) The orbits and masses of satellites of Pluto. Icarus 246:317–329 15. Iacomussi P, Radis M, Rossi G, Rossi L (2015) Visual comfort with LED lighting. In: IBPC, pp 729–734 16. Cerezo E, Perez F, Pueyo X, Seron FJ, Sillion FX (2005) A survey on participating media rendering techniques. Visual Comput 21:303–328

Image Quality Evaluation Metric of Brightness Contrast Haoting Liu, Fenggang Xu, Shuo Yang, Weidong Dong and Shunliang Pan

Abstract An image quality evaluation method of brightness contrast is proposed. It is assumed that the change trend of gradual enhancement of an image with a high contrast is different with that of an image with a low contrast; the proposed calculation steps are as follows: First, regarding an image, a series of control parameters of gamma correction (GC) is generated orderly and they are used to implement the GC computation. Second, one reference image is selected from the image set above and the structural similarity (SSIM) method is employed to compute the evaluation results among the selected reference image and each image in the enhanced image set. Third, the control parameters of GC and the computation results of SSIM are used to build a curve. Finally, the Gaussian function is used to fit the curve above and the standard deviation of it is regarded as the brightness contrast metric. Many experiment results have shown the validity of proposed method. Keywords Image quality evaluation SSIM Gaussian function fitting



 Brightness contrast  Gamma correction

H. Liu (&) School of Automation and Electrical Engineering, University of Science and Technology Beijing, 100083 Beijing, China e-mail: [email protected] H. Liu Beijing Engineering Research Center of Industrial Spectrum Imaging, Beijing 100083, China F. Xu Astronaut Research and Training Center of China, Beijing 100094, China S. Yang  W. Dong  S. Pan Institute of Manned Space System Engineering, Beijing 100094, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_32

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1 Introduction With the fast development of information technique, more and more visible light cameras are utilized for the security or the surveillance applications [1]. The image quality (IQ) of visible light camera is always affected by the environment light or the atmosphere easily [2]. A low IQ not only influences the watching effect but also makes some troubles to the subsequent computation of image processing algorithm. This is mainly because the image with low quality always loses many details but contains too much-unwanted information. Thus, in order to give the user an objective evaluation of imaging quality, the IQ evaluation issue has become an important task for the vision-based system design. Many IQ evaluation metrics have been proposed, such as the blur metric [3], the noise metric [4], and the brightness contrast metric [5], etc. Among these metrics, the design of image brightness contrast (IBC) metric is one of most interesting tasks. Many brightness contrast evaluation methods have been proposed. In [5], the author proposed a series of methods to evaluate the imaging contrast. In [6], the authors assessed the contrast in the DCT domain. In [7], the authors used the method in wavelet domain to evaluate contrast. After a comparative study, it can be found that some problems still exist in the current methods: (1) As a kind of blind IQ evaluation metric, many methods are still influenced by the image content seriously [8]. (2) The computation complexities of some methods are high. In this paper, a blind IBC metric is proposed. The basic design idea of it is as follows: The enhancement change trend of an image with a high brightness contrast is different with that of an image with a low contrast. That is to say when we use an image enhancement technique to process an image and if we increase the enhancement degree little by little, the quality change of the image with a high brightness contrast should be different with that of the image with a low contrast. Thus, the computation steps the gamma correction (GC) [9] and the structural similarity (SSIM) method [10] are combined to compute a kind of change effect curve of the original image; and then, the IQ can be assessed by observing the change trend of the enhancement effect curve above.

2 Proposed Computational Flow Chart The proposed computation flowchart is shown in Fig. 1. From Fig. 1, first, to change the brightness contrast of an image, the GC is used to process the original image. The control parameters of GC are increased gradually, and then these parameters are employed to process the original image. Second, one of the enhanced images is selected as the standard reference image from the image set above. For example, the image with the lowest brightness will be chosen. Third, the SSIM is utilized to assess the IQ among the standard reference image above and the other enhanced images orderly. After that, the relationship curve between the

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Fig. 1 Calculation flowchart of proposed algorithm

control parameters of GC and the evaluation results of SSIM can be gotten. Finally, the Gaussian function is used to fit the series above and the standard deviation of that function can be regarded as a metric to evaluate the IQ of the brightness contrast. The least square method is utilized here [11] to accomplish curve fitting task.

3 Design of Brightness Contrast Metric 3.1

Gamma Correction Method

The GC is utilized widely to improve the visual output quality of the degraded image. It is typically suited for solving the nonlinear degraded problem which always derives from the complex nature light. The classic GC method utilizes an exponent function to map the original image signal into a new data space. The corresponding equation is shown in (1). From (1), it can be seen that the main control parameter of GC is the parameter ci. In this paper, to get a series of enhancement results of GC, the control parameter ci is updated by (2) gradually. Then, a series of control parameters can be used to carry out the GC computation to the original image.   1=ci Iic ¼ Iimax  Iio Iimax

ð1Þ

ci ¼ c0 þ Dt  cs

ð2Þ

where the subscript i means the ith image; Ici is the image processing result of GC; Ioi is the gray value of point in the original image; Imax is the maximum value of the i original image; Imax can be set by 255; ci is the control parameter of GC; c0 is the i initial value of the control parameter and cs is the step length; Dt is the sample space; in this paper, c0= 1.0, Dt = 0.1, cs= 1.0, and ci< 3.0.

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Selection Method of the Reference Image

The aim of the selection of a reference image from the GC processing results is to acquire a benchmark image; then, the SSIM method can be used to compute a series of full reference evaluation results to assess the enhancement change trend of the degraded image. With the value increase of control parameter ci, the brightness contrast of the original image will be improved to some extent. This result can be proved by using the contrast evaluation metric (3). It also can be found that the image brightness will increase monotonously with the change of GC control parameter. Here, the brightness can be computed by using the average of image intensity in a certain sample block. In this paper, the image with the lowest contrast is used as a reference image. Mc ¼

N X k¼1

ðIikmax



Iikmin Þ



!, ðIikmax

þ Iikmin Þ

N

ð3Þ

and Imin are the maximum and the minimum gray values of the kth where Imax k k image block; N is the pixel number of the sample block.

3.3

SSIM Evaluation Method

The SSIM is a full reference IQ evaluation method which assesses the nature attribution of an image by using the texture description. The SSIM emphasizes the structural relativity of the neighboring pixels; and it does not use the traditional method of error accumulation to evaluate the IQ. Regarding two images x and y, the SSIM can evaluate the IQ by three terms: the luminance information l(x, y) (see 4), the contrast information c(x, y) (see 5), and the structure information s(x, y) (see 6). The final SSIM evaluation equation can be calculated by (7). To improve its performance, the Gaussian weighting function can be used to estimate the corresponding statistics lx, ly, rx, ry and rxy.    . 2 lðx; yÞ ¼ 2lx ly þ C1 lx þ l2y þ C1

ð4Þ

  . 2 cðx; yÞ ¼ 2rx ry þ C2 rx þ r2y þ C2

ð5Þ

   sðx; yÞ ¼ rxy þ C3 rx ry þ C3

ð6Þ

SSIMðx; yÞ ¼ ½lðx; yÞa ½cðx; yÞb ½sðx; yÞg

ð7Þ

where C1= (K1I)2, C2= (K2I)2, C3= C2/2 are constants, I 2 [0, 255], K1 and K2 are scalar constants; here K1= 0.01, K2= 0.03, I = 255; lx, ly are the means of images

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x and y; rx, ry are the variances of the corresponding images; rxy is the covariance; a  0, b  0 and η  0.

3.4

Curve Fitting Method

After a series of SSIM evaluation, results are computed; it is needed to analyze the relationship between the SSIM results and the GC control parameter ci. To compare the change trend, in some cases, all the data of SSIM results need to perform the normalization processing. However, some experiment results have also shown that this processing step can be omitted. Then, a Gaussian function can be used to fit the change trend of curve above. The least square method can be used to realize that fitting computation. In this paper, the form of the Gaussian function can be written by (8). The standard deviation r of Gaussian is employed as the IQ evaluation metric. Obviously, this parameter can reflect the decrease trend of a curve clearly. h . i q ¼ a  exp ðp  bÞ2 r2

ð8Þ

where p is the input variable, q is the output variable, and a, b, r 2 R.

4 Experiments and Discussions To test the validity of proposed metric, a series of simulation experiments is performed. The test images come from the nature scene image or the computer-generated image. Both the subjective IQ evaluation and the objective IQ evaluation are utilized in this section. The simulation programs are written by C and MATLAB in our PC with 1.70 GHz processor and 4G RAM.

4.1

Test Image Dataset

Figure 2 shows the experiment dataset samples. In Fig. 2, images (a)-1, (a)-2, (a)-3 are the data captured by a surveillance camera; the name of this dataset is “building”. Images (b)-1, (b)-2, and (b)-3 are the data recorded by a motion camera; the name of this dataset is “mountain”. Image (c)-1, (c)-2, and (c)-3 are the image processing results of enhancement and blur computation, where (c)-2 is the original image, while (c)-1 and (c)-3 are the enhancement and the blur results, respectively. The name of this dataset is “forest”. From Fig. 2, it can be seen that the image quality will decrease gradually in each dataset; and the image contents in (a) series and (c) series are almost same, while the image contents in (b) series are different.

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(a)-1

(a)-2

(a)-3

(b)-1

(b)-3

(c)-1

(c)-2

(c)-3

(b)-2

Fig. 2 Illustrations of experiment dataset samples. Image (a) series come from the Web site http:// www1.cs.columbia.edu/CAVE/; image (b) and image (c) series are captured by ourselves

4.2

Subjective Evaluation of the Image Dataset

The subjective IQ evaluation [12] should be made to build a benchmark for the objective IQ evaluation. The subjective evaluation is implemented by an ergonomics experiment: First, some images with different imaging qualities are accumulated. Second, parts of images in the dataset above are selected to build a typical dataset. Their IQs are evaluated by some experts. Third, these typical data above are used to train the subjects. If the subject has learnt the distinguishability of IQ evaluation, they will be asked to finish the subjective evaluation test of all the left images. In our experiment, eight volunteers are selected and more than 300 images are used in this experiment. All the experiments are performed in the darkroom of the astronaut research and training center of China.

4.3

Experiment Results

Figure 3 shows the curve fitting results of Fig. 2. Here, these curves recorded the relationship between the control parameter of GC and the evaluation result of SSIM. In Fig. 3, (a) is the fitting result of the image series “building”, (b) is the

Fig. 3 Curve fitting results of Fig. 2

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Table 1 Subjective and objective evaluation results of the images in Fig. 2 Image name

Evaluation method

Left image

Middle image

Right image

Building

Subjective evaluation Objective evaluation Subjective evaluation Objective evaluation Subjective evaluation Objective evaluation

4 5.929 5 5.649 4 5.814

3 6.075 3 5.739 3 6.107

1 6.519 1 6.021 1 7.821

Mountain Forest

result of the image series “mountain”, and (c) is the result of the image series “forest”. Regarding the computation of SSIM, for the sake of simpleness, we set a = 1.0, b = 1.0, and η = 0.0. From Fig. 3, it can be seen that the curve change trends of the images with different brightness contrast have some prominent differences: (a)-1, (b)-1, and (c)-1 have the slowest decrease trend, while (a)-3, (b)-3, and (c)-3 have the fastest decrease trend. Table 1 shows the evaluation results of proposed method. In Table 1, the subjective and the objective evaluation results of the images in Fig. 2 are given. Here, the “left image” points to (a)-1, (b)-1, and (c)-1; the “middle image” points to (a)-2, (b)-2, and (c)-2; and the “right image” points to (a)-3, (b)-3, and (c)-3. The subjective evaluation employs the 5-degree assessment method, where the degree “5” means the brightness contrast is best while the degree “1” indicates the brightness contrast is worst. The objective evaluation is the computation result of the brightness contrast metric. From Table 1, it can be seen that the objective IQ evaluation results have the same change trends with the subjective IQ evaluation results; i.e., their increase or decrease trends are same. These results can indicate the effectiveness of proposed method to some extent. Some conclusions may be made by the analyses of the calculation results above: First, the proposed brightness contrast metric can represent the image attribution to some extent even if its computational results is still related with the image content. Second, some other curve fitting methods can be used to improve that processing effect in future, such as the polynomial model or other time series features.

4.4

Discussions

The blind IQ evaluation design is one of most difficult problems in the IQ assessment research fields. A well-designed blind IQ evaluation metric at least has three characters: First, its evaluation process does not need any prior information comparing with other evaluation methods, such as the evaluation with full reference or the evaluation with reduced reference. Second, it should be or partly be independent to the image content; i.e. the image content will not influence its evaluation

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result seriously. Then, it can represent the inherent attribution of an image. Third, its processing cost should not be too high. Because the blind IQ evaluation metric has these merits above, it has been widely used in the fields of image processing and intelligent control applications. Regarding the proposed metric in this paper, its novelty comes from two facts: First, although it belongs to a kind of blind IQ evaluation metric, the classic evaluation method with full reference, i.e., the SSIM, is used in its computation step. Second, it uses a kind of dynamic change trend to characterize the inherent attribution of the degraded image. Many improvements still can be made when designing the IBC metric. We think the possible improvements can come from the GC method and the design of the curve fitting method. Other image enhancement measurement can be used to replace the GC and the machine learning-based method, or the statistics-based method can be used to improve the computation effect of the curve fitting computation.

5 Conclusion An IQ evaluation method of the brightness contrast is presented. Our design concept is that the gradual change effect of the contrast enhancement has a relationship with the image contrast itself. So by using the GC and the SSIM methods, an image dataset and its evaluation results can be gotten to describe the change trend of the contrast enhancement. Then, the IQ can be assessed by analyzing the difference of that change trend. The Gaussian function is utilized in this paper. Many experiment results have verified the correctness of proposed method. Acknowledgements This work is supported by the National Nature Science Foundation of China under Grant No. 61501016 and the open project of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect under Grant No. SKLIPR1713.

References 1. Filonenko A, Hernandez DC, Jo K-H (2018) Fast smoke detection for video surveillance using CUDA. IEEE Trans Ind Inform 14:725–733 2. Andrade J (2017) Improvement of visibility under foggy conditions. IEEE Lat Am T 15:1983–1987 3. Li Y, Wang Z, Dai G, Wu S, Yu S, Xie Y (2017) Evaluation of realistic blurring image quality by using a shallow convolution neural network. In: ICIA, pp 853–857 4. Yang G, Liao Y, Zhang Q, Li D, Yang W (2017) No-reference quality assessment of noise-distorted images based on frequency mapping. IEEE Access 5:23146–23156 5. Peli E (1990) Contrast in complex images. J Opt Soc Am 7:2032–2040 6. Tang J, Peli E, Acton S (2003) Image enhancement using a contrast measure in the compressed domain. IEEE Signal Proc Let 10:289–292

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7. Winkler S, Vandergheynst P (1999) Computing isotropic local contrast from oriented pyramid decompositions. ICIP 4:420–424 8. Zhou W, Yu L, Zhou Y, Qiu W, Wu M, Luo T (2018) Local and global feature learning for blind quality evaluation of screen content and natural scene images. IEEE T Image Process 27:2086–2095 9. Xu G, Su J, Pan H, Zhang Z, Gong H (2009) An image enhancement method based on Gamma correction. In: ISCID, pp 60–63 10. Moorthy AK, Bovik AC (2009) Visual importance pooling for image quality assessment. IEEE J Sel Top Signal Process 3:193–201 11. Wu C-C, Chang H-T, Tsai S-A, Lin C (2017) Least square fitting of Pollock model for tree detection and crown delineation. In: IGARSS, pp 5802–5805 12. Fan Z, Jiang T, Huang T (2017) Active sampling exploiting reliable informativeness for subjective image quality assessment based on pairwise comparison. IEEE Trans Multimed 19:2720–2735

Short-Term Public Transportation Passenger Flow Forecasting Method Based on Multi-source Data and Shepard Interpolating Prediction Method Wenzhou Jin, Peng Li, Weitiao Wu and Lanhui Wei Abstract The accurate passenger flow prediction is the base of bus scheduling and bus dispatching. Many factors, including internal factors and external factors, have great impact on the fluctuation of passenger flow. In the modern informationized bus system, many influencing factors became available by multi-source data. Current passenger flow prediction methods are mainly based on statistical predicting methods and machine learning methods. The implication of interpolating prediction method on passenger flow prediction is preliminary. Interpolating prediction method makes use of historical data; the prediction result is generally accurate, and the method is robust. Interpolating prediction method shows good performance and has mature application in other research areas. This paper makes use of historical passenger data and multi-source data; apply Shepard model to predict public transportation passenger flow. The result shows that Shepard prediction model has better performance than that of neural network (NN) model and support vector machine (SVM) model. The mean absolute percentage error (MAPE) has increased 7.5 and 3.43%; the MSP has increased 16 and 10.51% compared with NN and SVM and has lower dependency of parameters.





Keywords Intelligent transportation Urban transportation Public transportation Passenger flow forecasting Interpolation prediction



W. Jin  P. Li (&)  W. Wu  L. Wei School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, Guangdong, China e-mail: [email protected] W. Jin e-mail: [email protected] L. Wei e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_33

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1 Introduction Accurate and timely vehicle scheduling is the guarantee of the operating efficiency of the bus system, and the prediction of bus passenger flow is the data basis of bus scheduling. Especially in the network dispatching environment, information of passenger flow will have a great impact on the effectiveness of scheduling. Therefore, the accurate passenger flow forecasting is an important decision-making basis for bus operation planning and vehicle scheduling. However, public transportation passenger flow tends to fluctuate with time and seasonal changes. In real life, factors that affect public transportation passenger flow are numerous and complicated, such as the nature of working days, the nature of school, holidays, and weather. These factors make it difficult to accurately predict the bus passenger flow, which brings great uncertainty to the public transportation system [1], causing the unreliability of the public transportation system, finally reduces the attractiveness of the public transportation system to the passenger. According to the span of time dimension, passenger flow forecasting can be divided into two categories: long-term passenger flow forecast and short-term passenger flow forecast. For short-term public transportation passenger flow forecast, the methods currently used are divided into the following categories: time series analysis, statistical prediction, neural network (NN), support vector machine (SVM). Liu [2] analyzed the influence factors of the number of people getting on and off in the bus line and proposed to predict the passenger flow at the same time in the first three weeks and the first two days of the prediction period, as well as the passenger flow at the first three days of the same day, as the input of neural network; Jiang [3] put forward a kind of bus passenger flow forecasting method based on neural network; Deng [4] proposed a multi-core least squares support vector machine; Liu [5] proposed a short-term transit passenger flow wavelet forecasting method; Zhao [6] used wavelet analysis combined with neural network algorithm to predict passenger flow; Ren [7] adopted the wavelet neural network to predict short-term passenger flow of Beijing Subway; Zhang [8] proposed the prediction model of short-time passenger flow of bus stations with Kalman filter and gives the solution to the model; Gu [9] put forward the method of short-term prediction by time sequence model and established the auto-regressive-moving-average model to forecast the short-term total passenger flow of the hub site; Wei [10] adopted the method of empirical mode decomposition combined neural network to make a short-term prediction of subway passenger flow in Taipei; Liang [11] used the Grey model to predict the arrival rate of passengers on the bus routes; Wang [12] proposed the recent bus passenger flow prediction method based on the random gray ant colony neural network. These methods are also used in traffic flow and traffic status prediction, such as Wu [13] used the BP neural network to determine the traffic condition. Castroneto [14] considered the impact of accidents, adverse weather, and abnormal condition on short-term traffic flow on expressways, then used online support vector machine model to predict traffic flow.

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The forecasting methods used in the above studies are mainly focused on statistical methods and machine learning methods. The traditional statistical forecasting method simply analyzes the change rules of passenger flow from the perspective of data statistics and then makes statistical forecasting. The forecast quality heavily relies on the quality of statistical data. Therefore, these methods have low reliability. Traditional machine learning prediction methods improve the prediction accuracy and reliability, but they have the defects of complex model, large dependency of parameters and high dependency on training data quality. Interpolation prediction methods are also widely used in many research fields, which have good performance in accuracy and stability, and less dependency of parameters. Recently, the method of interpolation has preliminary research on traffic flow prediction and has achieved some results. Based on dynamic tensor model of traffic data and multi-modal analysis, Tan [15] proposed a tensor filling method based on matrix decomposition to solve the problem of short-term traffic flow prediction, and then proposed a tensor filling method based on multi-mode matrix decomposition. Wu [16] lately proposed another tensor filling method to predict short-term traffic based on dynamic tensor completion. Based on the research and practice, considering advantages and disadvantages of the existing bus passenger flow forecasting methods, this paper proposes a bus passenger flow forecasting method based on the Shepard interpolation algorithm. Experimental results show that compared with the traditional neural network and support vector machine, this method has high prediction accuracy and reliability, and has lower parameter dependence.

2 Predicting Bus Passenger Flow Based on Shepard Algorithm The main idea of this algorithm: the first step is to quantify and normalize the influence factors that have effects on passenger flow fluctuation, establishing a multi-dimensional influence factor matrix for the historical passenger flow data; the second step is to evaluate the correlation and sensitivity between each quantized value of influence factor and the value of passenger flow, eliminate the dimensions of low effectivity, and set weighting values of each dimension accordingly; The third step is to perform Shepherd interpolation prediction algorithm based on the historical data in the preprocessed influence factor matrix, achieving the prediction value of passenger flow of the target date. At the end of this paper, the quality assessment of the prediction results is carried out. Passenger flow forecasting process based on Shepard interpolation algorithm is shown in Fig. 1.

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Fig. 1 Flowchart of prediction model based on improved Shepard interpolation algorithm

Establishing Influence factor matrix

Evaluate the correlaƟon and sensiƟvity between influence factors and passenger flow

Gets the weighted matrix of influence factors

Perform Shepard interpolaƟon predicƟon method in the matrix

ForecasƟng model compare and conclusion

2.1

Shepard Interpolation Algorithm

The relationship between passenger flow and its influencing factors is a complex nonlinear relationship. It is difficult to describe the intrinsic quantitative relationship with precise mathematical functions. Based on interpolation prediction theory, the historical passenger flow data are discrete data point of the prediction model, and the relationship between passenger flow and affecting factors in a small range of parameters interval can be approximately described by simple linear function to predict the unknown data of given observation points [17]. Based on this theory, this paper proposes a passenger flow forecasting model based on Shepard interpolation algorithm. Shepard algorithm is also called Inverse distance weighted algorithm. This algorithm is a prediction method based on similarity. When two objects have similar influence factors, the target value tends to be similar. In the problem of passenger flow prediction, dates with higher influence factors similarity tend to be more similar in passenger flow state. This prediction algorithm performs weighted average interpolation based on the influence factors similarity between the prediction point and the historical data point, and the more similar the prediction point, the greater the weighting [18, 19].

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The Shepard algorithm has two preconditions: (1) The correlation between the predictive factor and the target values is statistically significant. (2) The historical sample set between the predictor and the target should be adequately representative. The first precondition can be verified by checking the correlation between historical passenger flow data and each predictive factor. This paper evaluates the affect efficiency between the impact factor and the historical passenger flow with correlation coefficient. As for the second precondition, we use recent historical passenger flow data in a long-time span, which can be regarded as full-sampled and adequately representative. Thanks to modernized bus information environment, historical information of passenger flow of the large time span, fine time granularity, and specific routes can be collected.

2.2

Establishing of Influence Factor Matrix

Bus passenger flow of a period is affected by many factors, including day of year, workday/holiday, time of day, weather, temperature, and other factors. Therefore, this paper uses the methods of feature engineering to quantificat the influence factor in study period, forming a multidimensional vector of influence factors [20]. And then, eliminate dimension effect through normalization. And then, the correlation test is carried out to retain the significant influence factors. Then we use sensitivity analysis method to determine the impact factor’s contribution to the diversity of different influence factors vector (this process will be detailed in the following pages). The influence factors matrix established with above-mentioned steps can serve as a data basis of the Shepherd interpolation prediction algorithm. In this matrix, the shorter the distance between the influence factors vector, the closer the bus passenger flow value is. After the feature engineering processing, the problem of passenger flow prediction is transformed into interpolation problem in a multi-dimensional influence factor space, which is applicable for Shepard interpolation algorithm.

2.3

Improved Shepard Prediction Model

Set the sample influencing factor sequence as fxði; j; tÞji ¼ 1; . . .; n; j ¼ 1; . . .; m; t ¼ 1; . . .; 24g. Set historical passenger flow sequence as fyði; tÞji ¼ 1; . . .; n; t ¼ 1; . . .; 24g. n denotes the number of samples. m denotes the number of influencing factors. xði; j; tÞ is the ith quantized value of the jth influencing factor in period t. yði; tÞ is the historical passenger flow volume of the ith sample in period t. To eliminate the dimensionality effect of influencing factors, the effect factors should be normalized with following formula.

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x0 ði; j; tÞ ¼

xði; j; tÞ  E ðxðj; tÞÞ Sðxðj; tÞÞ

ð1Þ

In this formula, Eðxð jÞ and Sðxð jÞÞ are the mean value and standard deviation of the jth sample of influence factors. The correlation coefficient of the influence factor xðj; tÞ on the target value yðtÞ is donated by r ðj; tÞ. The correlation coefficients of the candidate influencing factors and the target value were calculated to obtain the correlation coefficient vector RðtÞ ¼ ½r ð1; tÞ; . . .; r ðj; tÞ; . . .; r ðm; tÞ. If r ðj; tÞ is positive, the jth influence factor is positively correlated with the target value at time t, and vice versa. Obviously, greater the jr ðj; tÞj, the greater the influence of this factor on the target value. According to the empirical value of correlation theory, when jr ðj; tÞj [ rmin ¼ 0:3, it is considered that the factor is significantly correlated to the value of passenger flow of the period; otherwise, it is irrelevant, and the weight should be set to 0. The Shepard method needs to evaluate the distance (generally Euclidean distance) of different xði; j; tÞ to determine the interpolation weight of each sample point. As for public transport passenger flow prediction problem, different influencing factors have different contribution to the distance of different xði; j; tÞ; for example, workday/holiday influence factor has greater influence on passenger volume in morning peak hours than that of temperature. To take this situation into consideration, this paper uses the sensitivity analysis method and distance between groups to determine the weight of each influencing factor [21]. Firstly, classify the target value into groups according to each discrete values of each influence factor, calculating the mean value of each group of target value. Then, the weight of each influence factor in time t can be achieved by dividing maximum difference of the mean value of each group by maximum influence factor value difference. The calculating method of weights of each influence factor is as follows.A0 ði; j; tÞ denotes the weighed x0 ði; j; tÞ. Range (A′(j, t)) denotes the range of all values of A′(j, t). 8 0 0 > ( x ði; j; tÞ0  0wðj; tÞ 0 0 < A ði; j; tÞ ¼ maxðEðy ðA ¼ah ;tÞEðy ðA ¼ak ;tÞÞ if r ðj; tÞ  0:3 ð2Þ RangeðA0 ðj;tÞÞ > : wðj; tÞ ¼ 0 if r ðj; tÞ\0:3 The basic idea of Shepard’s prediction is to interpolate the target value of a given influence factor vector with historical global sample points with the inverse distance between influence factor vectors as weight. 8 dib > < wi ¼ s ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi m  2 P 0 ^0 > : di ¼ j¼1 wðj; tÞ A ði; j; tÞ  A ðj; tÞ

ð3Þ

Short-Term Public Transportation Passenger Flow …

^yðtÞ ¼

287

n X w yði; tÞ Pi n i¼1 wi i¼1

ð4Þ

di is the distance between the influence factor of the ith day and the influence factor of the predicted target, wi is the weight of the ith historical value, and b is the SP model parameter b is usually a constant greater than 1. The larger the value is, the more flat the fitting surface is. On the contrary, the smaller the value is, the rougher the fitting surface is. ^yðtÞ denotes the predict passenger flow volume of t period. b represents the degree of influence of the phase difference between the influence factor vectors on the target value. The key of Shepard model is to determine the optimal value of model parameter b can be optimized by historical data within empirical range [18]. minf ðbÞ ¼

n X

j^yði; tÞ  yði; tÞj s:t: 1  b  10

ð5Þ

i¼1

yði; tÞ denotes the ith real value of period t, ^yði; tÞ denotes the predict passenger flow volume of the ith sample of t period. The following four indicators are generally used to evaluate the prediction results. n 1X MAE ¼ ð6Þ j^yðtÞ  yði; tÞj n i¼1 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn yð t Þ  yð t Þ Þ 2 i¼1 ð^ MSE ¼ n MAPE ¼

MSP ¼

 n   1X ^yðtÞ  yðtÞ  n i¼1 yð t Þ 

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  uP  u n ^yðtÞyðtÞ 2 t i¼1 yðtÞ n

ð7Þ ð8Þ

ð9Þ

^yðtÞ denotes the predicted value of period t and yðtÞ denotes the real value of period t. The mean absolute error (MAE) indicates the overall average deviation of the predicted value. The mean square error (MSE) indicates the overall reliability of the prediction. The mean absolute percentage error (MAPE) represents the relative average deviation. The mean square percentage error (MSP) indicates relative reliability.

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3 Case Study To verify the algorithm proposed by this paper, the passenger flow of route 218 in Guangzhou of each operating hour between August 1, 2014, and December 31, 2014, are selected as experimental data. The passenger flow data of December 2014 are taken as test data. Passenger flow is affected by the season, so the first influence factor in this article is the day of year denoted by A1 . Workday/holiday influence factor heavily affect passenger flow, the workday influence factor is set to 0, the holiday influence factor is set to 1, denoted by A2 . School day/holiday has a greater impact on the passenger flow of students and teaching and administrative staff; school days are set to 0, and student holiday is set to 1, denoted by A3 . The temperature (unit, °C) might influence passenger flow, denoted by A4 . Extreme weather impacts volume of certain passengers. In this paper, the extreme weather such as heavy rains on the same day is set to 1, and the remaining time is set to 0, denoted by A5 . Finally, the influence factors vector is denoted by ½A1 ; A2 ; A3 ; A4 ; A5 . Table 1 shows some examples of quantified influence factor values after partial date normalization. Due to the diversity of travel purposes and the complexity of the passenger flow structure, the impact of each influencing factor on passenger flow of a certain line is different. Figure 2 is drawn based on the correlation matrix of each influence factor of each time segment. The dotted line in the figure indicates the correlation threshold, and if the correlation is greater than this threshold, the correlation between this influencing factor and the passenger flow is considered significant; otherwise, it is not significant. It can be seen from the figure that the seasonal fluctuation of passenger flow is mainly concentrated in the afternoon off-peak hours and the evening off-peak hours. The working day/holiday influence factor has a greater impact on the morning and evening peak hours, the effect on the morning peak hours is greater than that of the evening peak hours, and there is a certain effect on the noon passenger flow. The effect of the nature of the workday/holiday is greater than that of school day/holiday. Furthermore, the temperature has great influence on the passenger flow in the afternoon off-peak hours, but the impact of the extreme weather on the passenger flow can be neglected for this route. In conclusion, the weight of the quantized influence factors is added to the influencing factor sequence according to the algorithm, and then, the weighted influencing factor sequence is substituted into the Shepard model to predict the target date. Table 1 Quantified date properties

Date

A1

A2

A3

A4

A5

2014/12/24 2014/12/25

0.9611 0.9667

0 0

1 1

0.20 0.16

0.5 0.5

Short-Term Public Transportation Passenger Flow …

Fig. 2 Correlation between each influence factor and the passenger flow and its weight

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Fig. 2 (continued)

Table 2 shows the quality of the prediction models with different b values. The error of the prediction results decreases rapidly and then slowly increases with the increase of the b value, and the optimal b value is 3. To verify the validity of the proposed algorithm, a BP neural network and support vector machine model are established to predict the passenger flow. The training data are the influence factors vector used by the algorithm and its corresponding passenger flow volume. Based on the same data set, three algorithms are used to predict the passenger flow volume on same target dates and evaluate the results with same index. This paper selected a typical working day and a typical holiday as an example, and the results are shown in Fig. 3. As can be seen from Fig. 3a, the accuracy of the three prediction algorithms is higher due to the relatively stable passenger flow during the working day, but Shepard algorithm is slightly higher than the other two algorithms. As shown in Fig. 3b, the accuracy and reliability of the Shepard interpolation prediction algorithm are obviously higher than that of the neural network algorithm, which is slightly higher than that of the support vector machine algorithm because of the multiple and complex

1

190.22 13.59 256.03 22.11

b

MAE MAPE (%) MSE MSP (%)

177.28 12.67 230.27 19.31

2 176.29 12.66 227.69 19.06

3

Table 2 Quality of prediction results of different b values 183.32 13.22 236.64 19.87

4 185.68 13.41 238.98 20.11

5 187.83 13.58 241.29 20.33

6 189.83 13.73 243.58 20.54

7

191.76 13.88 245.88 20.75

8

193.67 14.02 248.2 20.95

9

195.61 14.16 250.53 21.15

10

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Fig. 3 Passenger flow predictions comparison at typical workday and typical holiday

factors affecting the passenger flow data of the holiday. Due to the less training samples and the existence of extreme data, the neural network model and support vector machine model are susceptible to affect the prediction accuracy. Shepard interpolation prediction algorithm reduces the noise in the process of a weighted average of the data on the predict results. The neural network model needs to determine the type of neural network, the neural network layers, the number of nodes in each layer, the excitation function, the initial weights of neural network, and other related parameters in the process of model establishment. Support vector machine model also needs to determine the type of model, the type of kernel function, and other relevant training parameters. Compared with the other two algorithms, the Shepard interpolation prediction algorithm has only a b value that affects the fitting degree and the parameter dependence is small. Therefore, it is easy to calibrate the optimal prediction algorithm model. Given the above, the neural network algorithm and SVM algorithm have strong dependence on parameters, and the selection of training samples is very strict. They

Short-Term Public Transportation Passenger Flow … Table 3 Indexes of prediction quality comparison between different predict method

293

Method

MAE

MSE

MAPE (%)

MSP (%)

Shepard NN SVM

176.29 238.51 252.4

227.69 307.99 437.3

12.66 20.16 16.09

19.06 35.07 29.57

are also susceptible to noise data. But Shepard interpolation prediction algorithm has obvious advantages in these two aspects, and it is superior to the other two algorithms in accuracy and reliability. Indexes of prediction results of different models are shown in Table 3.

4 Conclusion Bus system is an important part of urban passenger transport system, and passenger flow forecasting is an important decision basis of bus scheduling. In this paper, we use Shepard interpolation prediction algorithm to establish the prediction model and predict it based on the historical short-term passenger flow data, and then compared the result with that of traditional neural network algorithm and support vector machine algorithm in the same dataset. The results show that the algorithm has the advantages of high precision, high stabilization, and small parameter dependence, which proves the correctness and validity of the model. It can take an accurate passenger flow forecasting at any period in the near future for bus dispatching and provide basis for reducing the cost of bus operation and improving service level.

References 1. Wu W (2015) The robustness and control strategies of bus network schedule coordination with uncertainty. South China University of Technology 2. Liu C, Zhang YQ, Chen HR (2008) Transit stations temporal getting on/off flow forecasting model based on BP neural network. Transp Res 5:186–189 3. Jiang P, Shi Q, Chen WW (2009) Forecast of passenger volume based on neutral network. J Wuhan Univ Technol (Transp Sci Eng) 33(3):414–417 4. Deng H, Zhu X, Zhang Q (2012) Prediction of short-term pubic transportation flow based on multiple-kernel least square support vector machine. J Transp Eng Inf 10(2):84–88 5. Liu K, Li W, Zhao J (2010) Study on wavelet forecast method for short-term passenger flow. J Transp Eng Inf 8(2):111–117 6. Zhao S, Ni T, Wang Y (2011) A new approach to the prediction of passenger flow in a transit system. Comput Math Appl 61(8):1968–1974 7. Ren CL, Cao CX, Li J (2011) Research for short-term passenger flow forecasting based on wavelet neural network. Sci Technol Eng 11(21):5099–5103 8. Zhang C, Song R, Sun Y (2011) Kalman filter-based short-term passenger flow forecasting on bus stop. J Transp Syst Eng Inf Technol 11(4):154–159

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9. Gu Y, Han Y, Fang XL (2011) Method of hub station passenger flow forecasting based on ARMA model. J Transp Inf Saf 29(2):5–9 10. Wei Y, Chen MC (2012) Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks. Transp Res Part C Emerg Technol 21(1) 11. Liang XL (2012) Prediction method research of dynamic mass transit passenger flow. Urban Public Transp 4:33–34 12. Wang QR, Zhang QY (2012) Forecasting of short-term urban public transit volume based on random gray ant colony neural network. Appl Res Comput 29(6):2078–2080 13. Wu WT, Jin WZ, Lin PQ (2011) The method of traffic state identification based on BP neural network. J Transp Inf Saf 29(4):71–74 14. Castro-Neto M, Jeong YS, Jeong MK (2009) Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions. Expert Syst Appl 36(3):6164–6173 15. Tan HC, Feng GD, Feng JS (2013) A tensor-based method for missing traffic data completion. Transp Res Part C Emerg Technol 28(3):15–27 16. Tan HC, Wu YK, Shen B (2015) Short-term traffic prediction based on dynamic tensor completion. Beijing Institute of Technology 17. Zhong EJ, Huang TZ (2004) Numerical analysis 18. Jin JL, Wei YM, Ding J (2002) Shepard interpolation model for predicting annual runoff. J Yangtze River Sci Res Inst 19(1):52–55 19. Zhang F, Lv ZY, Zhao XP (2010) Novel method based on sequence Shepard interpolation for structual reliability analysis. J Mech Eng 46(10):176–181 20. KP Murphy (2012) Machine learning: a probabilistic perspective. MIT Press 21. Hu D, Cai Y, Xing Y (2008) On sensitivity analysis. J Beijing Norm Univ (Nat Sci) (01):9–16

The Color Choices of Chinese Pilots for Aircraft Cabin Interior Jian Du, Chunmei Gui, Xiaochao Guo, Yanyan Wang, Qinglin Zhou, Yu Bai, Guowei Shi and Duanqin Xiong

Abstract Objective To investigate use requirements of pilots for inner color in aircraft cabin design. Methods Compared to the light and dark color system boards with rank-order method, 198 Chinese pilots participated in the experiment. Pilots were asked to rank 24 pieces of color boards according to the fitness as aircraft cockpit interior and select their favorite colors in daily life from standardized color cards. Results (1) In light color system, the lowest grades were E and C boards, and the highest grades were L and K. At the same time, the pilots’ favorite to 12 light colors had statistical significance (P < 0.001). (2) In dark color system, the lowest grades were E′, H′, and A′ boards, and the highest grades were L′ and K′. The pilots’ favorite to 12 dark colors had also statistical significance (P < 0.001). (3) Pilots’ favorite to daily colors had no significant effect on their choice in cockpit color. Conclusions Through the pilots’ comparing color boards and questionnaire investigation, the decorating colors that fit control devices and cabin walls in aircraft were proposed. Pilots’ favorite to daily colors had no effect on their choosing colors for cockpit decoration.





Keywords Color perception Pilots Aircraft cockpit interior Man–machine environment Color preference Human factor engineering Psychology





1 Foreword Aircraft cabin interior is a special work environment in long-time flying for pilots. How to promote mental adaptive ability of flying has become an interest of aeromedical ergonomics [1]. Ninety percent of information interaction is transferred J. Du  C. Gui  X. Guo  Y. Wang  Q. Zhou  Y. Bai  G. Shi  D. Xiong (&) Institute of Aviation Medicine PLAAF, Beijing 100142, China e-mail: [email protected] J. Du e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_34

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by vision; therefore, it is significant of improving man–machine system reliability to study perception characteristics of man–machine environment and optimize the color environment of man–machine system. During color perception, a different color would certainly have an effect on psychology. Physiological changes appeared by psychological changes [2]. Interior color and texture directly affect vision fatigue, comfort, and emotional change of pilots [3]. Proper cabin interior and related control device color will alleviate flight fatigue, increase pilots’ comfort, and promote the performance of flight [4].

2 Methods 2.1

Subjects

One hundred and ninety-eight male pilots were selected as subjects with normal color sense. Their average age was 31.73 ± 3.48 years, and flight time was 1272.5 ± 526.7 h.

2.2

Color Palette and Experimental Device

On the basis of investigation and research of aircraft cabin interior color from home and aboard, light and dark colors were chosen to set two suites of test color palettes which included 12 colors of every color palette. The material of color palette was made of metal with the size of 10 cm  19 cm. It was produced by specialized paint industry with dedicated color of the research in direction of FED-STD-595C [5] and GB/T 3979-2008 [6]. Light colors included 10 light greys and 2 camels numbered A– L as well as dark colors include 10 dark greys and 2 camels numbered A′– L′ as shown in Fig. 1.

Fig. 1 Color palette used in the test

The Color Choices of Chinese Pilots …

297

Fig. 2 Testing scene with light box

National standard color card was used for the choice of pilots’ favorite color (Fig. 1), and a questionnaire was used for the experimental records. Judge II standard multiple light box was used in the test. The light source in box was set at D65 (6500K), which simulated the average sunlight in the north. The color palettes were placed in the box and ranked under the light source (Fig. 2).

2.3

Test Procedure

Classical grade ranking method was adopted in color preference test. Before ordering, the detector “shuffled” the palette to make sure of randomization. The procedure of the test was as follows: (1) Fill in the background information of every pilot. (2) Pilot chose the favorite color form national standard color card. (3) Pilots rank two suites of test color palettes according to their flying experience and realization. Dark color grade of aircraft cabin control device and light color of grade cabin bulkheads are ranked. (4) Color choice and suggestions from pilots

2.4

Statistical Analysis

The grades of color palettes ranked by pilots were taken as a statistical index. The lower grade the color was rated, the more suitable for aircraft cabin interior it was.

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3 Results and Analysis 3.1

Daily Preference of Color of the Pilots

Blue was the favorite color of most pilots in daily life as shown in Fig. 3.

3.2

The Choices of Light Color by Pilots

Light colors were mainly used for aircraft cabin bulkhead interior. The color grades of the 12 light colors ranked by pilots were listed in Table 1. Statistical results were shown in Table 2, which indicated pilots had a different favorite degree on 12 colors of light color series. The lowest grade of 12 color palettes was E palette and C palette in Table 1. It was indicated that from the view of pilots, E and C palettes were the most suitable color for aircraft bulkhead interior. The highest grade palette was L palette and K palette which indicated they were the most unsuitable color for aircraft bulkhead interior in this study.

3.3

The Choices of Dark Color by Pilots

Dark colors were mainly used for control devices in aircraft cabin. The color grades of the 12 dark colors ranked by pilots were presented in Table 3. Statistical results were shown in Table 4, which indicated pilots had different favorite degrees on 12 colors of dark color series. The lowest rank grade was E′, H′, and A′ palettes in Table 3. It was indicated that from the view of pilots, these palettes were the most suitable match color for Fig. 3 Daily color preference of the pilots

Average grade Standard deviation Z Z + 0.86

6.59 2.16 −0.021 0.841

5.85 2.13 0.150 1.012

4.82 3.77 0.392 1.254

Color palettes in test A B C 5.30 2.06 0.276 1.138

D

Table 1 Twelve-color-grade rank results of light color series

4.43 3.33 0.490 1.352

E 5.17 1.97 0.307 1.169

F 8.17 2.78 −0.390 0.472

G 6.98 2.53 −0.111 0.751

H

5.74 3.83 0.175 1.037

I

5.44 1.79 0.243 1.105

J

9.80 3.07 −0.840 0.022

K

9.86 3.24 −0.862 0.000

L

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Table 2 Test results on the difference of favorite degree in 12 colors of light color series Statistical index

Friedman test

Kendall’s test

N df Chi-square P

198 11 594.275 0.000

198 11 149.847 0.000

Table 3 Twelve-color-grade rank results of dark color series Color palettes in test A′

B′

C′

D′

E′

F′

G′

H′

I′

J′

K′

L′

Average grade

4.44

5.76

5.24

6.38

3.88

4.59

6.47

4.15

6.97

9.48

10.6

10.0

Standard deviation

3.4

1.8

2.0

2.2

1.8

2.2

2.0

2.6

2.0

2.3

2.3

2.1

−1.13

−1.03

Z

0.63

0.06

0.25

0.05

0.69

0.54

0.02

0.73

−0.10

−0.99

Z + 1.13

1.76

1.19

1.38

1.18

1.82

1.67

1.15

1.86

1.03

0.14

Table 4 Test results on the difference of favorite degree in 12 colors of dark color series

0

0.10

Statistical index

Friedman test

Kendall’s test

N df Chi-square P

193 11 1.159E3 0.000

193 11 1.159E3 0.000

control device in aircraft cabin. The highest rank grade was L′ and K′ palettes which indicated that they were unsuitable for control device in aircraft cabin.

3.4

The Choices of Color Without Influence by Daily Preference

It was analyzed whether the choices of color for aircraft cabin interior by pilots were influenced by the daily preference of the color of their own. The results were listed in Table 5 for the 12 light colors and Table 6 for the 12 dark colors. It was found that both the light colors and the dark colors had no statistical difference as shown in Table 5. It was indicated that there was no influence of pilot’s daily preference of color on the 24-color-grade ranking. In other words, pilots chose the aircraft interior color according to the work environment but had no influence of daily color preference.

The Color Choices of Chinese Pilots …

301

Table 5 Relationship of the light color ranking to the daily preference of color Color palettes in test Chi-square

A

B

C

D

E

F

G

H

I

J

K

12.25

7.28

9.87

8.59

5.54

3.06

8.49

11.60

7.20

5.06

4.82

L 7.07

df

6

6

6

6

6

6

6

6

6

6

6

6

P

0.06

0.30

0.13

0.20

0.48

0.80

0.20

0.07

0.30

0.54

0.57

0.31

Table 6 Relationship of the dark color ranking to the daily preference of color Color palettes in test A′

B′

C′

D′

E′

F′

G′

H′

I′

J′

K′

L′

Chi-square

3.70

2.87

5.49

0.27

9.32

3.26

11.22

4.04

5.04

7.39

4.22

8.82

df

6

6

6

6

6

6

6

6

6

6

6

6

P

0.72

0.83

0.48

1.00

0.16

0.78

0.08

0.67

0.54

0.29

0.65

0.18

4 Conclusions Proper color of cabin interior and control device will produce flying fatigue, improve comfort and satisfaction, as well as promote work efficiency. A psychological and human factor engineering survey was conducted to probe use requirements of pilots for inner color in aircraft cockpit design. Twelve light color palettes and 12 dark color palettes were made by paint industry and used in the test. There were 198 Chinese male pilots participating in the experiment who compared the color palettes in the light or dark color systems with rank-order method in psychology on the basis of color functionality in aircraft cabin excluding the daily preference of color as possible. The main findings in the present study were as follows: (1) Most of the pilots were blue preference (56.57%) in daily life. (2) The most suitable color for aircraft cabin bulkhead interior color was E and C palettes in light colors, i.e., light gray such as FS 36463, FS 36473 or FS 36628, FS 36492, FS 36622 in FAA FED-STD-595C [5]. (3) The most suitable color for control device in aircraft cabin was E′ and A′ palettes in dark colors, i.e., dark gray such as FS 36173, FS 36118 or FS 36176, FS 36152 in FED-STD-595C [5]. (4) The choices of color for aircraft cabin interior by pilots were not influenced by the daily preference of color of themselves own. Compliance with Ethical Standards The survey was approved by the Academic Ethics Committee of Institute of Aviation Medicine PLAAF. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Wu Y, Zhang X (2009) Experiment study of modal and algorithm for color perception in human-machine system. Harbin Institute of Technology, Harbin 2. Zhang B (2010) Research on modals and algorithms of color vision perception. Harbin Institute of Technology, Harbin 3. Fang L, Fang X (2006) Ergonomic and color design analysis of numerical control machine. Wuhan University of Technology, Wuhan 4. Dinges DF, Grace R (1998) PERCLOS: a valid psychophysiological measure of alertness as assessed by psychomotor vigilance. US Department of Transportation, Federal Highway Administration 5. FED-STD-595C (2008) Color used in government procurement 6. GB/T 3979–2008 (2008) Methods for the measurement of object color. China Standard Press, Beijing

Part IV

Research on the Man-Machine Relationship

Comparative Study on Cab’s H Point Design Model Based on Human Factors Engineering Jiangli He, Chenxuan Yang, Tong Zhu, Xiaoyong Wang and Yueqi Hu

Abstract In order to determine a suitable relative location of AHP and H point in the vehicle cab and improve the SAE standard design model, this paper modeled the H point which is suitable for Chinese according to human factor engineering principle. First, this paper optimized the location of H point by theoretical analyzing. It can be found that the dimension parameter of human body had an impact on H point location. Besides this, when compared this relationship with the SAE empirical formula, the reasonable ranges of vertical dimension between H point and AHP point are different. Then JACK was used to create Chinese male’s digital model models and their human percentile was set to 5, 50, and 95% which are representative. These models were used to simulate the location of AHP point and H point by evaluating, Comfort, Vision Zones, and Reach Zones. Least square method was used to process the location data and find the optimal H point. The result showed that the model to design H point for Chinese male in this paper was more reasonable than that in SAE. It can be used to design the driving cab for Chinese vehicles. Keywords Human factor engineering H point JACK



 Human percentile  Vehicle AHP

1 Introduction Human body’s H point is the abbreviation of hip point which is the hip joint location of two-dimensional or three-dimensional human body model. In another word, it is the connection of leg center line and human trunk line. H point is an important benchmark in designing cab. The location of H point is closely related to driving comfort, handling stability and vision field, and it is also the first factor that should be considered when designing the vehicle cab. J. He (&)  C. Yang  T. Zhu  X. Wang  Y. Hu School of Automobile, Chang’an University, Xi’an 710064, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_35

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SAE J1517 recommended empirical formula to determine H point location according to different human percentile [1]. This model is suitable for the occident. However, Chinese human body dimensions are different from those of the occident, so it is probably that the H point design is unsuitable for Chinese. Jinlin Huang, 2000 optimized the H point but they only analyzed the comfortable area based on the model recommended by SAE. They did not compare it with the H point of Chinese people [2]. Now, there is only procedure for Chinese people H point determination instead of normative recommended models [3]. Moreover, the existing evaluation index is inaccuracy because of the subjective judgment and complex spatial relationship. Besides, the difference of subjects’ feeling and the content of their endurance can also influence the evaluation of the comfort [4]. This paper analyzed Chinese male body’s comfortable sitting posture referred to Human Factors Engineering Principles. The location data of AHP point and H point were simulated, and a high precision mathematical model was fitted by using the least squared method. Lastly, this model was compared with the model recommended by SAE to verify its reliability.

2 Creation and Comparison of H Point Design Theory Model 2.1

Analysis of Human Comfortable Sitting Gesture System Model

This study started with adjusting the drive comfortable joint angle to optimize the H point location. The AHP was considered as original point of the two-dimension coordinate, and then the human body model with sitting gesture was created. The AHP point is accelerator heel point, specifically, the contact point of human body model’s heel and cab floor when the acceleration pedal is released (Fig. 1). Because the comfortable joint angle range is used universally in different countries (Table 1), this paper used the data to study the relationship as well. The meaning of each lever is explained in Table 2.

2.2

The H Point Empirical Formula Recommended by SAE

SAE J1517 recommended a group of empirical formula based on plenty of experiment to determine the H point under the circumstance that the height of H point is known. Here are the empirical formula of 5, 50, and 95 human percentile’s H point location that recommended by SAE.

Comparative Study on Cab’s H Point Design …

307

Fig. 1 Model of human body’s comfort sitting gesture

Table 1 Range of comfortable joint angle No. The angle between the trunk axis and the vertical line The angle between the thigh axis and the trunk axis The angle between the shank axis and the thigh axis The angle between the shank axis and the pedal plane The angle between the upper arm axis and the trunk axis The angle between the lower arm axis and upper arm axis The angle between the hand central line and the lower arm axis The angle between the pedal plane and the horizontal plane The angle between thigh axis and the horizontal plane

The minimum angle (°)

The max angle (°)

a1

3

20

a2 a3

90 95

115 135

a4

78

105

a5

0

50

a6

80

130

a7

170

190

a8

40

70

a9

2

12

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Table 2 Meaning of each lever of human body’s comfort sitting gesture model Label

Meaning

L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L11 a

The length of H point to the neck joint The length of H point to the shoulder joint The length of the knee joint to H point The length of the knee joint to the ankle The length of the elbow joint to the shoulder joint The length of the wrist joint to the elbow joint The length of the wrist joint to the palm The vertical dimension of ankle to pedal plane The length of AHP to the perpendicular which was mentioned in the description of L8 The length of AHP to the ankle The length of the neck to the top of the head The angle between the connection line of heel point and AHP and pedal plane

X95 ¼ 913:7 þ 0:672316Hz  0:00195530Hz2

ð1Þ

X50 ¼ 793:7 þ 0:903387Hz  0:00225518Hz2

ð2Þ

X5 ¼ 692:6 þ 0:981427Hz  0:00226230Hz2

ð3Þ

In the empirical formula, Xi is the horizontal distance between AHP and H point and the Hz is the vertical height of H point to AHP (mm).

2.3

Comparison of Different H Point Location Line Design Models

After analyzing the relationship between the angles of lower limbs in human body’s comfort sitting gesture model, the following equation can be found. a3 þ a9 ¼ a4 þ a8

ð4Þ

The coordinate of H point can be found according to their relative location. AHP was set to be the origin of coordinates (0, 0) and H point was (XH, ZH). Their geometrical relationship is followed.

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Fig. 2 Comparison of H point curve before and after optimizing

XH ¼ L10  cosð180  a8  aÞ þ L4  cosð180  a3  a9 Þ þ L3  cos a9 ZH ¼ L10  sinða8 þ aÞ þ L4  sinða3 þ a9 Þ  L3  sin a9

ð5Þ ð6Þ

The date ranges of a3, a4, a8, and a9 referred to Table 2, and the value of a is generally 53°; different drivers have different human percentile, and the value of L3, L4, L10 were according to the sizes of a Chinese adult with national standard GB 1000–1988. It can be known from the equation above that when two of the angle a3, a4, a8, a9 were constant, the rest two were changed among their comfort range so that a curve of H point can be plotted. X95 ¼ 701:94 þ 1:2556Hz  0:0029466Hz2

ð7Þ

X50 ¼ 639:76 þ 1:2828Hz  0:0032035Hz2

ð8Þ

X5 ¼ 583:89 þ 1:3045Hz  0:0034836Hz2

ð9Þ

Figure 2 shows the relationship between the plotted H point curves above and those calculated by SAE empirical formula.

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3 Simulate Experiment Design of Human Factor Engineering 3.1

Design of Simulate Experiment

The Jack human simulation system was developed at the Center for Human Modeling and Simulation at the University of Pennsylvania. It contains functions of 3-D simulation, digital modeling, human factor, and so on [5]. (1) Create the driver model Jack is able to create accurate digital model in different dimensions [6]. Usually, 5, 50, and 95 human percentile were used to express short, medium, and tall three physical body model in experiment and simulation [7]. In this study, digital model was used to create 5, 50, and 95% dimension of Chinese driver [8, 9]. (2) Create the cab model The cab model in this study is in keeping with the Class A recommended by SAE. It mainly contains seat, steering wheel, pedal, instrument panel, and other devices by 3-D software. The humanoid model of the rod system under the above-mentioned driver’s sitting posture is constructed to carry out ergonomics simulation analysis such as Comfort, Vision, and Reach Zones. The origin of the coordinates is AHP.

3.2

Create the H Point Design Simulate Parameters

After creating different human percentile drivers, the experiment could be conducted in the software. The vertical distance Hz between H point and AHP is the independent variable. The joint angle was adjusted among the comfort range under different value of Hz, and then the most comfortable angle was simulated by Comfort Assessment. Furthermore, the visible range and reachable region were also considered under each sitting gesture.

3.3

Analysis

This study was followed control variate method. Different value of Hz decided different vertical distances between H point and AHP. The most comfortable value of a4 and a8 was decided first, and then the value of a9 was also be decided. The maximum value of X was calculated lastly. The comfort evaluation was consequently made by Comfort Assessment. If a3 is not in the comfort range, the distance X should be decreased until it reaches its maximum value. During this process,

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the most suitable value of X was achieved. Lastly, the Vision and Reach Zones should be judged as well. If the value of them is reasonable, the experiment was ended. The value of X was the vertical distance between H point and AHP.

4 Create and Verify the Model of Vehicle’s H Point Design Based on Human Factor Engineering This study adjusted the comfortable joint angle in the simulation environment created by Jack. After calculating, Jack output the data table of comfort analysis, visible analysis, and reach analysis. The most optimized horizontal distance X for each vertical distance Hz was calculated as well. The result is shown in Table 3. MATLAB was then used to analyze the experimental data by the method of curve fitting so that the model that determines the most comfortable AHP location for Chinese male driver was figured out. This model was verified by coefficient of determination, and the fitting rate is over 98%. It proved that this model is reliable. The fitting polynomial and the linear model were shown in Fig. 3. X95 ¼ 1080  1:317Hz þ 0:0008106Hz2

ð10Þ

X50 ¼ 1052  1:520Hz þ 0:00091Hz2

ð11Þ

X5 ¼ 1019  1:766Hz þ 0:01375Hz2

ð12Þ

In addition, in Fig. 3, it depicts the curve of SAE empirical formula to illustrate the difference.

Table 3 Comfort H point location of different percentiles The vertical distance of AHP and H point Hz (mm)

The horizontal distance of AHP and H point X (mm) 95% 50% 5%

220 240 260 280 300 320 340 360 380 400

827.8 809.5 791.1 784.3 764.7 737.2 720 707.4 697.8 687.2

752.3 743.4 734.2 698.2 674.7 651.3 633 626.7 611.8 588.4

697.7 676 651.4 626.4 615.7 597 580.7 558.3 546.5 532.64

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Fig. 3 H-spot alignment of Chinese with SAE

It can be concluded that as human percentile declines, the horizontal distance between AHP and H of Chinese driver is also decreasing. This tendency is in line with the SAE empirical but the slop is not so big. As the vertical distance between AHP and H point declines, the horizontal distance is also reducing. Additionally, the H point design locations in different human percentiles are smaller than those of SAE recommendation. These results are all in accord with the fact that the figure of Chinese is smaller than that of occidental so that this model is reasonable to be used in designing Chinese driving cab.

5 Conclusion (1) This paper firstly created the human comfort sitting gesture rod system model, optimized the theory among the comfort joint angle range. Then the H point theory empirical model was created, and it can be found that the initial value of the vertical distance of H point and AHP for Chinese should be lower than that recommended by SAE. It can also be found that the horizontal distance of Chinese is shorter than SAE empirical value so the SAE empirical model is not suitable for the design of different Chinese human percentiles. (2) Jack was used to simulate the digital model and cab according to different dimensions of Chinese driver. The optimized data was then simulated by analyzing three evaluation index of human factor engineering. They are comfort, visible range, and reachable region. Lastly, MATLAB was used to fit the quadratic polynomial mathematical model whose coefficient of determination was 1. The result proved that this model is accurate and reliable.

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(3) When compared the H point design model for Chinese fitted by MATLAB with the SAE empirical model, it can be found that they were similar in tendency. As a result, the model for Chinese driver in this paper is effective and reliable. Although the H point location and the interval between different percentiles’ vertical distance are smaller than those of SAE, it is in line with the fact that the figure of Chinese is smaller than that of occidental. So the model in this paper is more suitable for Chinese driver than that of SAE. (4) This article provides a more reliable and accurate design optimization methods and mathematical models for different human body in the design of H position of the cab. Finally, it can help achieve the most comfortable human factor environment and optimized cab design.

References 1. SAE Recommended Practice J1517 (1985) Driver selected seat position 2. Huang J, Gong L, Ge A (2000) H-point optimization of vehicle body layout. Automot Eng 22 (6):368–372 3. GB/T29120-2012 (2012) H point and R point determination procedure. China Standard Press, Beijing 4. Grabisch M, Duchêne J, Lino F et al (2002) Subjective evaluation of discomfort in sitting positions. Fuzzy Optim Decis Making 1(3):287–312 5. Niu J, Zhang L (2012) Jack human factors engineering and application examples. Electronics Industry Press 6. Guo Q, Ma C (2014) Jack-based civil aircraft maintenance mission simulation and ergonomics evaluation. Comput Sci Mod (11):82–85 7. GBT 12985-1991 (1991) General rules for the application of body size percents in product design. China Standard Press, Beijing 8. GB 3975 (1988) Anthropometric terms. China Standard Press, Beijing 9. GB 10000-88 (1988) Chinese adult body size. China Standard Press, Beijing

Human–Machine Analysis of Bus Station Identification System in Changzhou Canqun He, Jinting Hu and Xiaolei Tan

Abstract This paper studies and designs the guidance, interface, color, height, and shape of the identification system of Changzhou bus station with the knowledge of ergonomics. Based on the basic function of the bus station identification system, considering body scale and visual characteristics of different groups, and through a variety of forms such as on-the-spot investigation and questionnaire research, puts forward the existing unreasonable problems that exist in the system. Then analyzes the problems and proposes the improvement scheme to provide the best visual guidance service for the passengers. Keywords Bus station

 Identification system  UI design  Ergonomics

1 Introduction With a small area, low cost, and high carrying capacity, buses have a wide range of routes and are still one of the most popular ways for people to travel. However, there are many problems in the traditional bus station, and the human–machine is not reasonable, and the unreasonableness of the identification system is an urgent problem to be solved. The main purpose of this paper is, in the design of bus stop sign system, combined with the principle of ergonomics, design scientific identification system, to satisfy the logo-oriented systems for passengers in the physical in all aspects of the physical and psychological effect, make the marking system to achieve the best effect.

C. He (&)  J. Hu  X. Tan College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_36

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2 Investigation of Changzhou Bus Station 2.1

Data Measurement and Passenger Traffic Analysis

See Tables 1 and 2. It can be seen from Table 3, in the morning and afternoon peak, the traffic is about 10 to 20 people every 10 min and the average number of people is around 20. Among them, the early-morning rush hour is dominated by the elderly and the children who go to school, and the evening rush hour is dominated by the children who leave school and the young people who get off work (Table 4).

Table 1 Overall size of bus station (unit: m) Site

LanXiang Sinchon

Hehai-huishan road

Tongjiang-chaohu road

The total length The total width

9.80 2.00

6.50 2.00

13.80 3.20

Table 2 Size of bus stop (unit: mm) Total length

Total width

Height above the ground

Indicator width

Average width

2880

630

1230

510

200

Table 3 Traffic monitoring map of bus station

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Table 4 Classification of the waiting crowd

Evening peak

Morning peak 34% 52% 8%

2.2

16%

Children

20%

Young people Middle-aged people

19%

Old people

27% 34%

Children Young people Middle-aged people Old people

The Requirements of the Waiting Crowd

The identification system design of the bus station relates to the destination of the passengers, and the bus stop is a manifestation of its concretization. The design of bus stop sign must accord with humanized design; a good bus stop design will bring great convenience. Through the interviews with the waiting crowd and the analysis of the questionnaire results, the need for the identification of bus stations can be divided into the five points: identify the location, provide drive circuit and directions, tell bus running time, provide relevant distance information, and provide other route information.

2.3

The Analysis of Existing Problems

1. The size of the bus stop is not reasonable. The overall size of the bus stop is too high, the width is slightly narrow, and the main content of the stop sign is too high from the ground. People with a height of 1.7–1.8 m can guarantee a straight line of sight, but people under 1.7 m need to look up to see the content. According to the results of the survey, more than half of the people who take the bus are elderly and children, the height of these people is generally below 1.6 m. When the required information is at the top of the bus stop, they must raise up their neck, frequent backdrops cause damage to their cervical and lumbar vertebrae. 2. The text size and layout problem of the bus stop. The text of the site information on each bus stop sign is arranged vertically. From left to right are the starting stations, intermediate stations and terminus, and the arrangement from left to right and from top to bottom conforms to the characteristics of human vision. However, its characters are too small, and its word spacing and row

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Fig. 1 Sketch map of the bus stop and the scene of looking up. Note The image in Fig. 1 is Xiaolei Tan, one of the authors

spacing are narrow. In addition, the design form of green bottom white character, the text and background color contrast is not high, the recognition degree is low, the information expression is not obvious. Generally, children and young people have good eyesight and can get information clearly from about 2 to 2.5 m. The elderly and some people with poor vision have to look within a meter or so to get the information they need. In addition, the existing bus stop is the compilation fixed information, it is difficult for the waiting crowd to know when the buses will arrive at the station, and there are how many buses on the route to be taken. So there should be a change route, a nearby map and a time prompt for the bus, etc. (Fig. 1).

3 Investigation of Changzhou Bus Station 3.1

The Design Requirements of Bus Station Identification System

The final purpose of the identification system design is to provide the direction information with reference value. The design and setting of the bus site-oriented logo should give full consideration to information needs pf people, behavior characteristics, the characteristics of the urban spatial environment. According to the survey results, the use objects of bus site-oriented logo are generally classified as tourists, passengers, and drivers, and different objects have different information needs [1]. The bus station identification system design requirements can be summarized as the following five: 1. Useful: Orientation is accurate and line is clear. 2. Suitable: Can fully mobilize the visual design elements, alleviate the boredom of waiting people, and is also an emotional design.

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3. Reasonable: Whether the visual effect and size of the bus stop or the placement position should be reasonable. 4. Concerted: Can fully and environment fusion, smart but not abrupt. 5. Universality: Commonality can meet different people oriented requirements.

3.2

Ergonomic Analysis of Bus Station Identification System

1. The size analysis of identification system. The size of the signboard is the area formed by the intersection of the signboard and the viewer’s sight. The size of the signboard is related to the viewer’s field of vision and visual angle. Field of vision refers to the range of space that can be seen when the head and eyes are fixed and the eyes are looking straight ahead. Visual angle refers to the angle of light drawn from both ends of the object (upper, lower or left, right) when viewing the object. The smaller the object is, the smaller distance from the observer, and the smaller the visual angle is [2]. Usually, people is in a relatively static state with the observed object. The vertical field of vision of people is the area above the eye level of 50° and below the eye level of 70°, the best color discrimination area is the range of 30° above the eye level and 40° below the eye level. The level field of vision area within range is about 60° [3]. According to our country’s adult population and the average height calculation, the maximum height of signboard should be within the scope of the 200–250 cm, the width should be controlled in about 120 cm. In addition, two points should also be noted in the layout design of signboard: • It is not suitable to set up information sources within a range of less than 60 cm from the ground. • The identification information of the area above 190 cm should be simple and clear, and the maximum should not exceed 250 cm. Otherwise, the viewer will be unable to obtain the information completely. The applicable people for the guidance of the bus station identification system include the waiting crowd, pedestrians and drivers, so the design must be considered in stationary and motion under the two states of visual characteristics, especially closely related to the change of the line of sight visibility is refers to the human eye to observed the horizontal distance of content, general best stadia range should be kept between 38–76 cm [4]. According to Fig. 2, the visible height range and the maximum width of the stop can be calculated:

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Fig. 2 Human visual range and visual field, the side and horizontal sketch of bus stop

h  D tan a þ X  H  h þ D tan a þ X;

ð1Þ

G  2D tan 0:5B:

ð2Þ

H is the distance of the visible area, D is the average sight distance, and 800 mm is taken; a is the best vertical observation angle, take 40°; h is the average height, according to the main female size of our country, the height of the 95% is 1541 mm; X is the correct amount of shoes to be worn, 680  H  2230 mm. G is the maximum width of bus stop; B is the best level of observation angle, take 30°, G  1.054 mm. By H and G, we can know that the area of the station display screen should be 1690–2230 mm in the vertical direction, and the horizontal length is about 1054 mm. This size of the bus stop can ensure that when most people read the bus information, can easily read the bus information, meet the basic requirements of ergonomics. 2. The color analysis of identification system. As the most powerful visual impact, the most perceptual visual language, color in the identification system design application has irreplaceable role. Color has three basic elements: brightness, hue, and purity. Because of different colors’ stimulus to the human eye is different, and the vision field for color is different, which makes the discrimination and reception of different color. Due to the existence of objective and subjective factors, according to different types and purposes, the color selection of identification system should not only meet the physiological needs of people in a specific environment, but also meet the psychological needs of people [5]. 3. The expression analysis of identifying information. Words and symbols are the main carriers of identifying information. When selecting fonts and symbols, it is necessary to consider the problem of distance recognition and the differentiation of multiple layers of information to avoid blurring of vision. Firstly, the identification of fonts and symbols must be strictly followed by international standards (such as GB/T), use standardized or universal symbols and fonts. Whether the design of fonts and symbols is reasonable or

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standard will directly affect the speed of recognizing the identification information [6]. When choosing the form of identifying information, the text should be given priority to the appropriate amount of universal symbol.

4 The Design Scheme of Bus Station Identification System 1. Dimensional design. The identification system is reflected in the bus stop. The shape of the bus stop we design is vertical and one-piece. According to the above-mentioned height dynamic range and width range, then combine the font size and spacing for reading to adjust. Eventually, the overall dimension height is 2300 mm, the width is 900 mm, the thickness is about 100 mm, and the height is about 73 mm from the ground (Fig. 3). 2. Visual design. When people identify a variety of different colors from a distance, their legible order is red, green, yellow, and white. Red is too strong, for people who don’t need to use identification system may cause errors, so we choose the green for the whole design. At the same time, green also has the function of eye protection and can alleviate the visual fatigue of the crowd when searching information. We chose green of high purity with light color as the color system, compared with the original identification system, makes a great improvement on the beauty. Dinosaur land is famous in Changzhou, the background of the stop is foil with the silhouette of a dinosaur, which represents the image of the city. The appearance of

Fig. 3 Size and layout of the bus stop

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the cartoon can give an interesting visual effect when people waiting for the bus and ease the frustration of waiting for the bus. In addition, the stop marks the starting stations, intermediate stations, and terminus. There are some flashing lights, by which to show the location of the bus. These flashing lights not only help the waiting crowd choose bus and estimate waiting time more convenient, but also avoid the circumstance that some people look up repeatedly. To some extent, it can relieve the impatience of the crowd.

5 Conclusion With the continuous development of era, the public transport system is still an important link in the transportation system of a city, and some problems of the identification system of the bus station are being paid more and more attention. This paper focuses on the theoretical basis, through various researches and data analysis, the improvement of human–machine problems of the identification system is proposed, which makes the identification system of Changzhou bus station more reasonable. Due to the limited data collection, there may still be some deficiencies in the improvement plan, and the human-oriented design will be the development direction of the future bus station identification system. Acknowledgements This work is supported by the Cooperation and Education item of Ministry of Education, No. 201702145009 and Undergraduate Innovation Program, No. 2017102941270.

References 1. Wang L (2012) Research on visual interface design with the sign of static public transport stop boards. Packag Eng 33(04):23–27 2. Ding Y-L (2011) Ergonomics. Beijing Institute of Technology Press, Beijing 3. Wang D (2010) Analysis of railway station identification system based on ergonomics. Sichuan Archit 30(02):65–66, 68 4. Yan D-F, Zhang J-Y, Yang L-C, Liu Q (2015) Design of bus stop display screen based on ergonomics. Sci Technol Innov Herald 12(33):78, 80 5. Wang J-C (2011) Ergonomics in product design. Chemical Industry Press, Beijing 6. Chen H-L, Lu J-S (2010) The application of ergonomics in the identification system-visual essay. Advert Panor (China Signage) 01:35–38

Research About UI Color Preference for Mobile Terminal Based on the User’s Visual Thinking and Perception Jing Jin and Huaqing Shen

Abstract The paper takes mobile terminal UI as the research object and explores mobile users’ preference about UI color in iPhone 5 through eye movement experiment from two aspects which are color perception part of visual perception organ and perception of objective visual thinking. According to PCCS color system, determine three kinds of colors which are warm colors, cool colors and neutral colors, and subdivide into 18 kinds of colors as UI samples. Then uniform color and combination in Photoshop and select 45 subjects to do eye movement experiment. By using SPSS20.0 statistical method to analyze data, we can get different colors in UI that has different levels of concern, and the result shows a consistent trend; gender, age, cultural differences, education levels, and some other factors have different impacts on color preference. According to research results, the paper offers some proposals about the color design of UI which might be the useful references for UI design and interaction design.



Keywords Mobile terminal UI Color preference perception Eye movement experiment



 User’s visual thinking and

1 Visual Thinking and UI Color Perception The concept of visual thinking was put forward by Rudolf Arnheim on the basis of cognitive psychology, who was an American psychologist in Germany and also a main representative of art theorist, gestalt psychology, and aesthetic [1]. Visual thinking is also known as the visual perception, which is divided into thinking and emotional components and both of them can be complementary. Images in the J. Jin (&) Hangzhou Animation and Game College, Hangzhou Vocational and Technical College, Hangzhou, China e-mail: [email protected] H. Shen School of Humanities, Zhejiang University, Hangzhou, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_37

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perceptual components can be created from different levels of abstraction, and images of the activity of visual perception is mainly to grasp and capture the meaningful and interesting forms, which reflects some of the most prominent structural characteristics [2]. Color perception of visual thinking is an important part of the UI interaction design, which depends on the user’s perception just like graphic language. For most users, the color perception of the visual perceptive organ has a specific feature, but it may vary from the user’s personal preferences. Different users have different preferences for UI color due to the objective visual perception of color, and the main influencing factors are age, gender, cultural differences, education levels [3]. So this article will do eye movement experiments and data analysis to study the effect of UI color preference from two aspects which are color perception part of visual perception organ and perception of objective visual thinking [4].

2 Experimental Scheme Design 2.1

Selecting Experimental Color

PCCS (Practical Color Coordinate System) color system is developed by the Japanese Color Institute, and the tone series is a color organization system based on it [5]. According to the PCCS color system, determine three color series, which is warm colors, cool colors, and neutral colors, respectively. Among which the color purity and brightness of the warm colors and cool colors are higher than neutral colors, and then they are subdivided into 18 colors as the experimental colors of eye movement experiment and applied in UI to explore color preference by observing eye movement experiment [6].

2.2

The Experiment Pictures of UI

Combination and numbering UI and 3 kinds of color systems (18 common colors). Picture samples are six pieces in total. The pictures of No. 1–3 are composed of a kind of color system, which are six kinds of warm colors, six kinds of cool colors, and six kinds of neutral colors; the pictures of No. 4–6 are composed of two kinds of color systems, which are 12 kinds of warm colors plus cool colors, 12 kinds of warm colors plus neutral colors, and 12 kinds of cool colors plus neutral colors. The interface of iPhone 5 which has iOS mobile operating system with a high recognition degree is selected as sample pictures, and Photoshop as a kind of image software is used for uniform color and combination, as shown in Table 1. The interface size of iPhone 5 is 640  1136, the resolution of Web UI and mobile

Sample pictures

Variable

Picture numbers—color 1—warm 2—cool colors colors

Table 1 Pictures of experimental sample 3—neutral colors

4—cool + neutral colors

5—warm + neutral colors

6—warm + cool colors

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terminal UI are 72 ppi generally. The size of elements are as follows, the size of status bar is 40 px, the size of navigation bar is 88 px, the size of main menu bar is 98 px, the size of content area is 910 px.

2.3

Experimental Subjects

Take 45 subjects who are 11 males and 34 females, and age distribution between 18 and 49 years old. All subjects are required that naked eyes’ vision or corrected visual acuity must reach 1.0 and above, without color blindness.

3 Experimental Data and Statistical Analysis 3.1

Experimental Data Extraction

After checking all index record data of the eye movement experiment, delete some invalid samples which have too much default values and serious visual field loss. At last, a total of 42 valid samples are screened.

3.2 3.2.1

Experimental Data Processing Color Perception of Visual Perception Organs

By classifying and average processing of the output excel report, get the results of related data for different regions. Table 2 shows concrete conditions of eye

Table 2 Eye tracking index of the experimental sample pictures in different colors regions (mean value) Picture number

Total fixation time (ms)

Percentage of time (%)

Number of fixation points

Group differences

4

4471 3725

0.527 0.439

15 13

5

4773 3520

0.500 0.373

14 11

6

5127 3172

0.595 0.373

17 11

Cool colors Neutral colors Warm colors Neutral colors Warm colors Cool colors

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Fig. 1 Histogram of picture No. 4, 5, and 6’s total fixation time ratio

Fig. 2 Histogram of picture No. 4, 5, and 6’s number of fixation points

movement data for different color systems in the picture of No. 4, 5, and 6, and we can find that it has significant differences in the total fixation time and the number of fixation. Arrange the proportion of total fixation time and the number of fixation points of each picture’s two interested areas, then pair comparison to get Figs. 1 and 2. From the figures we can see, the comparison for concerning degree in different colors shows a unified trend. The concrete analysis is as follows: 1. For the region of different colors in same picture, compared with neutral colors, the total fixation time of subjects in warm colors and cool colors area are longer, and the number of fixation points is also more. 2. When compared with warm colors region and cool colors region, the degree of concern in warm colors area is far greater than cool colors area, both on the total fixation time and the number of fixation points.

3.2.2

The Influence of Objective Visual Thinking and Perception on the Color Preference of UI

The objective visual thinking and perception of the UI color preference experiment includes four factors, which are gender, age, cultural differences, education levels, and so on. First, by selecting subjects’ individual information table to collect the individual information when finish the experiment, then classify the eye movement experimental data according to sex, cultural differences and the levels of education, then analyzing the results of each factor under the influence of color preference difference.

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Table 3 The variance (ANOVA) result of gender factor Color Cool colors

Square sum

df

Mean square

Between groups 12.507 1 12.507 In the group 77.993 40 1.950 Total 90.500 41 Warm colors Between groups 24.403 1 24.403 In the group 94.382 40 2.360 Total 118.786 41 Neutral colors Between groups 1.970 1 1.970 In the group 166.316 40 4.158 Total 168.286 41 F Analysis of Variance (ANOVA), which is the comparison value of two

F

Significant

6.415

0.015

10.342

0.003

0.474

0.495

mean squares

Information summary of subjects Eight males and 34 females are tested, and divide them into three groups according to the China’s age segmentation: 12 persons in youth group (less than 29 years old), 20 persons in middle-young-aged group (30–39 years old), 10 persons in the middle-aged group (40–49 years old). Correlation analysis between gender and color preference of UI First of all, classify the experimental data according to gender then, make one-way analysis of variance to analyze the fixation duration and fixation count of each color system by using SPSS, and the results are shown in Table 3. From Table 3, the Sig. (P values) of preference score of cool colors and warm colors are less than 0.05. It shows that gender have significant influence on cool and warm colors’ preference scores. It also means different gender has different preference degrees on cool and warm colors, but it has little effect on preference degree of neutral colors. On the basis of the above analysis, using descriptive analysis to realize the specific situation of the gender on the colors preference. Table 4 lists male and female subjects’ preference scores about three colors which are mean, standard deviation, standard error, and so on. As to the score of mean, cool colors of women’s score is 2.24 and men’s score is 3.63, while warm colors of women’s score is 3.44 and men’s score is 1.5. Hence, it can be concluded that men prefer to cool colors of UI, and women prefer to warm colors of UI; what’s more there is no obvious difference on mean score of different gender to neutral colors preference, which means the less affected by gender. Correlation analysis between age and color preference of UI In the same way, make a descriptive analysis of each color system’s score based on the variable of age. As for age, the mean score for cool colors preference of young group (less than 29 years old) are 3.25, which is significantly higher than the other two characters, while middle-young-aged group (30–39 years old) gives a

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Table 4 Descriptive analysis results of gender factor N

Cool colors

Female Male Total Warm Female colors Male Total Neutral Female colors Male Total N Effective sample size,

Mean

Standard deviation

Standard error

34 2.24 1.350 0.231 8 3.63 1.598 0.565 42 2.50 1.486 0.229 34 3.44 1.599 0.274 8 1.50 1.195 0.423 42 3.07 1.702 0.263 34 2.32 1.918 0.329 8 2.88 2.532 0.895 42 2.43 2.026 0.313 which is 8 males and 34 females

Mean 95% confidence interval The lower Upper limit limit 1.76 2.29 2.04 2.88 0.50 2.54 1.65 0.76 1.80

2.71 4.96 2.96 4.00 2.50 3.60 2.99 4.99 3.06

higher preference score of warm colors, whose mean values are 3.36; the mean score for neutral colors preference of middle-aged group (49–40 years old) are 3.08, which is higher than the other two characters. Thus, it can be seen that the youth group (less than 29 years old) prefer to cool colors, the middle-young-aged group (30–39 years old) prefer to warm colors, and the middle-aged group (40–49 years old) prefer to neutral colors. Correlation analysis of UI color preference about cultural differences and education levels As to the cultural differences and education levels, through the single factor analysis of variance we can find that the significant values of preference scores of any one color systems are greater than a (0.05). It shows that the cultural differences and education levels have effect on the colors preference, but do not have a significant effect.

4 Conclusion and Suggestion 4.1

Conclusion

In this paper, we use eye movement experiment to study color preference to UI of mobile terminal through the user’s visual perception and get the following conclusions: 1. The concern degrees of different colors of UI from big to small is warm colors, cold colors, and neutral colors, respectively.

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2. In a certain extent, gender influences on the color preference of UI, and the specific result is that female prefer to warm colors and male prefer to cold colors. 3. Age has a significant impact on color preference, and the specific result is that the older people prefer to neutral colors and middle-youth-aged people prefer to cool colors and warm colors. 4. Cultural differences and education levels have an effect on colors preference, but do not have a significant effect.

4.2

Suggestion

According to the above research results, the paper puts forward to some suggestions on the color design of UI for the two significant factors which are gender and age. 1. Increase the various targets of screen in the different effects to highlight the information, by using the brightness, contrast, and color saturation adjustment of color. In the conclusion one, the concern degrees of different colors of UI from big to small is warm colors, cold colors, and neutral colors, respectively. So, the suggestion one is to improve the color design of UI according to the conclusion one. 2. Gender has significant influence on color preference hence, gender cannot be ignored in the early market research of color design. Relevant content also can distinguish by gender, such as the content of female can refer to the color preference on women to design colors of UI. 3. Different ages of users have different observe abilities to observe colors, and there is an obvious gap about color preference. Aged people will give priority to use conservative and stable color tone, while to attract young users will choose bright colors in scheme of UI design. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Hangzhou Vocational and Technical College. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Arnheim R (1998) Visual thinking. Sichuan people’s press, Sichuan 2. Zhang M (2013) Analysis of color in the design of UI applications. Vis Commun 4:97–98 3. Gu W (2012) UI design of user interaction experience of visual thinking. The China academy of art master’s degree thesis, pp 17–18 4. Zhen Z (2015) The application of color in mobile phone interface design. Mod Decor (theory) 11:26–28 5. Liu W, Bao X (2017) A brief analysis of color semantics in the application of mobile UI design. Art Sci Technol 11:62–64 6. Hou Y (2016) The analysis of visual performance of mobile phone interface based on user experience. Packag Eng 10:58–60

Interface Ergonomics Evaluation Methods and Applied Research for Fighter Cockpit Haijing Song and Xiaofang Xu

Abstract According to the requirements of interface ergonomics evaluation of fighter cockpit from type development and the characteristics of interface, the evaluation indexes were established based on modified Delphi, the engineering evaluation methods applicable to flight test step were proposed, and also the data process integrating multiple attribute decision making, membership function, and fuzzy mathematics were put forward, realizing the quantitative results of interface qualitative evaluation. Finally, this method was applied in one fighter with clean interface during flight test step, and the results proved the validity of this study and can also provide the reference for interface ergonomics evaluation for other military aircraft.



Keywords Interface ergonomics Evaluation index Delphi method Quantitative evaluation



 Data processing

1 Introduction Fighter cockpit is the main interface of information interaction for pilot, known as the man–machine interface [1]. Through this interface, pilots receive information from the display device and complete the task through the control device based on information processing, achieving the manipulation of the aircraft. With the continuous improvement of the fighter system, the display of information is highly integrated and the pilot’s workload is getting more and more heavier. To ensure the flight safety and efficiency, the man–machine interface design is required to meet ergonomics requirements [2]. Nowadays, most types of military aircraft proposed evaluation requirements of good adaptability from the human–machine interface, including the cockpit layout, display, control, maintenance, workload, and microenvironment. However, due to H. Song (&)  X. Xu Chinese Flight Test Establishment, Xi’an 710089, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_38

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Modified Dephi

Indicator system

Interface evaluation index

Task characteristics analysis

Engineering evaluation method

Ground verification test verification

Multi-attribute decision membership function

Comprehensive evaluation model

Comprehensive evaluation value

Expert checklist system

Evaluation example verification

Interface problem feedback

Fig. 1 Evaluation framework of interface ergonomics evaluation for fighter cockpit

complex and huge amount of ergonomics evaluation factors, the existing evaluation methods are subjective and weak in engineering application, leading to the qualitative results and the difficult entity verification, which makes the breakthrough in interface ergonomics evaluation key technologies extremely hard. According to the mission characteristics and evaluation features of fighter aircraft, combined with the actuality of flight test, this paper analyzes the influencing factors of fighter cockpit interface ergonomics based on modified Delphi method; the assessment criteria and the static assessment and dynamic assessment based on flight task were put forward; then, the experimental data were collected to determine the comprehensive quantitative evaluation model; Finally, the effectiveness of evaluation methods was validated based on one type fighter cockpit. The evaluation framework of interface ergonomics is shown in Fig. 1.

2 The Establishment of Three-Level Evaluation Indexes The evaluation requirements for interface ergonomics are to ensure the adaptability of the man–machine interface; that is, to say, on the one hand, “pilots are fit for aircraft,” and at the same time, they are also “suitable for pilots” [3, 4]. This method applied the consensus of experts and considered the weights of experts based on typical Delphi method. Combining the characteristics of fighter flight test tasks, 15 pilots with multi-aircraft flight experience were chosen as consultants (flight time is at least 1500 h), and the questionnaires were sent to the consulted experts about the effect

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The evaluation of interface ergonomics evaluation for fighter cockpit O1

O2

Installation layout

O11 O12

Pi lot Se ats

Da sh bo Ar d

U1

U2

O13

O14

Dri Thr vi ottle ng leve rod r

U3

U4

Display ergonomics

O15 O16

O21 O22

O31

O32 O33

Inte Si Gap Disp rnal De lay and bar size char exte acte rnal risti v cs iew

Ope rati onal post ure

Tec Ope hnic rati al ng wor spac kloa e d

U5

U9

U6

U7

U8

O4

O5

Maintenance efficiency

Workload

O3 Control ergonomics

U10

U11

O41 O42 O43

Acc essi bilit y

Inte rcha nge abili ty

U12 U13

Dia gno stic quic kne ss

O6 microenvironm ent

O44 O45

O46

Lo go & Err or

Hu man ele men t

Sa fe ty

Phy Psy Co siol chol mfo ogic ogic rt al al

U16

U17

U18

U14 U15

O51

Total target level

O

O52 O53

U19

U20

O61

O62 O63

Lig V htne ib ss rati on

U21

Indicator layer

No ise

U22

U23

Sub-in dicator

Indicator

Fig. 2 Three-level indicator system of interface evaluation for fighter cockpit

of indexes to the interface ergonomics. The expert’s opinions have basically reached the same level after 2–4 rounds that means the consensus of experts was received. Finally, the three-level evaluation indexes were achieved based on the evaluation results and weights of experts, in which the first-level target indicator level used O to indicate, and the second-level specific indicators are considered as U, as shown in Fig. 2.

3 The Comprehensive Evaluation Methods and Model 3.1

Experts and Attribute Weights to Determine

Assuming the target level of evaluation as O ¼ f O1 O2 . . . Os g, the specific evaluation indicators as U ¼ f U1 U2 . . . Um g, the weight of corresponding to the specific indicator Uj is considered as xj , where 0  xj  1, j ¼ 1; 2; . . .; m, and Pm j¼1 xj ¼ 1. Experts involved in decision making are E ¼ ð E1 E2    En Þ, and the weight of experts Ek was determined asP wk based on the analytic hierarchy process, where 0  wk  1, k ¼ 1; 2; . . .; n, and nk¼1 wk ¼ 1.   ; after the determination of the experts The expert decision matrix is Rk ¼ rijk mn

weights and attribute weights based on the analytic hierarchy process, the evaluation score of one expert for one target scheme Os is: lk ðiÞ ¼

n X j¼1

rijk xj

ð1Þ

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It can be seen that the group decision-making score for scheme Os is: l0 ðiÞ ¼

s X

lk ðiÞwk

ð2Þ

k¼1

where xj is the weight of the attribute, wk is the weight of the expert, rijk is the evaluation level of the expert k for the specific index Uj under the target scheme Oi , and lk ðiÞ is the score of the expert k for the scheme Os .

3.2

Index Value Pretreatment

During interface ergonomics evaluation, some indicators, such as workload and comfort, are mostly described by natural and variable language and cannot be easily standardized [5, 6]. Therefore, in order to ensure the commensurability of each index value, the eigenvalues of each index should be uniformly transformed before the evaluation so as to satisfy the normalized and dimensionless conditions. This paper proposed the corresponding membership function of different evaluation indicators.

3.2.1

The Treatment for Quantitative Indicators

(1) The indicator tends to be better if its value is bigger, such as the screen clarity, readability and so on, the corresponding quantification function is as follows: li ¼

8 < 1

xi mi : Mi mi

0

xi  M i Mi [ xi [ mi xi  mi

ð3Þ

(2) The indicator tends to be better if its value is smaller, such as the intensity of operation, the amount of noise and so on, the corresponding quantification function is as follows: 8 xi  m i < 1 xi li ¼ MMiim ð4Þ m i \xi \Mi i : 0 xi  M i (3) Medium-sized indicators, that means, the indicator tends to be better if its value is not too large or too small, such as the internal field of vision, cabin lighting, the corresponding quantification function is as follows:

Interface Ergonomics Evaluation Methods and Applied …

li ¼

8 > <

2ðxi mi Þ Mi mi 2ðMi mi Þ > : Mi mi

0

337

mi  xi \ Mi þ2 mi

ð5Þ

Mi þ mi  xi  M i 2 xi [ Mi ; xi \mi

(4) Interval indicators, that means, the best indicators' values should lay in a fixed interval, such as installation angle, gap size, the corresponding quantification function is as follows: 8 qi1 xi < 1  maxfqi1 mi ;Mi qi2 g 1 li ¼ : qi2 1  maxfqi1xim i ;Mi qi2 g

xi \qi1 xi 2 ½qi1 ; qi2  xi [ qi2

ð6Þ

where xi refers to the eigenvalue of the index ui ; Mi and mi are the allowable upper and lower bounds of xi ; ½qi1 ; qi2  is the optimal stability interval; and li is the membership of the indicator ui .

3.2.2

The Treatment for Qualitative Indicators

In terms of some qualitative indicators, such as cabin comfort, technical workload, evaluation experts can only give subjective assessments based on personal experience and preferences. For such indicators, the linguistic variables and fuzzy number can be used to overcome the ambiguity and inaccuracy of subjective judgments.

3.3

Comprehensive Evaluation Model

The mathematical model of comprehensive evaluation based on fuzzy sets determined in this paper is as follows [7]: B ¼ W  R ¼ ðB1 ; B2 ; . . .; Bm Þ

ð7Þ

Among them, W is an expert weight vector set, obtained from multi-attribute decision-making analysis; R indicates the fuzzy matrix of the index being evaluated; “” means generalized fuzzy synthesis. Then to analyze B, the column vector is: ^

^

^

^ 1j Þðw2 r ^ 2j Þ. . .ðwp r ^ pj Þ ðj ¼ 1; 2; . . .; mÞ bj ¼ ðw1 r ^

ð8Þ

Formula (8) is a comprehensive evaluation model, where “” means generalized ^ means generalized fuzzy “and” operations. B may be fuzzy “or” operation, and “” referred to as a fuzzy comprehensive evaluation set based on a comment set V. bj is

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Table 1 Evaluation results of interface ergonomics Evaluation levels

V

Evaluation score

Evaluation meaning

Excellent

v1

90–100

Good

v2

70–80

Middle

v3

50–70

Poor

v4

30–50

Inferior

v5

0–30

Very satisfied, the performance does not require additional attention Negligible defects, satisfactory performance does not require additional attention from pilots or maintenance personnel Moderately unsatisfied deficiencies, adequate performance required pilot and maintenance appropriate compensation Unsatisfied with high defects, inadequate performance requires strong compensation from pilots and maintenance personnel Big flaw, cannot complete part of the required operation

referred to as a membership degree of a hierarchical rating vj to the fuzzy evaluation set B obtained by the comprehensive evaluation. Assuming that each level parameter column vector is J ¼ ðj1 ; j2 ; . . .jm Þ0 , the evaluation result of calculating the level parameters is as follows: Q¼BJ

ð9Þ

If the evaluation result B is converted into a comprehensive score Q, it can be used to evaluate the ergonomics and level of interface; the evaluation level, score, and meaning can be drawn as shown in Table 1 [8].

4 Instance Analysis and Verification In this paper, a type of fighter cockpit with a concise interface is taken as an example. Based on the evaluation index and cockpit ergonomics methods, different verification scenarios were designed according to specific flight subjects. The static evaluation and task assessment are used to evaluate the layout, operation efficiency, workload, and microenvironment module assessment, and flight test and ground verification test data were collected based on detailed quantitative and qualitative methods [9, 10]. Specific assessment steps are as follows: The rating matrix: V ¼ fv1 ; v2 ; v3 ; v4 ; v5 g ¼ fExcellent, Good, Middle, Poor, Inferiorg; The evaluation index set is: U ¼ fu1 ; u2 ; u3 ; u4 ; u5 g = f layout, display ergonomics, control ergonomics, workload, microenvironmentg

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Among them, each evaluation module had established a corresponding three-level index system, each index layer had the corresponding experimental support data, and then the weight value was calculated based on Sect. 3.1; the membership degree was determined based on Sect. 3.2. A total of 126 indicators for the five modules from the bottom were analyzed (considering the length of the paper, specific indicators data were not described in details); the results of the comprehensive evaluation of interface ergonomics were as follows: The weight vector set: W ¼ fw1 ; w2 ; w3 ; w4 ; w5 g ¼ f0:27; 0:3; 0:2; 0:1; 0:13g; After each index value pretreatment, the final evaluation matrix was obtained: 2

0:45 6 0:2 6 R¼6 6 0 4 0:1 0

0:3 0:45 0:35 0:45 0:05

0:15 0:05 0:125 0:125 0:35 0:2 0:3 0:1 0:4 0:4

3 0:05 0:1 7 7 0:1 7 7 0:05 5 0:15

The final evaluation result is: B ¼ W  R ¼ ð0:1915 0:3375 0:23 0:153 0:088Þ The final calculated result was Q ¼ B  vT ¼ 0:7263, the corresponding degree to the evaluation was “good” level, which means the overall evaluation of the interface ergonomics of the aircraft was 72.63. Further analysis of the corresponding indicator layer showed that the aircraft had a higher score in terms of spatial layout and operation efficiency that mean better performance for pilots and maintenance personnel. However, in actual work, we continued to conduct in-depth analysis of specific sub-indicator layers and found that the aircraft had moderately negligible flaws in glare, lighting, and noise and required additional attention and compensation from pilots and maintenance personnel.

5 Conclusion The proposed comprehensive evaluation model for fighter cockpit in this paper has certain scientific, reasonable, and engineering application. (1) The Physical interfaces ergonomics and human-computer interaction performance were fully considered and the experienced experts were invited to select index based on the modified Delphi, enhancing the scientific of the 3-level index system result; (2) Considering the subjectivity and fuzziness of experts, the multi-attribute decision making, the membership function, and the fuzzy mathematics were

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combined to process the experimental data, realizing the quantitative results of the interface ergonomics evaluation. (3) The results of the example analysis have shown that the evaluation model could be applied to the engineering practice to obtain the evaluation results and to reflect the ergonomics drawbacks. This method can also be used for military aircraft ergonomics evaluation and further extended application to other complex systems interface evaluation.

References 1. Hickey LF, Springer WE (1969) A development in cockpit geometry evaluation. Boeing Company, Seattle 2. Wang H, Wu G, Liu B (1998) Study on advances in aerodynamics. Chin J Aerosp Med 9 (3):180–183 3. Boeing Commercial Airplane Group (2002) Statistical summary of worldwide operations for commercial jet aircraft accidents 1991–2001. Boeing Corporation 4. Li Y, Yuan X, Yang F (2003) Research on multi-level fuzzy evaluation of aircraft cabin. Chin J Safety Sci 13(3):50–53 5. McClumpha AJ, Rudisill M (2000) Certification for civil flight decks and the human– computer interface. In: Wise JA, Hopkin VD (eds) Human factors in certification. LEA 6. Keota R, Toivonen R (2004) Expert assessment of physical ergonomics at video-display unit workstations: repeatability, validity and responsiveness to changes. Environ Health 77 (2):437–442 7. Wong WG (1999) Grey evaluation method of concrete pavement comprehensive condition. J Transp Eng 25(6):27–31 8. Zhang J (2000) Fuzzy analytic hierarchy process. Fuzzy Syst Math 14(2):80–88 9. Xiao J, Douglas DA (1997) Delphi evaluation of the factors influencing length of stay in Australian hospitals. Int J Health Plann Manag 12(6):207–218 10. Li Y, Yuan X (2003) Research progress of geometric adaptability evaluation technology for aircraft cockpit. J Erg 9(2):29–32

Study on the Optimization Design Method of Human–Machine Interface of Vehicle Equipment Nan Men, Zhibing Pang, Fenghua Wang, Honglei Li, Pengdong Zhang and Quanliang Yin

Abstract The purpose is through the analysis of the current status of the human– machine interface of vehicle equipment, and to study the basis and principles of the optimization design of human–machine interface, so as to provide guidance for optimizing the design of human–machine interaction and improving the efficiency of human–machine interaction. The method is Using Man–machine-environment system engineering theory and analysis method, consulting literature and related data, carry out comparative and empirical research on the optimization design method of vehicle equipment human–machine interface. The result is the optimization design of human–machine interface of vehicle equipment must be based on military needs, based on the development of computer technology, and according to the basic principles of human–machine interface optimization design. The conclusion is giving full play to the efficiency of equipment and improving the friendliness and efficiency of human–machine interface is always the theme and goal of the optimization design of human–machine interface. Keywords Vehicle equipment

 Interface  Optimization  Design

1 Introduction The human–machine interface of vehicle equipment is the medium of transmitting and exchanging information between personnel and equipment. The internal form of vehicle equipment information and the conversion of vehicle handling personnel can be realized [1]. The vehicle equipment operator is the main body of the vehicle equipment, and it is the decision-maker and the controller. The vehicle equipment is the combat weapon, and it is the controlled object. The operator must understand the N. Men (&)  Z. Pang  F. Wang  H. Li  P. Zhang  Q. Yin CPLA Army Artillery and Air Defence Forces Academy, Zhengzhou Campus, Zhengzhou 450052, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_39

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performance of the controlled object and know its running state at any time. When its running state is different from the required state, it can intervene in time to make it meet the required state. In order to achieve accurate, rapid, and convenient control of the target, the human–machine interface of the vehicle equipment must meet the control ability and control characteristics of the operator. At the same time, it is also convenient for the operator to master the operating state of the equipment, make the decision and carry out the correct control. The human–machine interface of vehicle equipment directly affects the response time of vehicle equipment and the usability of the system, which affects the operational effectiveness of the equipment [2]. A reasonable design of human–machine interface of vehicle equipment is more convenient for operators to learn and adapt, which enables the operation to be faster, more accurate and safer, so that the operational effectiveness of vehicle equipment can be brought into full play.

2 Status Quo of Human–Machine Interface of Vehicle Equipment At present, the technology used in human–machine interface of vehicle equipment remains in the graphical interface; interactive device is mainly used in ordinary computer display screen, joystick, track ball, etc., is a kind of interaction mode called “people adapt to machine”, which is lack of natural and efficient interaction. This seriously affects the efficiency of the command decision-making and restricts the operator’s subjective initiative [3]. In the overall design of the old equipment, the human–machine interface is mostly designed by experience. The subjective factors of one or more designers decide the style, the specific interface, and the information displayed in the system’s human–machine interaction.

3 Problems to Be Grasped in the Optimization Design of Human–Machine Interface 3.1

Users and Requirements Analysis

According to the user-centered theory, in the early stage of the design of human– machine interaction interface for vehicle-mounted equipment, we need to analyze users from three perspectives: user thinking mode, system operation mode, and interface designer mode [4]. User thinking mode: In man–machine engineering, the user’s system of work is based on experience and what they care about and think about when they are using the product. Vehicle equipment as a product, its users are officers and soldiers who

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run the system directly. Analyzing the main contents they are concerned about during the operation process and maintenance process can generally include the following aspects: What is the basic operation process? How do you identify the target and determine the target to be hit? When and how to assign the target? What other intervention operations are there? How to do maintenance operations? System operation mode: The man–machine engineering theory, the way and method that the product completes its function is determined by the designer of the system, and the human–machine interface must be consistent with the product’s hardware platform, software implementation method, content and so on. Therefore, in designing the human–machine interface of the vehicle equipment, the following factors must be taken into consideration: What is the running platform of the software? Which development tools are used for interface development? Does the interface implementation affect the operation of other software? How does the software interact with each other? Interface designer mode: After analyzing the vehicle equipment from the perspective of user thinking mode and system operation mode, should have formed a more comprehensive human–machine interface demand plan, at this time, the interface designer needs to use professional man–machine engineering theory, integrate the requirements and the resources provided by the system organically to form a preliminary human–machine interface scheme. It is mainly considered from the following aspects: Determine the operating platform and development environment of the software; determine the mode of human–machine interaction (image, operation panel, voice, etc.); determine the main functional area of the image interface; determine the main items and timing of the operation.

3.2

Basic Principles

The goal of human–machine interaction optimization design is to enable users to use the equipment efficiently and to produce a good experience in the interaction with the system. Excellent interaction design enables the user, system, and environment to work in harmony. In the three elements of interaction design, the user is the main body of human–machine interaction, the system interface is the carrier of human–machine interaction, and the environment is the influence body that runs through the whole human–machine interaction process. In the interaction design, only the three factors are taken into full consideration can a truly “usable” interface be designed.

3.2.1

Enhance User Interaction Proficiency

For novice users, it is necessary to provide step-by-step guidance for the optimization design of the human–machine interface. For example, give a certain operation prompt or help to explain, let it be familiar with the system slowly,

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establish good psychological suggestion, and enhance the familiarity of interactive process. For skilled users, more free choice space can be given in the optimization design of the interface. For example, provide quick keys, set hot keys, and other functions to improve their ability to control and operate the equipment.

3.2.2

Enhance Interaction Efficiency

The first is to optimize the task module and establish reasonable human–machine interaction task flow. In the process of vehicle equipment man–machine interaction, the high efficiency of human–computer interaction is directly reflected in the efficiency of user’s execution system tasks, and it is an efficient way to optimize the module and establish reasonable task flow. The object of task module optimization is the task module that is often executed by the equipment, analyze the execution process and find the redundant action, and then merge or reduce unnecessary actions or automate them according to people’s cognitive habits, accordingly simplify the interactive dialogue process, reduce the cognitive load and cognitive time needed for user information processing, and improve the quality of user information processing. A reasonable task flow is to divide a task into multiple sub-tasks based on the optimization of task modules and to connect these sub-tasks according to a logical process. The use of this kind of task process has a certain interaction guidance to the user, which can improve the efficiency of human–computer interaction [5]. The second is to provide the necessary fault tolerance and recovery mechanism. The complexity of vehicle equipment determines that the user will have certain misoperation when operating; when the user errors, human–machine interaction system can give timely warning, detecting and reporting errors, put forward correction methods, and guide the user to error correction; such mechanism will help to improve the effectiveness of the interaction. In addition, the humanized interactive system also needs to have a recovery function, allowing users to cancel and repeat the operations that have been executed.

3.2.3

Enhance Human–Machine Interaction Intuition

The first is to use multichannel human–computer interaction technology. Multi-modal interaction is a kind of human–machine interaction technology which has developed rapidly in recent years. It adapts to the “human-centered” natural interaction criterion [6]. Multi-modal interface integrates language input, gesture input, posture understanding, gaze tracking, and other input modal to extract user interaction semantics, identify the ultimate purpose of interaction and improve the efficiency of human–machine interaction. The second is to use visual interaction. The human–machine interface of vehicular equipment has a huge amount of information and complex structure. Visual interaction can realize the effective presentation and efficient interaction of a

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large number of information in the system. Visual interaction consists of two processes: First is to convert a large amount of abstract information into visual graphics; second two is to obtain information through human–machine interaction, user control, and the various stages of the transformation process. The use of visual interaction enables users to directly observe and understand large-scale information and even discover the characteristics and rules that are hidden inside information [7].

3.2.4

Enhance the Harmony with the Environment in Interaction Process

In the human–machine interaction of vehicle equipment, the influence of operating environment on human–machine interaction is mainly reflected in two aspects: the external influence and internal influence. For example, in the operation of vehicle equipment, sometimes the shaky cockpit will cause the operator to sway, resulting in the inconvenient interaction between users and the system. At this time, the stability of the interactive system should be considered. Internal influence refers to the influence of extreme operating environment on people’s internal physiology or psychology. For example, in some cabins, a dark environment can cause visual discomfort to the operator, and an interactive design for a dedicated night mode should be used. In a word, in the human–machine interaction of vehicle equipment, only the harmonious coexistence of man–machine and the environment can improve the efficiency of the interaction and improve the operational effectiveness of the whole system.

4 Conclusions The optimization design of human–machine interface for vehicle equipment is an important work in the overall design of equipment. The direct driving force for this work is the military demand traction and the development of computer technology. Focusing on how to give full play to the operational effectiveness of equipment and improve man–machine interaction friendliness and efficiency, it is always the theme and goal of optimization design and research of the man–machine interface of vehicle equipment.

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References 1. Huichuan W, Xiaozhe Z (2012) Development of man-machine interface of nawal weapon system. Command Control Simul 34:1–4 2. Zhibing P (2000) The man-machine-environment system engineering of air defense, p 244 3. Liebin Y, Fanwen M (2013) New technology of human-machine interaction in weaponry system. Electron World 12:164–165 4. Yingying C, Lei W, Huiyi (2016) Research on man-machine interface design of the user-centered air defense missile weapon system. Command Control Simul 38:127–130 5. Chengqi X (2015) Digital human-machine interface design method and application of complex information system. Southeast University Press, Nanjing, p 189 6. Changling L, Weihua L (2014) Multi channel human-machine interaction model for battlefield. Fire Command Control 37(11):110–114 7. Xiangxu M, Xueqing L, Chenglei Y (2016) The basic course of human-machine interaction, 3rd edn. Tsinghua University Press, Beijing, pp 91–98

Ergonomics Evaluation of Large Screen Display in Cockpit Based on Eye-Tracking Technology Yanyan Wang, Qingfeng Liu, Wanli Lou, Duanqin Xiong, Yu Bai, Jian Du and Xiaochao Guo

Abstract Eye-tracking technology was used to study the visual sensitive area and the ergonomics of commonly used information encoding methods in large screen primary flight display (PFD) in order to optimize the interface design. Methods A total of 44 pilots (36 ± 6 years) attended the experiment. Seven typical flight human–machine interface images were adapted according to varied factors such as 12 quadrants, 6 colors, and 10 presentation encodings which would affect the ergonomics design. The pilots were asked to search a target picture with full information intercepted from the typical images, and the eye tracker was used to record the eye movement data during the task. The performance differences were analyzed among factors. Results The results of multivariate test showed that: (1) There are significant differences between 12 quadrants and 7 typical pictures (P < 0.01), and the interaction effect between pictures and quadrants is significant (P < 0.01). (2) There were significant differences among the 6 colors, 7 typical pictures, and 12 quadrants groups (P < 0.01); and the interaction among three factors were significant (P < 0.01). (3) There were significant differences among the 10 presentation encodings, 7 typical pictures, and 12 quadrants (P < 0.01). The interaction among three factors was significant (P < 0.01). Conclusion (1) The visual sensitive area of the large screen primary flight display is quadrant 1, 5, 7; the area of visual insensitivity is 10, 12. (2) According to colors, red was the optic color, yellow and green were the worst color. (3) According to presentation encodings, white character with white borders and white character with red shading borders are optic encoding, and black character with yellow borders and green shading was the worst. Keywords Eye-tracking technology Primary flight display

 Man–machine interface  Ergonomics

Y. Wang  Q. Liu Beihang University, Xueyuan Road 37, Haidian District, Beijing 100191, China e-mail: [email protected] Y. Wang  Q. Liu  D. Xiong  Y. Bai  J. Du  X. Guo (&) Institute of Aviation Medicine PLAAF, Beijing 100142, China e-mail: [email protected] W. Lou Air Force Flight Test Bureau, Xi’an 710089, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_40

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1 Introduction Ergonomics level of aircraft cockpit display interface, which is the direct medium pilot control aircraft, affect the effectiveness of aircraft control. Large-size active-matrix liquid crystal display is increasingly used in modern cockpit. As the previous switch and button were replaced by all the information on the integrated screen, aviation designers face a new challenge of how to design a human– machine interface in order to make the operation more secure and efficient. Therefore, ergonomics evaluation of human–computer interface is particularly important. Usability assessment methods of aircraft cockpit man–machine interface are divided into fundamental research and application research according to the research purpose, and also are divided into qualitative research and quantitative research according to the measurement methods. Specific research often integrated psychology, sociology, and engineering methods. Qualitative research methods include: ① Subjective survey: Subjective questionnaire was used to collect the respondents of people, self-interest, and other psychological reaction data [1]; ② Observation method: A group of experts were trained to observe and evaluate the frequency and characteristics of behavior of observers when performing human– computer interaction [2]. Quantitative research methods include: ① Eye tracker: It is used to record the characteristics of eye movements when processing visual information and to analyze the processing mechanism of visual information. Commonly used eye movement indicators include fixation point, fixation time, fixation point number, eye movement distance, pupil diameter [3]. Ergonomics researches using eye-tracking technology focused on the impact of visual coding on information perception [4]. Applying this technique to visual searching of dynamic and static image target, it was found that a number of eye movement indicators were sensitive to the evaluation of the display interface and later validated in aviation displays [5]. Tullis and Schum [6, 7] studied the identification efficiency of digital display and graphic display information. Yeh [8] studied the effect of color and brightness coding on the identification of electronic map information. ② Performance measurement: Mainly through the flight simulator, the subjects were asked to complete the same flight mission with different difficulty interface in flight simulator, and flight performance scores were used as the basis for ergonomics evaluation [9]. With the “user-centered” design concept gradually applied to all stages of aircraft design and manufacture, man–machine interface designers should also consider from the user’s point of view, however, it is difficult to implement the ergonomics concept due to the lack of quantifiable design standards. Now cockpit man–machine interface assessment is mainly depended on subjective comments of flight experts according to their own feelings. Sometimes opposite opinions could occur due to the limited number of experts. In addition, designers may find it difficult to determine the direction of the design change if pilots are not satisfied with the design of the man–machine interface because of the lack of objective indicators. Therefore, in this study, the eye movement data of pilots were recorded

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during visual searching task on the cockpit display interface, so as to provide technical support for optimization and improvement of the large screen display interface of the cockpit.

2 Methods 2.1

Subjects

A total of 44 subjects (36 ± 6 years), with total flight time (2142 ± 1723 h), attended the experiment. The protocol passed the ethics committee’s review, and the participants signed an informed consent form before the experiment. The study was approved by the Logistics Department for Civilian Ethics Committee of Beihang University. All subjects signed a consent form that informed them the aim and procedure of the experiment.

2.2

Equipment

The instrument used is ASL-D6 Eye View Monitoring System manufactured by Applied Science Laboratory (ASL). The instrument sampling rate is 60 Hz. Record indicators include eye track map, eye movement time (including fixation time, back view time, eye time, eye movement distance, pupil diameter).

2.3

Experiment Design

Randomized block design was used. Subjects were asked to complete a visual search task as soon as possible. Seven typical flight human–machine interface images were adapted according to varied factors such as 12 quadrants, 6 colors, and 10 presentation encodings which would affect ergonomics design by a self-developed computer program. The pilots were asked to search a target picture with full information intercepted from the typical images, and eye tracker was used to record the eye movement data during the task. Since the cockpit integrated display is widescreen, and for a more detailed analysis, the typical picture is artificially divided into 12 quadrants (Fig. 1), each quadrant can involve a “target” picture, including color, presentation encoding. At the beginning of each question, the “target” appears first, and then the “target” disappears. The typical picture with the “target” appears. The subject should locate the target with eyes as soon as possible. Each picture presentation time is 200 ms. Program records eye tracking data acquired by smart eye. A total of 174 questions were compiled and presented at random order.

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1

2

3

4

5

6

7

8

9

10

11

12

Fig. 1 Twelve quadrants diagram

2.4

Test Procedure

Illumination of experiment environment was in daytime mode from 8:00 to 17:00 (20–220 lx). The participants were informed of the test purposes and precautions before the test. ① The pilot adjusts sitting and scales using eye tracker. Double-click to start testing. ② After reading the introduction, click “next” to enter practice and complete three exercises. ③ After all three exercises were completed correctly, you can begin a formal test. ④ The “target” to be found appeared first; the pilot remembers it and then clicks space key to continue. ⑤ The big picture with target appears. ⑥ The pilot found the target and clicked the space key to confirm. ⑦ Automatically enter the next question. Loops ④–⑥ steps until the end of the test (Fig. 2).

Fig. 2 “Target” and larger figure with target

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351

Data Statistics

SPSS 19.0 statistical software package was used for data analysis, and all the test data are expressed by M ± SD (s). Multivariate test was used for analysis; P < 0.05 was set as the threshold value with significant difference in statistics.

3 Results 3.1

Visual Sensitive Area for Large Screen PFD

The AOI fixation time, the number of fixation points, and the total fixation time of 12 quadrants of the typical primary display are analyzed as shown in Table 1. The multivariate test analysis (subjects, typical images, quadrants) showed statistically significant differences among the typical images (Spent time in AOI F(6.5235) = 39.32, Number of fixation points F(6.5235) = 41.11, Total fixation duration (6.5235) = 39.98, P < 0.001); There was statistical difference among different quadrants (Spent time in AOI F(11.5230) = 5.86, Number of fixation points F (11.5230) = 5.17, Total fixation duration F(11.5230) = 5.18, P < 0.001); There was an interaction effect between images and quadrants (Spent time in AOI F(56.5185) = 7.40, Number of fixation points F(56.5185) = 6.65, Total fixation duration F(56.5185) = 7.01, P < 0.001). LSD-t Post Hoc test showed that 12 quadrants should be divided into three categories. The visual dominant regions were quadrants 1, 5, 7 and the worst visual regions quadrants were 10 and 12. The rest were general visual regions.

Table 1 Twelve quadrant AOI descriptive statistical analysis results Dependent variable

Spent time in AOI

1 2 3 4 5 6 7 8 9 10 11 12

2.80 3.10 3.82 3.92 2.95 3.26 2.78 3.61 3.73 4.13 2.91 3.82

± ± ± ± ± ± ± ± ± ± ± ±

3.72 4.20 4.64 5.25 3.54 4.00 3.45 4.73 4.11 5.01 2.83 3.71

Fixation points 14.86 16.75 19.48 19.45 14.08 19.03 14.47 17.95 18.53 19.54 15.03 19.18

± ± ± ± ± ± ± ± ± ± ± ±

21.20 23.17 24.19 26.65 19.56 30.55 19.06 23.75 22.38 24.01 15.21 20.80

Total fixation duration 2.33 2.67 3.08 3.05 2.31 2.99 2.44 2.88 2.94 3.11 2.38 3.03

± ± ± ± ± ± ± ± ± ± ± ±

3.28 3.56 3.66 4.07 3.07 4.06 2.97 3.69 3.35 3.83 2.43 3.16

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Table 2 SNK results of six color

Spent time in AOI

Fixation points

Total Fixation duration

3.2

Six colors

N

Subset 1

Red Blue Red rose White Yellow Green Red Blue Red rose White Yellow Green Red Blue Red rose White Yellow Green

317 80 197 714 158 1811 317 80 197 714 158 1811 317 80 197 714 317 80

1.64

2 2.58 3.05 3.45

3

3.05 3.45 5.29 4.30

7.42 12.59 14.44 16.49 21.80 21.92 1.30 2.04 2.38 2.57 3.31 4.02

Results of Different Colors

Factor analysis was used, and there were significant differences among 6 colors (Spent time in AOI time F(5.5236) = 15.49, Number of fixation points F(5.5236) = 26.23, Total fixation duration F(5.5236) = 24.46, P < 0.001), 7 typical pictures (Spent time in AOI F(11.5230) = 5.60, Number of fixation points F(11.5230) = 4.24, Total fixation duration F(11.5230) = 4.05, P < 0.001), and 12 quadrants groups (P < 0.01); and the interaction among three factors were significant (P < 0.01); SNK Post Hoc test results were shown in Table 2. According to the results, red was the optic color; yellow and green were the worst color; blue, rose red, and white were average.

3.3

Results of Encoding Methods

There were significant differences among the 10 presentation encodings, 7 typical pictures, and 12 quadrants (P < 0.01). The interaction among the three factors was significant (P < 0.01). SNK test results of 10 encoding presentations are shown in Table 3. According to presentation encodings, white character with white borders

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Table 3 SNK test results of 10 encoding presentations

Spent time in AOI

Fixation points

Total fixation duration

Encoding

N

Subset 1 2

White character with white borders White character with red shading Black character with red shading Black character with yellow shading Black character with green shading Green character with yellow borders Green character with white borders White character Green character Black character with green shading yellow borders White character with white borders White character with red shading Black character with red shading Black character with yellow shading Black character with green shading Green character with yellow borders Green character with white borders White character Green character Black character with green shading yellow borders White character with white borders White character with red shading Black character with red shading Black character with yellow shading Black character with green shading Green character with yellow borders Green character with white borders White character Green character Black character with green shading yellow borders

40 40 159 40 752 40 352 198 747 40

1.19 1.37 1.82 2.04 2.74

40 40 159 40 752 40 352 198 747 40

5.70 6.60 8.92 11.35 14.32

40 40 159 40 752 40 352 198 747 40

0.99 1.11 1.50 1.75 2.27

1.82 2.04 2.74 3.26 3.47

3

4

2.04 2.74 3.26 3.47 3.69 3.88 7.28

11.35 14.32 18.13 18.32 19.32

14.32 18.13 18.32 19.32 21.59 41.38

1.75 2.27 2.92 2.93 2.97

2.27 2.92 2.93 2.97 3.35 6.40

and white character with red shading borders are optic encoding; black character with yellow borders and green shading was the worst; and black character with red or yellow shading, green character with white borders or yellow borders, green character, and white character were average.

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4 Discussion In the 1960s, researchers began to study pilots’ glance patterns based on eye movement data. Eye-tracking data were used to assess pilot glance behavior and to understand how pilots control aircraft attitude, position, and speed of movement in a three-dimensional space, as well as acquiring information from gauges. Glance analysis technology has developed rapidly since the 1980s. This technique is combined with control technology and aircraft flight parameters to evaluate the display design [10]. Kasarkis et al. [11] used an aircraft simulator to simulate the airplane’s simulated landing of seven skilled pilots and ten trainees. By using eye movement analysis technique, it is found that different pilots have different visual scanning rules during takeoff and landing. Experts are more attentive than novices and have a short residence time; experts have a clearer glance pattern. Schriver et al. [12] examined the differences in decision-making between skilled pilots and pilots by verifying the attention–action relationship. Ergonomics experiments on cockpit display interface such as HUD speed, altitude and heading, flight instruction symbol format did not use eye-tracking technology [13]. According to the statistical results, the visual sensitive area of large screen PFD is quadrant 1, 5, 7; the second is quadrant 2, 3, 4, 6, 8, 9, 11; the less sensitive area is quadrant 10, 12. In the 1950s, Fitts and others began to study the eye movement characteristics of pilots when landing, and the eye movement recording technology provides a valuable method to evaluate the importance of new meters, the difficulty of instrument interpretation, and the arrangement of instrument panels, thus forming classic “T” panels [14]. “T” sensitive area should be “2”, “3”, “6”, “7”, “10”, “11”, which is different from the results of this experiment. There are two possible reasons: First, the traditional “T” distribution is the layout of the cockpit instrument. In this experiment, the typical display interface includes not only the pictures related to the instrument display, but also other interface such as the whole system state(menu screen), radar monitoring (graphics category) and other images. Different content will inevitably lead to different screen layout. Second, 56.15% of the subjects were first searching from the first quadrant of the test picture, which is consistent with the facts that subjects follow the top to down and left to right search rules in visual search tasks [15, 16]. The results of different encoding models are of great value in the iterative design of aircraft. According to past research [17] following color coding principles were proposed and should be paid attention to: (1) In a color coding system, up to 6–5 color coding were proposed; (2) the following colors were recommended: yellow, green, purple, green, orange; (3) the brightness contrast between target and background the should be sufficiently large; (4) the saturation of the selected color shouldn’t be too high; (5) color coding should be used in combination with other coding methods. However, in the research results of color analysis, “yellow” theory should be visually sensitive color, especially in the black background. Its work efficiency should be second only to “red”; however, its work efficiency is poor in this study. After sampling the color samples, it is found that the “yellow” RGB

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values in the experiment picture are not the usual “255, 255, 0”. According to the picture used in the experiment, there are three “yellow” in the picture, but RGB values are very different. This shows that the design unit at the beginning of the design did not seriously implement the recommended color, resulting in ergonomics differences. On the other hand, it also shows the role of this study in the evaluation of aircraft design. According to different ways of information presentation encoding, Hackman and Tinker [18] investigated readings of performance of different color characters with different color papers on the basis of perception time, fixation frequency, and fixation duration. The results showed that the black letter with yellow background, the red letter with white background, the green letter with red background, and the black letter with white background had the best clarity. And black letter with the purple background, light yellow letter with white background, and red letter with green background font clarity are the worst. This is similar to the results of this study, but the difference is that Hackman conducted a reading test and only the foreground and background colors were compared. In the present study, it is a search experiment that examines the characters of different encoding methods and was tested using visual search task to find out the ergonomics differences. Therefore, the research results provide ergonomics basis for optimizing the design of human–machine interface. In summary, this study used the eye-tracking system to observe the visual search performance of cockpit static human–machine interface in more detail. However, the task did not combine with the actual flight performance; therefore, we need to further verify the results in dynamic environment and flight mission.

References 1. Kaber DB, Alexander AL, Stelzer EM, Kim SH, Kaufmann K, Hsiang SM (2008) Perceived clutter in advanced cockpit displays: measurement and modeling with experienced pilots. Aviat Space Environ Med 79:1007–1018 2. Duchowski A (2007) Eye tracking methodology: theory and practice. Springer, New York 3. Moacdieh NM, Sarter NB (2012) Eye tracking metrics: a toolbox for assessing the effects of clutter on attention allocation. Proc Hum Factors Ergon Soc Ann Meet 56(1):1366–1370 4. Moacdieh NM, Prinet JC, Sarter NB (2013) Effects of modern primary flight display clutter evidence from performance and eye tracking data. Proc Hum Factors Ergon Soc Ann Meet 57(1):11–15 5. Treisman AM, Gelade G (1980) A feature-integration theory of attention. Cog Psych 12: 97–136 6. TullisT S (1981) An evaluation of alphanumeric, graphic, and color information displays. Hum Factors 23(5):541–550 7. Schum DA (1991) The weighting of testimony in judicial proceeding from sources having reduced credibility. Hum Factors 33(2):172–182 8. Yeh M, Wickens CD (2001) Attentional filtering in the design of electronic map displays: a comparison of color coding, intensity coding, and decluttering techniques. Hum Factors 43(4):543–562

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9. Eckstein MP, Thomas JP, Palmer J, Shimozaki SS (2000) A signal detection model predicts the effects of setsize in visual search accuracy for feature, conjunction and disjunction displays. Percept Psychophys 62(3):425–451 10. Backs RW, Walrath LC (1992) Eye movement and pupillary response indices of mental workload during visual search of symbolic displays. Appl Ergon 23:243–254 11. Kasarsikis P, Stehwien J (2001) Comparison on expert and novice scan behaviors during VFR flight. In: The 11th international symposium on aviation psychology. The Ohio University, Columbus, pp 1–6 12. Schriver AT, Morrow DG, Wickens CD, Talleur DA (2008) Expertise differences in attention strategies related to pilot decision making. Hum Factors 50(6):864–878 13. Guo X, Xiong D, Xiong Y, Yi L, Ma X (2007) Effects of the display formats on pilots’ cognitive performance with head-up display velocity, height and heading information in fighter. Chin J Aviat Med 18(2):84–90 14. Kim B, Dong Y, Kim S et al (2007) Development of integrated analysis system and tool of perception, recognition and behavior for web usability test: with-emphasis on eye-tracking, mouse-tracking and retrospective think aloud. In: Kim B (ed) Usability and internationalization. Springer, Berlin, pp 113–121 15. Gould JD, Peeples DR (1970) Eye movements during visual search and discrimination of meaningless, symbol, and object patterns. J Exp Psychol 85(1):51–55 16. Damin Zhuang, Rui Wang (2003) Research of target identification based on cognitive characteristic. J Beijing Univ Aeronaut Astronaut 29(11):1051–1054 (in Chinese) 17. Narborough-Hall, Niebur E (2004) Texture contrast attracts overt visual attention in natural scenes. Eur J Neurosci 19(3):783–789 18. Tinker MS (1958) Recent studies of eye movements in reading. Psychol Bull 55(4):215–231

Position of Heading Information Presented in HUD for Aircraft Cockpit Xiaochao Guo, Yanyan Wang, Qingfeng Liu and Duanqin Xiong

Abstract An experiment was conducted to research the optimal position of heading information in display formats of fighter HUD. Two display formats were programmed according to the guidelines in ARP5288 or the “Basic T” arrangement in AC25-11B, i.e. display format (a) in which heading information were located on the attitude, and display format (b) in which heading information were positioned below the attitude. In the present study, 151 pilots participated in user performance test in context of simulated A/A and A/G flight tasks for heading information reading and state judgment of aircraft based on the display formats. The results were that the main effect of display formats was marginally significant for CR (P = 0.05) and very significant for CRT (P < 0.001). The display format (b) was maybe slightly better than that of display format (a), or both of the display formats were compatible. The pilots preferred the display format (a) to (b) in a vote (about 98% vs. 30%) after experimental uses, although the display format (b) might be cognized slightly faster than the display format (a). Other findings were also discussed.





Keywords Head-up display (HUD) Display format Aircraft cockpit Heading Direction of flight Ergonomics Human factors







1 Introduction Head-up display (HUD) is one of the primary displays in aircraft cockpit that projects primary flight information (e.g. attitude, air data, guidance) on a transparent screen (combiner) in the pilot’s forward field of view, between the pilot and the windshield [1]. HUD was installed above the primary display panel front of the X. Guo  Y. Wang  Q. Liu  D. Xiong (&) Institute of Aviation Medicine PLAAF, Beijing 100142, China e-mail: [email protected] X. Guo e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_41

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pilot in fighter cockpit such as F22 [2] but hanged on the roof over the head of the pilot in the flight deck of large aeroplanes such as Boeing 787 and C919 [3, 4]. The display format of HUD was specified in SAE ARP5288 that heading information should be centred on the attitude information and the “present values” of heading should be located within the pilot’s central vision when looking through the HUD [5], while CS 25.1321 specified that the instrument that most effectively indicates direction of flight must be adjacent to and directly below the instrument in the top centre position [6], i.e. the heading information below the attitude, so did in FAR25 and CCAR25 [7, 8]. The positions of heading information were contrasted in display formats of fighter HUD on the basis of user performance test (UPT) for user-centred design (UCD) of aircraft cockpit in this paper.

2 Method 2.1

Heading Information in Display Formats of HUD

A heading scale with “present values” in digital window and “command value” indicated by command tick was programmed in display format (a) in which heading information were located on the attitude, and in display format (b) in which heading information were positioned below the attitude, as shown in Fig. 1.

Fig. 1 Position of heading information in HUD format. a Top, b bottom

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The display formats were dynamically driven in simulated flight tasks in the test. The flight tasks were Air-to-Air (A/A) task or Air-to-Ground (A/G) task.

2.2

Experimental Design

A within-subject design was in the experiment with flight tasks (2), display formats (2) and cognitive tasks (2) that were heading information reading and state judgment of aircraft by integrating heading with other flight information. The correct reaction (CR) and the correct reaction time (CRT) were recorded as indices of UPT in the experiment by PC. A subjective rating of usability was made on the scale of bad, moderate, good or excellent by participants after the experimental test, and the percentages of being approved were also statistically contrasted.

2.3

Participants of Pilots

There were 151 male fighter pilots taking part in the experiment. All the participants were volunteers and paid after completion of the works.

3 Results The results are presented in Table 1.

4 Discussions 4.1

A/A Versus A/G Flight Tasks

The main effect of flight tasks for CR in Table 1 was significant (F(1,134) = 14.15, P < 0.001). The interactions of flight tasks and occupational experience as shown in Fig. 2 were significant (F(3,134) = 3.26, P < 0.05, for flight grade; F(2,134) = 4.23, P < 0.05, for HUD system; F(2,134) = 4.04, P < 0.05, for flight grade and HUD system). The experienced pilots who ever used HUD system A and B had better performance than that of ones who only operated fighter without HUD (P < 0.05). The main effect of flight tasks for CRT was significant (F(1,45) = 21.50, P < 0.001). The mean CRT in A/A was faster than that in A/G (1.88 s vs. 2.45 s). The interactions of flight tasks and occupational experience were not significant.

Display Formats of HUD

(a) Heading above attitude (b) Heading below attitude A/G (a) Heading above attitude (b) Heading below attitude Note The data of CRT is the mean value

A/A

Flight tasks

88.74 58.28 78.15

93.38

78.81

85.43

outside the bracket and the

82.78

CRT (s) Information reading

1.70 (1.38) 1.44 (0.96) 2.79 (1.74) 2.02 (1.51) standard deviation inside the

State judgment

87.42

CR (%) Information reading 2.13 (1.62) 2.22 (1.41) 2.44 (1.33) 2.64 (1.48) bracket

State judgment

6.0

92.0

8.0

92.0

24.7

6.7

20.7

6.0

49.3

1.3

52.0

2.0

Pilot comments (%) Excellent Good Moderate

Table 1 Cognitive performances of two display formats of fighter HUD with different position of heading information

20.0

0

19.3

0

Bad

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Fig. 2 Occupational experience groups. a Flight grade, b fighter with HUD, c HUD system

4.2

Display Formats of HUD

The main effect of display formats for CR was marginally significant (F(1,134) = 3.79, P = 0.05) without interactions from occupational experience. It might suggest that the CR of display format (b) was maybe slightly better than that of display format (a), or both of the display formats were compatible whether the position of heading information was put on or below the attitude in the present study. The interactions of display formats for CR were also not significant with flight tasks and cognitive tasks in statistics. The main effect of display formats for CRT was significant (F(1,45) = 9.32, P < 0.005). The heading above the attitude was recognized much slower than itself below the attitude (2.28 s vs. 2.05 s).

4.3

Cognitive Tasks

The main effect of cognitive tasks for CR was significant (F(1,134) = 6.18, P < 0.05) without influence by occupational experience of the pilots in statistics. The CR of information reading was better than that of state judgment (86.14% vs. 76.78%). The main effect of cognitive tasks for CRT was significant (F(1,45) = 11.48, P < 0.005). The CRT of information reading was faster than that of state judgment (1.96 s vs. 2.37 s) especially for A/A flight tasks (F(1,45) = 10.98, P < 0.005).

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Subjective Rating of Participants

It was found that the participants of pilots had accepted the display format (a) of HUD in Fig. 2 whether in A/A (v2 = 216.38, P < 0.001) or A/G (v2 = 226.93, P < 0.001) simulated flight tasks (98.00% vs. 28.67 in A/A; 98.67% vs. 30.67 in A/G). In other words, the pilots preferred the display format positioning heading information on the attitude to the format of heading below the attitude in the present study.

4.5

Position of Heading Information in HUD

It is very interesting that the pilots did the better performance with the display format (b) positioning heading information below the attitude but preferred the display format (a) positioning heading information on the attitude in this study. The potential reasons were that the flight practice was used to the display format (a) for fighter pilots, and the marginal CR difference and slighter faster CRT for the display format (b) were not enough to make a redesign. The pilots’ choice is consistent with the guidelines in ARP5288 [5] that the HUD heading information should be centred on the attitude information, but different from the Basic T arrangement in AC25-11B [1]. However, both of the display formats (a) and (b) about heading information were recommended by GJB300 [9]; the display format (b) may be another choice for HUD in fighter cockpit.

5 Conclusions An experiment was conducted to probe the influence of position of heading information/direction of flight in display formats of aircraft HUD. Two display formats were designed according to GJB300 and SAE ARP5288 or the “Basic T” arrangement in AC25-11B cited from FAR25 as well as CS-25 and CCAR-25-R4, that is, display format (a) in which heading information were located on the attitude and display format (b) in which heading information were positioned below the attitude. Totally, 151 pilots participated in the experiment with user performance test in context of simulated A/A and A/G flight tasks. The participants gave their cognitive responses to heading information reading and state judgment of aircraft based on the display formats in dynamical operation. The results were found that the CR of display format (b) was maybe slightly better than that of display formats (a), or both of the display formats were compatible whether the position of heading information was put on or below the attitude in the present study because of their marginal difference in statistics. The pilots preferred the display format (a) to (b) in

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a vote (about 98% vs. 30%) after experimental uses, although the display format (b) might be cognized slightly faster than the former. Compliance with Ethical Standards The survey was approved by the Academic Ethics Committee of Institute of Aviation Medicine PLAAF. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. U.S. Department of Transportation Federal Aviation Administration (2014) Electronic Flight Displays (AC25-11B) 2. Lockheed Martin (2018) F-22 Raptor. https://lockheedmartin.com/us/products/f22.html?_ga=2. 95463836.1641045911.1521107184-1468719110.1521107184. Cited 15 Mar 2018 3. Boing (2017) 787 Dreamliner by design: state of the art flight deck. http://www.boeing.com/ commercial/787/by-design/#/flight-deck. Cited 15 Mar 2018 4. Zhao L (2014) Xi calls for large aircraft to boost power. https://www.chinadaily.com.cn/china/ 2014-05/25/content_17538934.htm. Cited 15 Mar 2018 5. SAE (2008) ARP5288 transport category airplane head up display (HUD) systems 6. European Aviation Safety Agency (2016) Certification specifications and acceptable means of compliance for large aeroplanes CS-25 7. Federal Aviation Administration (2018) Federal Aviation Regulations Part 25—Airworthiness standards: transport category airplanes (FAR25) 8. Civil Aviation Administration of China (2011) China Civil Aviation Regulations Part 25— Airworthiness standards: transport category airplanes (CCAR-25-R4) 9. GJB300-1987 Display symbology for head up display of aircraft. Military standard Publishing House of the General Armament Department, Beijing

Human–Computer Interaction Design Testing Based on Decision-Making Process Model Baiqiao Huang, Pengyi Zhang and Chuan Wang

Abstract According to the disadvantage that traditional software interface testing focuses on the overall evaluation of the satisfaction with human–computer interaction (HCI) without further consideration of the decision-making process rules of human in HCI and gives insufficient guidance for interface design. An approach for test of software HCI design based on decision-making model is proposed by analyzing the information visual search and logic decision-making process in HCI process and considering the effect of software interface design elements on decision-making. The test mainly includes tests of interface color matching, visual search efficiency, logic decision-making, and time pressure. The test elements provide better guidance for the design of software interface. Keywords Man-machine-environment system engineering (MMESE) Human–computer interaction design Decision-making process model Visual search Software test





1 Introduction Traditional software design attaches importance to the satisfaction of business needs other than the implementation method and the efficiency obtained. Traditional software test mainly validates the implementation of needs with softB. Huang  P. Zhang China Ocean Security system of system Innovation Center, Beijing 100094, China e-mail: [email protected] B. Huang  P. Zhang System Engineering Research Institute of China State Shipbuilding Corporation, Beijing 100094, China C. Wang (&) Naval Medical Research Institute, Naval Military Medical University, Shanghai 200433, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_42

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ware functions, performance, etc., and correct processing of various boundary and abnormal input by software with the needs satisfied. The focus is mainly put on the consistency between operation and user manuals of the test software, even if the human–computer interface (HCI) test contained. It does not explore deeper into the detail process in which an operator receives and processes information in the course of software using. With the emerging of human-centered design concept, more attention has been paid to HCI design in software design [1], followed by the test of software UI design by users that can be called software usability test [2–4]. Usability is given an international standard definition as the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction in a specified context of use. Effectiveness means the satisfaction of HCI design with functional requirements. Efficiency includes time efficiency, accuracy, and safety. Satisfaction is the extent to which users sensually satisfy with human– computer process. Software usability test generally tests the rationality of design one by one in a checklist form and evaluates the overall satisfaction with questionnaires. Traditional usability tests do not touch the detail process and efficiency of processing in terms of information receiving and decision-making in HCI course. Such test has limited guidance for the details of UI design. We believe that for the test of UI HCI design further exploration should be made to the detail process of information receiving, information processing, and decision-making by human in HCI process, in which way more accurate guidance will be generated for UI design. This paper comes up with a method for the test of HCI design based on decision-making model in which the rationality of software UI design is analyzed based on the effect of the use of software interface information in the software process by human on information receiving, processing, and decision-making by human. The test elements are designed by taking the effect of layout of software interface on the visual search efficiency of human, adaptability of software interface color matching to ambient lighting, rationality of decision-making logic in software, and time pressure arising from a comparison between “task completion time” and “given task time” into account.

2 HCI Decision-Making Process Model and UI Design Elements of Software 2.1

HCI Decision-Making Process Model of Software

In order to analyze the influencing factors in HCI course in a systematic manner and improve the comprehensiveness of problem analysis, man-machine-environment system engineering (MMESE) is used to guide the analysis. MMESE is a branch of science that properly deals with the relations among human, computer, and environment elements and makes in-depth research on the optimal combination of

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Fig. 1 Decision-making model of software using

human–computer–environment system by using system science theories and system engineering methods [5]. Software system is a typical man-machine-environment system, where “man” is the operator of software, “machine” is software itself, and “environment” includes not only hardware and software based on which software is operated but also the micro-climate environment where human and devices are located. While, HCI process is essentially the process in which human receives information from software interface, processes it , make decision and operates software. Information receiving is subject to the effect of color matching of software interface and layout of interface information. Information processing will be affected by the quantity of information, i.e., quantity and type, of parameters. The decision-making process is affected by the type and logic of decision-making. All these elements revolve around the decision-making process model of the operator. Rasmussen [6] divided the decision-making process into three types: skill-based decision-making, rule-based decision-making, and knowledge-based decision-making, as shown in Fig. 1. Decision-making of software HCI course is mainly rule-based decision-making process as the use of software generally has agreed operation procedures and rules. The operation will not encounter knowledge-based decision-making until unexpected abnormality occurs in software, in which case prior experience and knowledge are needed for the decision-making of subsequent processing.

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UI Design Elements of Software

With the analysis of the factors affecting HCI process above, the elements of software UI design mainly include interface color matching, information layout design, and functional logic design. Interface color matching design—On the one hand, color matching design of software interface should conform to the long-standing cultural customs of the industrial fields. On the other hand, it should adapt to the lighting conditions of external environment where clear display is capable. For naval equipment, for instance, software interface environment includes electronic lighting environment in cabins, daylight environment with different lighting intensities for day and night in shipboard cabins. The color matching design of software interface also requires the consideration of changes in lighting conditions. For example, day, dusk, and night software interfaces in three color matching styles should be designed for naval command software. These interfaces will correspond to strong sunlight in day, weak sunlight at dusk, and electronic lighting at night. Information layout design—The layout of information on software design will affect the efficiency in obtaining the information as necessary for the operator. The information receiving process of HCI process is a visual search process where the operator quickly searches and locates the information as required by the operation decision-making from much information on the interface. The strategy of search consists of random search and systematic search. Software interface is generally a structural area where the systematic search strategy is used for faster speed. The efficiency of visual search also relates to eye movement rule. On this account, eye movement rule of the operation should be referred to in the design of software interface layout. Key data in relation to decision-making should be organized in a structural form and located in the focal area of eyes so that the operator will quickly search and locate the required information. Functional logic design—Software operation generally belongs to rule-based decision-making process with the complexity subject to the quantity and type of parameters that is involved in decision-making and also to the complexity of decision-making logic. For software functional design, the quantity of parameters that participates in decision-making and complexity of decision-making logic should be minimized with respect to user decision-making so as to improve both efficiency and reliability of decision-making process.

3 Testing of Software HCI Design Software UI design testing may not await the full development of software logic portion. Tests can be performed only if the software interface design has been finished. The test process of software HCI design sorts out the software interface which the sequence in which software functions execute activities corresponds to

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and the layout of function-related information on the interface, both of which serve as the subject of test activities. This is done according to the description of functions in software requirements and by integrating with software UI design. Additionally, the tests are performed in terms of the compatibility of interface color matching design with the environment, efficiency of information visual search, sufficiency of decision-making at software use by users, and time pressure at user operation. We define software as a set of functions S = {F1, F2 … Fn} and software functions as an activity sequence F = {A1, A2 … An}. Each activity corresponds to the set of several parameters on a software interface, and the logic relationship among those parameters A = {P1, P2 … Pn, R(Pi)}. Of course, different activities may correspond to the parameter set on the same interface. The relationship between software function and software interface and among parameters on the interface in terms of decision-making logic is first analyzed prior to the tests.

3.1

Interface Color Matching Test

Human–machine interaction is the basis element for equipment to fulfill its functions and missions. Physical characteristics, physiological characteristics, psychological characteristics, and social characteristics shall be given into full consideration in design process of human–machine interaction for navy equipment so that designed product is able to suit to use by man and improve efficiency and reliability of people’s operation. Interface color matching test assesses the following with the test method of qualitative evaluation: (1) Whether the overall color matching style of the interface meets the agreed industrial specification; (2) Whether there is a strong contrast between interface background color and the color in which interface information is displayed and whether both colors will affect information reading; (3) Whether color matching of interface background conforms to the lighting condition of external environment; (4) Whether color matching of interface background is adjusted with consideration of the changes in the lighting condition of external environment.

3.2

Visual Search Efficiency Test with Consideration of Eye Movement Rules

Each operation in the operation sequence of software functions is a process in which the operator makes a decision according to the information provided by the

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software interface makes a choice and performs execution according, followed by making a choice and performing the execution. However, decision-making has a prerequisite that interface information should be located and obtained by visual search. The operator has some behavioral characteristics in eye movement when observing the software interface. The track of eye movement of the operator may be recorded with an eye tracker to make statistics of the first focus time and accumulated focus time of areas on the interface. The accumulated focus time is characterized in different colors to form a heat map of the software interface that intuitively reflects the extent to which the operator pays attention to interface areas. The visual search efficiency test assesses the following with the test method of qualitative evaluation: (1) In case of low quantity of information and arrangement in the same area, the state of such area in the heat map will be assessed for consistency with the importance of such function. That means, if the function is more important, its information should be arranged in the critical focus area; (2) In case of high quantity of information and arrangement in different areas, the distribution of areas where the information is arranged will be assessed for consistency with the track rule of eye movement of the operator.

3.3

Decision-Making Logic Test

Software operation decision-making generally belongs to the rule-based decision-making process. These rules make the decision-making logic. Decision-making logic may be simple single condition single parameter decision R (a) or single condition multi-parameter decision R(a, b, c…) or combined condition decision R1 and (R2 or R3), just similar to the decision condition of conditional statement in software code. The complexity of decision-making logic has a direct effect on time efficiency and correctness at the time of using by the operator. Decision-making logic test focuses on providing a better decision-making logic scheme for the designers. For software interface design, however, decision-making logic remains unchanged, but the change in the way of parameter presentation also improves decision-making efficiency. For example, more visual presentation mode with graphical control will be used as a substitute of direct character presentation mode. Decision-making logic test generally assesses the following with the combined qualitative and quantitative test method: (1) Parameters and decision-making logic are checked for satisfaction with functional requirements of the software, which means that correctness and sufficiency of decision-making logic is checked; and (2) Decision-making logic design is assessed for rationality and for existence of more convenient and efficient decision-making logic with software function

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satisfied. An improved logical decision-making scheme is proposed. To prove a more effective improvement scheme, design of a test for the “response time” of user operation is also required. The “response time” in prior scheme and improvement scheme will be recorded for comparison.

3.4

Time Pressure Test

The operator is subject to the business requirements when operating the software function. Each function requires that the operator must complete it with certain time scope, and we call such period of time “given task time.” The time with which users actually execute the software function is called “task completion time.” The ratio of “task completion time” and “given task time” is called “time pressure” indicator which represents the pressure on time the operator burdens when executing the function. Time pressure has greater effect on working performance. Too high time pressure results in tension of the operator, the result of which is increased wrong decisions. However, too low time pressure also leads to slack operator who will also make more wrong decisions. The purpose of time pressure test is to analyze the “given task time” of software function and design the “task completion time” for the test to obtain the “time pressure” indicator. Reasonable suggestions for improvement will be made in case of too high or too low time pressure indicator.

4 Conclusions The effect of software interface factor in HCI decision-making process on the efficiency of software use is analyzed with the man-machine-environment system engineering method. Importance is attached to visual search process and logic decision-making process. On this basis, it proposes a method for the test of software HCI design based on decision-making process model. The test method mainly includes interface color matching, visual search efficiency, logical decision-making, and time pressure tests. The method for the test of software HCI design based on decision-making model further allows for the effect of software interface design on HCI detail process. It is of higher significance in design guidance compared to traditional software interface tests.

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References 1. Dong J, Fu L, Rao P et al. (2013) Human-computer interaction: user-centered design and evaluation [M] 2. Sauro J, Lewis JR (2012) Quantifying the user experience: practical statistics for user research [M] 3. Dumas J, Redish JC (1999) A practical guide to usability testing, Rev edn. Intellect Led, London 4. Rubin J (2008) Handbook of usability testing: how to plan, design and conduct effective tests. Wiley, New York 5. Long Z (1993) Man-machine-environment system engineering theory and its significance in productivity development. In: Progress in man-machine-environment system engineering research, vol 01. Beijing Science and Technology Press, Beijing, pp 2–13 6. Rasmussen J (1983) Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. J IEEE Trans Syst Man Cybern 13(3):257–266

Contact Position Relation Between Car Bumpers and Lower Limbs of Pedestrians Involved in Crashes Quan Yuan, Song Chen, Chuanzhou Qin and Haojie Yang

Abstract Contact between lower limbs of pedestrian and bumper of passenger car is the first impact position in the vehicle to pedestrian crashes. Based on the principles of anthropotomy, anthropometry, and the statistic of traffic crashes, the contact position relation between bumper of passenger car and lower limbs of pedestrian in China is analyzed. According to the classification statistics of the crashes involving pedestrian, the physical dimensions of vehicle and pedestrian are applied to analyze the position relation mentioned above, including lateral, anterior, and posterior of human body impacted by frontal body of car. Considering the changes of position of pedestrians, the proportions of different contact position relations under Chinese traffic status are obtained. Dimension scope of car bumper covers the whole area of knee joint of Chinese pedestrians, and the contact position between bumper and lower limbs is knee joint and upper leg part. For female, the injury possibility of upper legs is higher than male. The results can provide insights for pedestrian protection and crash simulation. Keywords Pedestrian crashes

 Bumper of car  Lower limbs  Contact position

1 Introduction In China, the phenomenon of vehicle-pedestrian mixed traffic is prevalent in many regions. Pedestrians and cyclists are the most vulnerable groups in the road and are the main factors that cause traffic crashes. The crash that pedestrian is hit by vehicle is the common and frequently-occurring crash type in urban road of our country. It is shown from the crash statistics in 2016 [1]: The number of deaths and injuries of pedestrian traffic in China was 16,724 people and 37,282 people, respectively, accounting for 26.51 and 16.46% of the total number of traffic crashes. The inciQ. Yuan (&)  S. Chen  C. Qin  H. Yang State Key Laboratory of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_43

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dence of pedestrian crashes keeps high, and the injury severity of pedestrians in vulnerable road users is the highest [2], which has attracted wide attention in the society, and it is urgent to develop scientific and effective methods for its research and analysis. Pedestrian injury is a complicated problem to be considered synthetically from kinematics, dynamics, and biomechanics [3]. It is related to the factors such as collision velocity and impact morphology. Therefore, the influence of different factors on pedestrian injury is investigated, respectively, which shall be verified with significant amounts of data or simulations [4]. From the 1970s, the investigation of pedestrian crashes at home and abroad showed that [5–7] lower limb injury was the main cause of disability in pedestrian collision crashes. The bumper and leading edge of the engine hood are the main causes of lower limb injury. The commonly caused injuries are: knee injury, long bone fracture (including femoral fracture, tibia fracture, ligament tear, and strain), patella fracture, ankle joint, foot dislocation, etc. Transverse shear and bending are considered to be the most important causes of lower limb injury. According to the statistical result of the pedestrian crash classification, the contact position characteristics between the bumper and the lower limb are classified and analyzed by using the statistical size parameters of the vehicle and the human body. Based on the principle of human body size measurement and application in ergonomics, the relative position relation distribution of common car bumper and different pedestrian’s lower limbs in China’s road traffic condition is obtained, which provides the reference for pedestrian protection and collision simulation research.

2 Statistics of Contact Characteristics of Pedestrian Crashes For actual pedestrian crash in automobile accidents, the specific situation of the collision course depends on the speed and type of the vehicle and the height of the engine hood, the height of the human body, etc. Generally, braking is to be performed before the vehicle collides with the pedestrian, so the most crashes happened under low speed. According to the data collected in 228 pedestrian crashes in car accidents of Shandong province during 2016–2017, the motion characteristics of pedestrians were obtained, including crossing the road, walking along the road, standing on the side of the road, walking on the road, and working on the road. In the statistics on the contact position of the human and vehicle on the road, the pedestrian crossing the road is about 60% of the total number of crashes recorded by the pedestrian movement, and the contact position of the road surface is about 14% among the pedestrian crosswalk. It can be seen that most of the pedestrian crash in automobile collisions occur in the course of car straight ahead and the pedestrian crossing road. In addition, it is necessary to classify the AIS values of pedestrian injury and human body injury.

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According to the classification of the brand of vehicles, the model statistics of 228 pedestrian crashes in automobile accidents show that the proportion of Dongfeng, Volkswagen, Buick, Hyundai, Wuling, and Changan are close to the other, accounting for 37% of the total, and the remaining 30 kinds of models are more dispersed. The vehicle’s traffic characteristic parameters include the motion characteristics of the vehicle (straight, turn, reverse), driving behavior (braking, steering, escape, no), and collision speed. Among the results of the collision speed statistics of cars, the rate of 41–50 km/h was the highest, and the mortality of pedestrians increased with the speed of collision.

3 Human-Vehicle Characteristic Size 3.1

Size Characteristics of the Lower Limb Structure of Human

The main size (mm) of the lower limb of China’s human body is listed in Table 1 [8] by GB/T10000-88 Chinese adult human body size. The lower limb bones of the human body consist primarily of the femur, the patella, the knee, the tibia, the fibula, the ankle, and the foot bone, as shown in Fig. 1 [9], where the knee is the largest and most complex joint of the human body, which is composed of the femur, the tibia, and the patella and is covered with cartilage thereon. The stability of the knee joint is mainly maintained by the surrounding ligaments and tendons, the medial collateral ligaments, and the lateral collateral ligaments protect the knee joint against varus and valgus, the anterior cruciate ligament, and the posterior cruciate ligament provide stability in the anterior and posterior direction of the knee joint. The quadriceps tendon is the muscle extension of the anterior part of the thigh to the surface part of the patella, which acts as an extension of the knee. Thus, the knee joint becomes an important movement center of the lower limb.

Table 1 Human dimensions of Chinese adults

Upper leg length Lower leg length Perineum height Tibia point height

Male (aged 18–60) P5 P50

P95

Female (aged 18–55) P5 P50

P95

428 338 728 409

505 505 856 481

402 313 673 377

476 376 792 444

465 369 790 444

438 344 732 410

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Fig. 1 Human lower limb structure

3.2

Traffic Characteristics of Pedestrians

Pedestrians are vulnerable road users without protected measures in the traffic system and are most vulnerable to injuries in road traffic crashes, and injury severity is also serious. The freedom of the pedestrian is large, and the speed difference between driving by car and walking on foot is great. The average walking speed of pedestrians is related to age and sex. Women’s movements and reactions are slower than men. In the statistics of 228 pedestrian crashes, the proportion of men and women is close to 3:2. When the pedestrian is walking or running, the body height dimension is reduced slightly due to the motion amplitude, which will affect the possible human-vehicle contact position.

3.3

Size Features of Bumper Structure

The front-end shape feature of the car is an important aspect for the character analysis of pedestrian crash in automobile collision. It mainly includes basic shape parameters of the whole car and specific three parts in the front end (bumper, engine hood, and front windshield). The front-end shape characteristic parameters of 25 domestic car models are counted, and the height value of the front bumper of the vehicle is shown in Fig. 2. It is shown that most of the car front bumper has a height of less than 0.6 m to the ground, the upper edge height of the bumper is 500– 570 mm, and the lower edge height is 200–390 mm; at the same time, according to

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Fig. 2 Height of bumper and knee position of pedestrian

Chinese human body statistics, the tibia point height of 50% men is 444 mm, tibia point height of 50% women is 410 mm, consider the heel height and gait characteristic, the bumper of the car basically covers the human body’s knee joint area.

4 Contact Characteristics of Bumper and Lower Limb Transverse shear and lateral bending are two of the most important responses associated with lower limb injuries during the collision between the bumper and the lower limb. Most of the tibia, femur, and bone injuries are due to the bending moment due to bumper collisions. Kajzer has carried out detailed research on the damage mechanism of knee joint during transverse collision and pointed out that the damage of knee joint is mainly due to the shearing of transverse translational displacement and the mechanism of bending two kinds of injuries caused by angular displacement. The knee joint position of the pedestrian is usually directly impacted by the bumper, and the hysteresis of the femoral movement causes shear dislocation between the articular surfaces, resulting in stretching of the knee ligament and creating a lateral compressive force between the femoral condyle and the tibial condyle. The lateral compression force causes the joint contact surface to have a concentrated stress, and when the stress is too large, lateral fracture occurs between the tibial condyle and the femoral condyle. When the knee joint is bent laterally, the ligament of one side of the articular surface is subjected to tensile force, while the other side is subjected to axial compression force, resulting in stress concentration. Fracture occurs when the stress exceeds the compressive strength of the bone. The injury of the ligament of the knee joint mainly comes from the stretching force in the ligament during the rotation of the joint [10].

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The above study determines the mechanism of injury during the collision between the lower limb of the pedestrian and the bumper, and in order to accurately determine the contact position in the collision, the current model bumper is usually combined with the front profile of the vehicle, and the shape is not obvious, as a result, the most prominent position of the front end of the car in which the vehicle is in contact with the human is taken as the upper edge of the bumper, and the vertical height of bumpers of 21 cars and six SUVs to the ground is measured, and the upper height of the bumper of 20 cars and the three SUVs is 500–570 mm. This is the bumper height range of most vehicles, and the relative positional relationship between the height and the lower limb of human body is shown in Figs. 3 and 4. Based on the national standard human body size, the positional relationship between the human body and the bumper is compared, and the human body sizes of the 18–60 year-old man and the 18–55 year-old man are adopted, including the 1st, 5th, 10th, 50th, 90th, 95th, and 99th percentiles. As can be seen from Fig. 3, for a man, the portion of the car bumper in contact with the lower limb is mainly the knee joint and thigh, wherein the contact point lateral to the lower limb on the bumper includes the tibial condyle of the knee joint, the head of the tibia, the femoral condyle, and the muscles attached to the outside of the femur. The point of contact with the lower limb is mainly the patella and the thigh, and the contact point facing away from the lower limb is mainly the thigh and the lower leg. As Fig. 4, for a woman, the position where the bumper of the car is in contact with the lower limb is mainly the knee joint and the thigh, wherein the contact point on the bumper side to the lower limb is mainly the femur ankle of the knee joint and the muscle attached to the outside of the femur, and the contact point with the forward and back legs of the lower limb is mainly the thigh. Analyzing according to the above-mentioned figures, the probability of the knee joint and the thigh injury of the lower limb of the human body when the vehicle collides is high, and the human body damage statistics in the case of actual crash can be realized, the injury of the lower limb of the pedestrian is mainly caused by

Fig. 3 Height comparison between bumpers and males’ lower limbs

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Fig. 4 Height comparison between bumpers and females’ lower limbs

knee joint injury (including meniscal injury, knee joint capsule injury, anterior and posterior cruciate ligament tears, femoral condyle, and tibial condyle fracture), patella fracture, and long bone fracture (including femoral and tibia fractures, ligament tear, and strain).

5 Conclusion Based on the human anatomy and anthropometry, as well as the statistics of traffic crashes in China, the contact position relationship between the front bumper of more than 20 models of cars and the lower limb of the Chinese people was analyzed, and the following conclusions were recommended. (1) It is shown from the actual measurement on over 20 models of cars, the upper edge height of the front bumper is 500–570 mm, and the lower edge height is 200–390 mm. In addition, according to Chinese human body statistics, the height of 90% of men’s tibia point is 420–481 mm, the height of 90% of the women’s tibia point is 377–444 mm. The bumper of the cars covers the human knee joint area. (2) For both men and women, the position of the car bumper and the lower limb is mainly the knee joint and the thigh, and the probability of the knee joint and the thigh injury of the lower limb of human body during of collision is higher, and the injury of the thigh to the woman is higher than that of the man. (3) In case of collision, the injury to the lower limb of the pedestrian is mainly knee injury, long bone fracture, patella fracture, and so on. The study results contribute to the improvement of vehicle safety design and pedestrian protection.

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Acknowledgements This paper was supported by National Key R&D Program of China (2017YFC0803802). The authors gratefully acknowledge the real-world crash cases provided by the Traffic Forensic Science Center of Shandong Jiaotong University.

References 1. Traffic Management Bureau of the Ministry of Public Security of China (2017) Annual Statistical Report of China Road Traffic Collisions (2016), Beijing 2. Yuan Q, Chen H (2017) Factor comparison of passenger-vehicle to vulnerable road user crashes in Beijing, China. Int J Crashworthiness 22(3):260–270 3. Petrescu L, Petrescu A (2017) Vehicle-pedestrian collisions—aspects regarding pedestrian kinematics, dynamics and biomechanics. IOP Conf Ser Mater Sci Eng 252(1):012001 IOP Publishing 4. Wimmer P, Benedikt M, Huber P et al (2015) Fast calculating surrogate models for leg and head impact in vehicle-pedestrian collision simulations. Traffic Inj Prev 16(sup1):S84–S90 5. Otte D (1994) Influence of the fronthood length for the safety of pedestrians in car accidents and demands to the safety of small vehicles. SAE942232, pp 1923–1933 6. Mizuno K, Kajzer J (2000) Head injuries in vehicle-pedestrian impact. SAE2000-01-157 7. Li L, Yang J, Li W, et al (2005) A study on pedestrian injuries in traffic accidents. Automot Eng 27(1):44–46, 27 (in Chinese) 8. GB10000-88 (1989) Human dimensions of Chinese adults. Standards Press of China, Beijing (in Chinese) 9. Hansen, J, Netter, F (2010) Netter’s anatomy flash cards 10. Zheng W (2004) A study on leg protection during collision with pedestrians. In: Urban vehicles, vol 3 (in Chinese)

Part V

Research on the Man-Environment Relationship

Effect of Tight-Fitting Sportswear Compression on Sports Fatigue Yuxiu Yan, Xuan Li, Ke Liu, Zimin Jin and Jing Jin

Abstract According to the muscle status of runners during exercise, this paper uses the surface electromyography (sEMG) technique to monitor the change of time-domain index RMS under different garment pressure and exercise intensity, and studies the effect of the compression of the seamless knitted tight shorts on fatigue by introducing the heart rate synthesis index. Research shows that during exercise, wearing proper tight-fitting sportswear can reduce muscle vibration caused by impact and muscle contraction, and reduce muscle discharge, thus playing a role in delaying fatigue. But uncomfortably, tight dressing in sportswear not only increases the burden and fatigue in a long time of exercise on the muscles, but also easily harms the body. Keywords Tight-fitting sportswear Time-domain index RMS

 Clothing pressure  sEMG

1 Introduction With the economic development and social progress, all kinds of common sense about the daily health spread quickly. People are gradually beginning to pay attention to the safety and health of sports textiles and put forward a higher demand for it. However, the reasonable range of intrinsic quality of garment products to human physiology has not been regulated so far, especially for the tight-fitting elastic garment, such as the stress index applied to biomechanics and physiological hygiene of the body by the elastic underwear which women often wear. Overpressured clothing will oppress the skin and hinder the movement. The body Y. Yan (&)  X. Li  K. Liu  Z. Jin  J. Jin Zhejiang Sci-Tech University, Hangzhou, China e-mail: [email protected] J. Jin Hangzhou Animation and Game College, Hangzhou Vocational and Technical College, Hangzhou, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_44

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has to do lots of useless work to overcome this resistance and cause fatigue. It increases the body’s ineffective power consumption, makes people feel uncomfortable, affects the wearer’s health, and even makes the internal organs and nervous system tense for a long time [1]. Thus, grasping the effect of fatigue mechanism can not only help garment manufacturers and designers to produce moderate-pressure clothing, but also guide buyers to effectively choose comfortable clothing. The purpose of this paper is to verify the effect of the garment pressure on fatigue by the sEMG and heart rate, according to the muscle status during running exercise.

2 Experimental Design 2.1 2.1.1

Experimental Preparation Subjects

Ten college girls between 157–164 cm height and 47–54 kg weight, whose body size indicators (such as waist circumference, hip circumference, hip height, and hip height) were similar, were selected by the US [TC]2 non-contact 3D body scanner as experimental subjects. All subjects were required no abnormal cardiopulmonary function and respiratory system, no history of ankle joint, ligament, and musculoskeletal injury, no professional running training, and no running within one week before the experiment.

2.1.2

Experiment Garment

The sports tight-fitting seamless shorts fabric was made by 71% nylon, 21% polypropylene, and 8% spandex, with good elasticity and breathability, and the specific style was shown in Fig. 1. The comparative experiment chose three sizes for three different tightness, and the size and the fiber content ratio was shown in Table 1.

2.2 2.2.1

Experimental Program Test Point Selection

There are five muscle sites belong to the greater part of the leg muscle selected as experimental test points, including extensor rectus femoris (A), vastus lateralis (B), gluteus maximus (C), flexor biceps femoris (D), and semitendinosus (E), as shown in Fig. 2.

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Fig. 1 Plane and visualization of garment

Table 1 Garment sizes and fiber ratio Size specification

Waist circumference (cm)

Hip circumference (cm)

Leg opening (cm)

Pants length (cm)

Fiber content (%)

155/64A

60

74

32

40

160/68A

64

78

33

42

165/72A

68

82

34

44

Nylon/ polypropylene/ spandex (71/21/8) Nylon/ polypropylene/ spandex (71/21/8) Nylon/ polypropylene/ spandex (71/21/8)

Fig. 2 Test site of leg muscle

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Test of Tight-Fitting Sportswear Pressure, sEMG and Heart Rate

After entering the laboratory, test subjects sat for 30 min and started until they were stable. First, pressure sensors and trignoTM wireless sensors were attached to the test point of corresponding muscle group in subjects’ legs. And then, the subjects needed to wear a heart rate monitor and tight-fitting shorts to begin the measurement. Specific test steps are as follows: 1. Accelerated jogging: Until the subjects were stable, they began to run on the treadmill for 1 min, and then gradually accelerated to 5.5, 6, 6.5 km/h. 2. Constant running: The subjects kept 5.5, 6, 6.5 km/h for 3 min. 3. Slow jogging: The treadmill speed was gradually adjusted from 5.5, 6, 6.5 km/h to zero within 1 min.

2.3 2.3.1

Experimental Principle The sEMG Theory

The EMG is derived from an activity of motor neurons under the control of CNS. The electrical pulses sent by the central nervous system are delivered to motor neurons via the axons and then to the muscle fibers to cause muscle contraction. At the same time, electric pulses form electric field flow in the soft tissues, which show the potential differences between adjacent electrodes in the test sites and the sum of potential constitutes action potential. The sEMG is formed by the superposition of action potentials in time and space which are composed of potentials [2]. Chen Jin’ao proposed that tight compression had a significant effect on the increase of sEMG [3]; Andrew Fuglevand and Brenda Bigland-Richie suggested that during muscle fatigue, neuron pulse would increase the frequency of delivery and recruit more motor units [4]. Therefore, the sEMG signal can be used to characterize muscle fatigue. Time domain which characterizes a time course potential deviates and then goes back to baseline, which can be used to represent the synchronous excitability and conduction velocity of muscle fibers [2]. This is a method of using the sEMG to estimate the status of muscle in time. Related study suggested as exercise load increasing, new muscle fibers must involve in exercise continuously in order to compensate for the gradual decline of muscle strength due to fatigue. So the a motor neurons are more excited to enhance the synchronization levels of muscle fiber discharge and increase the frequency of nerve impulses generation so that the effect of raising motor units, the number of muscle fibers involved in muscle contraction and the muscle discharge are increased, which led to the continuous rise of the time-domain index [5].

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Indicators Selection of sEMG Test and Analysis

The RMS reflects the effective value of the discharge and represents the average change of sEMG from the time perspective by the mean square root of all EMG amplitude. When in fatigue, the EMG amplitude increases; the RMS increases. So, we can estimate the onset of muscle fatigue and the degree of muscle fatigue by RMS in different time periods [6]. The formula is: sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi RtþT XðtÞ2 dt RMS ¼ T The unit of measurement was second. The sEMG collected during the whole testing process were divided into ten segments on average, and each segment was 30 s. And then the RMS was compared after the analysis.

3 Experimental Results and Analysis 3.1

Pressure Distribution on Tight-Fitting Sportswear

Data on pressure experiment were analyzed by means of average due to the little individual differences between subjects. The results should be analyzed after removing the significant error data, and their average of the pressure at each test point was measured on ten running subjects in the 155/64A, 160/68A, 165/72A tight-fitting shorts. The movement was divided into 20 segments. In Figs. 3, 4, and 5, there were three pressure distribution figures of the five muscle points. As Figs. 3, 4, and 5 showed gluteus maximus (C) suffered the greatest pressure because of the back-and-forth friction of the fabric while running [7], and the test results were consistent with it. The changes of pressure on the vastus lateralis Fig. 3 Distribution of average pressure at each point in 155/64A

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(B) and biceps femoris (D) were more obvious, while on the rectus femoris (A) and semitendinosus (E) were not obvious when the size of the shorts was changed, indicating that the pressure on the vastus lateralis (B), biceps femoris (D) suffered a greater impact on the fatigue of exercise than it on the rectus femoris (A) and semitendinosus (E).

3.2

Changes of RMS and Related Heart Rate Analysis

Figures 3, 4, and 5 showed that the gluteus maximus (C) suffered the greatest pressure when subjects ran in shorts and the tight compression had a significant effect on the growth of sEMG [3]. Thus, the RMS of gluteus maximus (C) was representative. Under the same test conditions, the gluteus maximus (C) was used as the test point to compare and analyze the RMS of different garment sizes. In order to observe easily,

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Fig. 6 RMS analysis chart of different sizes at the same speed

the whole test results were divided into stages I, II; stage I was an adaptation phase, and stage II was a phase after adaptation, as showed in Fig. 6. In Fig. 6, the RMS curve decreased first and then rose in stageIdue to the process of uniform motion. The subjects did not adapt and triggered a lot of motion units at the beginning of the exercise. After gradually adapting to the speed, according to the principle of “saving,” the muscles only needed the minimum motion units involve in the contraction to ensure the movement [5], which was reflected in the decrease of the RMS. In stage II, the RMS of size 160/68A gradually decreased and finally fell below the initial value, indicating that fatigue at gluteus maximus (C) was eased in the size 160/68A; the RMS of size 155/64A decreased in the early period, but increased significantly as time gone on, which aggravated muscle fatigue; the RMS of size 165/72A fluctuates periodically, which was a cycle of spontaneous fatigue and recovery [8]. Therefore, shorts of size 165/72A had no significant effect on the exercise fatigue. Analysis showed that tight clothing compression could promote the efficient coordination of the central nervous system and improve the effectiveness of exercise greatly. During the exercise, wearing proper tight-fitting sportswear effectively reduced the impact, muscle vibration caused by the muscle contraction, muscle discharge and fatigue. Too-tight sportswear would not only increase the burden on muscles and the fatigue in the long time of movement, but also easily cause harm to the body. But low pressure could not be effective in promoting exercise either. When the body under a load movement, its instantaneous heart rate is greater than the HRrest; and the greater the load is, the higher the instantaneous heart rate is [8]. That was why we chose heart rate changes to reflect the body’s fatigue. In order to reflect the process of heart rate changes visually and clearly, heart rate changes (Fig. 7) were drawn with heart rate difference (instantaneous heart rate–resting heart rate) when

Fig. 7 Heart rate difference of different sizes at the same speed

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subjects worn different sizes of tight-fitting shorts at the same speed [8]. During the exercise, the corresponding line of the size 160/68A was always at the bottom, in another words, the heart rate difference of the subjects in the size 160/68A was the least. This showed proper clothing pressure could delay fatigue. The heart rate difference of the size 155/64A was less than the size 165/72A at the early stage of exercise, and then it gradually became greater than the latter. It could be seen that the larger the clothing pressure was during a long time of exercise, the more athletes felt tired.

4 Conclusion 1. Among the five test points, the gluteus maximus suffered the most stressed, and the clothing pressure of vastus lateralis and biceps femoris had a great impact on the fatigue, while of the rectus femoris and semitendinosus affected less. 2. When the body worn tight-fitting shorts during exercise, proper clothing pressure eased impact of exercise and muscle fibrillation caused by contraction. So that the effectiveness of running had been greatly improved. 3. Wearing too-tight clothing, muscle suffered too much pressure, as the RMS fluctuations frequency and the physical activity increased, the body trended to fatigue and was caused functional damage. However, the pressure too small could not be effective in promoting exercise. Acknowledgements The (2016D60SA732872).

project

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Zhejiang

Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhejiang Sci-Tech University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Chen D, Liu H (2012) Clothing pressure test technology based on safe dressing and advances in its evaluation research. J Mod Text Technol 4:53–58 2. Yang X (2004) The fatigue evaluation of young men’s quadriceps by the sEMG. Beijing Sport University, Beijing 3. Chen J (2012) Effect of different compression degrees on variation characteristics of sEMG on lower limb muscles during cycling motion. Soochow University, Soochow 4. Yang Z (1999) Study of the method of extracting fatigue information from EMG signal. Zhejiang University, Zhejiang 5. Jiang L (2012) The research of the evaluation method of the muscle fatigue in elite middle-distance race athletes’ specific movement. Beijing Sport University, Beijing 6. Wang K, Liu J, Song G (2004) The method and application of surface electromyography in estimating sports fatigue. J Anhui Sports Sci 25(3):49–51 7. Li D, Xia T, Li J (2007) Progress in the research on pressure comfort of garment. China Text Lead 11:98–100 8. Cai Q (1999) Study on methods of evaluating physical fatigue according to dynamic heart rate. Chin J Ergon 5(1):27–29

Study on the Effects of Noise on Crew’s Mental Workload in Information Processing Kaixuan Zhao, Weiping Liu, Binhe Fu and Junfeng Nie

Abstract In order to study the effects of noise on the mental workload of armored vehicle crews, the message transmittal task test is conducted with subjective evaluation results and task’s error rate as indicators. The experimental results show that during the 60 min exposure to noise, compared with control group, subjective evaluation results of subjects increased with the increase of noise intensity, but the increase of the subjective evaluation results decreased as noise intensity increased; the error rate of control group was lower than that of the noise group, and the error rate increased with the increase of noise intensity. To sum up, noise has a certain impact on crew’s mental workload, and mental workload of crew increases with the increase of noise intensity. When noise reaches a certain level, it has no significant influence on crew’s mental workload. Keywords Noise

 Armored vehicle  Mental workload  Subjective evaluation

1 Introduction Mental workload is an important factor for crew’s performance during information processing in armored vehicles and may be affected by operation environment, especially in noisy environment. Therefore, it is significant to investigate the influence of noise on crew’s mental workload. Research showed that noise had an impact on individual’s thinking skills and memory functions. When the noise intensity reaches 70 dB(A), it would affect memory functions. When the noise intensity reaches 70 dB(A), it would affect sustained attention and decrease performance [1]. Sandrock found that noise-sensitive mental workload in mathematical tasks was more affected by the noise [2]. Han studied the influence of medium intensity noise on human mental performance. The results showed that moderate noise had a certain impact on mental workload [3]. K. Zhao (&)  W. Liu  B. Fu  J. Nie Academy of Army Armored Forces, Beijing 100072, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_45

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The above studies have focused on impact of noise on performance but have not yet studied the impact of armored vehicle noise on mental workload of crew information operations. Therefore, this study aimed to study the impact of noise on crew’s information workload to provide human effective data for relevant protective measure and ergonomic standards.

2 Method 2.1

Participants

Thirty-six cadets who volunteered to participate in the experiment were selected. Their ages ranged from 20 to 25 years old. All men were in good health. All eyesight (corrected visual acuity) and normal hearing were tested. All of them were right-handed and were familiar with operation of information terminal.

2.2

Experiment Equipment

The experimental instrument is a simulation test platform for vehicle information terminal operations. The system software is developed independently based on Labview programming language to simulate information collection, processing, display, and distribution of armored vehicles on the battlefield [4]. It can control task presentation time and measure correct rate, task completion time, and so on. The experiment used BSWA806 portable type I precision sound level meter to measure noise, the precision is 0.4 dB, the test range is 18–140 dB(A). The subjects’ mental workload was measured by the NASA-TLX subjective evaluation scale. After the experiment, the subjective feelings of each participant were surveyed.

2.3

Experiment Design

The experiment adopts inter-test design. The independent variable is noise intensity. The dependent variable is an indicator of mental workload. Subjective assessment scale score and error rate are the main variables. After the message transmittal task was finalized, the basic conditions of the experiment were set out in Table 1. During the experiment, noise intensity was determined by engine speed at different speeds when armored vehicle started in situ. The noise intensity of armored vehicle was measured under four operating conditions of 0, 850, 1500, and 2000 r/min, as shown in Table 2.

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Table 1 Basic conditions of the experiment Serial number

Experiment condition

Details

1 2 3 4

The number of tasks (times) Experiment interval (s) Information prompts Information input method

10 1 Text prompt 3s Keyboard input

Table 2 Experimental noise intensity under four conditions Condition

Engine speed (r/min)

Noise intensity {dB(A)}

Quiet control group Noise one Noise two Noise three

0 850 1500 2000

30 85 90 95

2.4

Experiment Steps

(1) Before formal experiment, participants were trained on experiment task to ensure that subjects reached proficiency required for experiment task operation and correctly understood instruction words. And participants were concentrated on the experimental process, requirements, and rules to fill in the scales. (2) The subjects completed experiment under quiet environment and noise conditions of 85, 90, and 95 dB(A), respectively. Each exposure time was 60 min. The order of three intensity exposures was random, quiet environment as a control group. (3) In order to eliminate the impact of fatigue effects, using an alternating manner. The experiment system automatically records job performance data. If the subjects did not complete the task within specified time, the single experiment task would stop automatically. (4) Each participant completed the subjective questionnaire after completing the experiment and evaluated mental workload.

3 Results 3.1

Effect of Noise on Crew’s Mental Workload

The mean scores of NASA-TLX scale scores under different noise intensities were statistically analyzed. The change of mean value of NASA-TLX scales with noise intensity is shown in Fig. 1.

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NASA-TLX score

65 60 55 50 45 40

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Fig. 1 NASA-TLX score at different noise intensities

Table 3 ANOVA results of the NASA-TLX scale Between Within groups Total *p < 0.05

Sum of squares

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Mean square

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P

2825.962 2212.213 5038.175

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941.987 69.132

13.626

0.000*

Table 4 LSD multiple comparisons Noise intensity

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Mean difference

P

30

85 90 95 30 90 95 30 85 95

−13.00778 −19.38111 −23.38444 13.00778 −6.37333 −10.37667 19.38111 6.37333 −4.00333

0.002* 0.000* 0.000* 0.002* 0.114 0.012* 0.000* 0.114 0.315

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To further analyze the significance of different noise intensities on NASA-TLX scale scores, we use noise intensity as independent variable and NASA-TLX scale as dependent variable for variance analysis. Tables 3 and 4 show the NASA-TLX ANOVA results and LSD multiple comparison test results.

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As can be seen from Fig. 1, the mean value of NASA-TLX scale scores increases with the increase of noise intensity, but its increase rate decreases as the noise intensity increases, indicating that subjects’ mental workload increases with noise intensity Increased, but the degree of mental workload increased as the noise intensity increased. Analysis of variance in Table 3 (F = 13.626, P < 0.05) show that noise has a significant effect on subjects’ mental workload. The results of LSD multiple comparison tests in Table 4 show that there is a significant difference between the control group and the noise group in mental workload, P < 0.05. This indicates that noise affects subjects’ mental workload, and subjects’ mental workload increases with the increase of noise intensity. When noise reaches a certain level, it has no significant effect on subjects’ mental workload.

3.2

Error Rate

The mean error rates which completed the task under different noise intensities were statistically analyzed. The mean error rate as a function of noise intensity is shown in Fig. 2. In order to further analyze the significance of different noise intensity on error rate, the noise intensity as independent variable and the error rate as dependent variable were analyzed by ANOVA. Tables 5 and 6 shows ANOVA result of error rate and LSD multiple comparison results. As can be seen from Fig. 2, the error rate in control group is lower than the noise group, and error rate increases with increase of noise intensity. The results of variance in Table 5 (F = 35.170, P < 0.05) show that noise has a significant effect on error rate in completing the task.

Fig. 2 Error rate of experimental tasks under different noise intensities

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Mean difference

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−2.63978 −6.14500 −7.66022 2.63978 −3.50522 −5.02044 6.14500 3.50522 −1.51522

0.003* 0.000* 0.000* 0.003* 0.000* 0.000* 0.000* 0.000* 0.075

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4 Discussion Armored vehicle cabin interior noise intensity is high, generally between 85 and 115 dB(A). The variance of the noise intensity with operating conditions is quite different. The noise components are similar and mainly of low frequency. The noise intensity of armored vehicles in high speed is higher than that in launch session [5]. Compared with control group, error rate increased significantly under experimental conditions, and the mean value of NASA-TLX scale increased with the increase of noise intensity trend. The impact of noise makes crew’s information judgment and operation speed lower, and mental workload increases, resulting in an increase in error rate of crew to complete task and the reduction of the operational performance. The experimental results are consistent with Saeki’s research [6].

5 Conclusion Based on typical tasks of armored vehicles, subjective evaluation, and task error rate are used as indexes to study the impact of noise on crew’s mental workload. The noise has a certain impact on crew’s mental workload, and the mental workload of crews increases with the increase of noise intensity. When noise

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reaches a certain level, it has no significant effect on crew’s mental workload. Therefore, to complete information operations more effective, we must pay attention to noise protection measures to reduce crew’s mental workload. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of AAAF. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Jiao D (2002) Maximum allowed value of environmental noise. J Railway Energy Sav 29 (5):1003–1197 2. Sandrock S, Schütte M, Griefahn B (2010) Mental strain and annoyance during cognitive performance in different traffic noise conditions. J Ergon 53(8):962–971 3. Han L, Wu X, Li X et al. (1999) Effect of noise on human mental performance. J Space Med Med Eng 12(1):28 4. Liu W, Fu B, Liu X et al (2015) Experimental study of influences of input modes of vehicle-mounted display and control terminal on crew’s information processing capability. J Acta Armamentarii 36(11):1000–1093 5. Yang B, Liu W, Jin Y et al. (2017) Noise test and evaluation of armored vehicle cabin. J Acad 143 Armored Force Eng 31(4):52–55 6. Saeki T, Fuji T, Yamaguchi S et al (2004) Effects of acoustical noise on annoyance, performance and fatigue during mental memory task. J Appl Acoust 65(1):913–921

Study About the Effects of Noise on Crew’s Thinking Ability Kaixuan Zhao, Weiping Liu, Binhe Fu and Bo Yang

Abstract In order to study the effects of noise on the thinking performance of armored vehicle crews, the typical information processing task test is conducted based on the performance indicators of correctness and reaction time. The experimental results show that during the 60-min exposure under noisy condition, the accuracy rate of the subjects did not change significantly compared with the control group, while the reaction time performance and comprehensive performance decreased significantly. The comprehensive performance of subjects decreased with the increase of noise intensity, but the decrease was reduced with the increase of noise intensity. To sum up, noise has a certain impact on crew’s thinking performance, and crew’s performance decreases with the increase of noise intensity. When noise reaches a certain level, it has no significant effect on crew’s performance, indicating that noise has an impact on crew’s thinking ability. Keywords Noise

 Armored vehicle  Thinking  Operation performance

1 Introduction Thinking ability is crucial in the process of crew’s information operation. It may be affected by operation environment, especially in noise environment. Therefore, it is of great practical significance to study the influence of noise on crew’s thinking ability. Research shows that noise has a certain impact on individual’s thinking ability and memory functions. Gulian found that the speed of mental arithmetic task was significantly reduced, and the accuracy was not significantly affected after exposure to 20 min in the white noise of 80 dB(A) [1]. Hu showed that 85 dB(A) noise had a significant negative effect on mental arithmetic performance [2]. However, Belojević found that 75 dB(A) noise had no significant effect on the subjects’ K. Zhao (&)  W. Liu  B. Fu  B. Yang Academy of Army Armored Forces, Beijing 100072, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_46

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mental tasks [3]. The above studies focus on the impact of noise on performance but have not studied the impact of armored vehicle noise on crew’s thinking ability. Therefore, this study focuses on improving crew’s performance for the purpose of studying the impact of noise on the thinking ability of crews, providing human effective data for relevant protective measure and ergonomic standards.

2 Method 2.1

Participants

A total of 24 military cadets who volunteered to participate in the experiment were selected, aged 20–25 years old, male, healthy, all the subjects (corrected visual acuity), and normal hearing, all right-handed, and familiar with the information terminal operation experiment.

2.2

Experiment Equipment

The experimental instrument is a simulation test platform for vehicle information terminal operations. The system software is based on the independent development of LabVIEW programming language to simulate the functions of information collection, processing, display and distribution of armored vehicles in the battlefield [4]. It can control task presentation time and measure correct rate, task completion time, and so on. In the experiment, the measurement of noise is selected by BSWA806 portable I precision sound level meter, its precision is 0.4 dB, and the test range is 18–140 dB(A).

2.3

Experiment Design

The experiment adopts the design of the subjects. The independent variable is the noise intensity. The dependent variable is the performance index of the thinking operation, mainly including the correct rate and reaction time. Character rotation test: Two identical characters are displayed on the experimental platform screen. Subjects observe by observation whether the two characters are positive (coincidence only by rotation) or vice versa (mirror and rotation coincide). Subjects need to make the right choices and press the key to ensure the correct premise.

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Thinking depth test: The screen presents ten numbers at a time. The last two numbers of the numbers are empty. The subjects are required to find the inherent laws of the numbers and fill in the empty numbers to record the response time and the correct rate.

2.4

Experiment Steps

(1) Before formal experiment, the participants should be trained first to ensure that the subjects can achieve the required proficiency in the experimental task and understand the instruction correctly. The participants should focus on the experimental procedures and requirements. (2) Subjects completed the experimental tasks in the quiet environment and the noise intensity of 85, 90, and 95 dB(A) cabin, respectively. Each exposure time was 60 min, and the order of three intensity exposure was random, and the quiet environment was used as a control group. (3) In order to eliminate the effect of fatigue, it is carried out alternately. The experimental system automatically records the performance data. If the task does not complete the task within the specified time, the single experiment task will be stopped automatically. (4) After completing the experiment of one noise intensity level, after the subjects rest for 2 min, change the factor level and repeat the above experimental procedure.

2.5

Data Statistics Method

The data by SPSS software with the average and standard deviation ðx  sÞ expressed is to determine the differences by analysis of variance.

3 Results 3.1

Effect of Noise on Crew’s Mental Rotation Ability

The subjects are tested for 60 minutes' psychological rotation ability under different noise conditions. The results are shown in Table 1 and Fig. 1. As can be seen from Table 1, under different intensity noise conditions, the correct performance of the subjects did not change significantly compared with the control, and the response performance and comprehensive performance are significantly reduced (P < 0.05). As can be seen from Fig. 1, the comprehensive performance of subjects decreases with the increase of noise intensity, but the decrease trend decreases with the increase of noise intensity.

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Table 1 Effect of noise on psychological rotational ability experimental results Noise intensity [dB(A)]

Correct rate (%)

30

90.22 ± 10.33

85

86.64 ± 11.59

Correct rate performance 100 96.03 ± 11.53

Average reaction time (s) 2.23 ± 0.69 2.57 ± 0.83*

Reaction time performance 100 84.76 ± 26.6*

Comprehensive performance 100 81.39 ± 29.99*

90

86.96 ± 12.30

96.39 ± 12.23

2.87 ± 0.82*

71.30 ± 26.29*

68.72 ± 28.99*

95

86.15 ± 13.03

95.49 ± 12.96

2.92 ± 0.85*

69.06 ± 27.24*

65.94 ± 30.17*

*P < 0.05 compared to the control group

Fig. 1 Effect of noise on psychological rotational ability experimental results

3.2

Effect of Noise on the Depth of Crew’s Thinking

The test results of the subjects exposed to 60 min under different noise conditions are shown in Table 2 and Fig. 2. From Table 2, we can see that under the different intensity of noise, the accuracy rate of subjects has no significant change compared with the control, while the response time performance and comprehensive performance are significantly reduced (P < 0.05). As shown in Fig. 2, the comprehensive performance of subjects decreases with the increase of noise intensity, but the decrease trend decreases with the increase of noise intensity.

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Table 2 Effect of noise on the depth of thinking Noise intensity [dB(A)]

Correct rate (%)

30

87.33 ± 13.37

85

85.68 ± 10.56

Correct rate performance 100 98.11 ± 10.48

Average reaction time (s) 3.81 ± 0.93 4.82 ± 1.13*

Reaction time performance 100 73.49 ± 23.84*

Comprehensive performance 100 72.10 ± 26.04*

90

84.96 ± 10.89

97.28 ± 10.81

5.02 ± 1.15*

68.24 ± 24.26*

66.38 ± 26.56*

95

85.55 ± 9.89

98.96 ± 9.82

5.14 ± 1.04*

65.09 ± 21.94*

63.76 ± 24.04*

*P < 0.05 compared to the control group

Fig. 2 Effect of noise on the depth of thinking

4 Discussion Armored vehicle cabin interior noise intensity is high, generally between 85 and 115 dB(A). The variance of the noise intensity with operating conditions is quite different. The noise components are similar and mainly of low frequency. The noise intensity of armored vehicles in high speed is higher than that in launch session [5]. During this experiment, noise exposure to 60 min, compared with the control group, the average reaction character rotation and thinking depth test was prolonged, comprehensive performance decreased significantly, which indicates that noise has a certain negative effect on the mental rotation ability and deep thinking reasoning ability of subjects. Correct rate performance indicates the accuracy of the test when the task is completed, and the response performance reflects the speed of the task being completed. In the two test tasks, under the different noise environment, the accuracy

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rate of subjects does not change significantly compared with the control, while reaction time performance and comprehensive performance are significantly reduced. This is due to the increase in the average reaction time of subjects to ensure the accuracy of task, which leads to a significant reduction in reaction time performance and comprehensive performance. With the increase of noise intensity, the decrease of task performance decreases, which may be the adaptation of subjects to noise exposure, and the negative effects of noise on the subjects are reduced. Therefore, noise has a certain influence on the performance of thinking, which indicates that noise has a certain influence on the thinking ability of crews’ information operation.

5 Conclusion Based on typical tasks of armored vehicles, the experiments are carried out on the basis of correctness and reaction time to explore the impact of noise on crew’s thinking ability. Noise has a certain effect on the performance of crew’s thinking operation, and the performance of crew decreases with the increase of noise intensity. When the noise reaches a certain level, it has no significant influence on crew’s performance. This indicates that noise has a certain influence on the thinking ability of crew’s information operation. Therefore, when crew completes information operation, we should pay attention to noise protection measures to reduce the influence of noise on crew’s thinking ability. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of AAAF. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Gulian E, Thomas JR (1986) The effects of noise cognitive set and gender on mental arithmetic performance. J Brit J Psychol 77(4):503–511 2. Hu Z, Liang Z, Shi X et al (1997) Effect of noise submarine compartment on signal discrimination and arithmetic performance. J Space Med Med Eng 10(3):214–216 3. Belojević G, Öhrström E, Rylander R (1992) Effects of noise on mental performance with regard to subjective noise sensitivity. J Int Arch Occup Environ Health 64(4):293–301

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4. Liu W, Fu B, Liu X et al (2015) Experimental study of influences of input modes of vehicle-mounted display and control terminal on crew’s information processing capability. J Acta Armamentarii 36(11):1000–1093 5. Yang B, Liu W, Jin Y et al (2017) Noise test and evaluation of armored vehicle cabin. J Acad 143 Armored Force Eng 31(4):52–55

Research on Protective Performance of Basketball Knee Pads Based on 3D Motion Capture Yuxiu Yan, Quan Wang, Zimin Jin and Jianwei Tao

Abstract This subject uses a three-dimensional dynamic capture system to catch two movements of the jump shot and the rebounds in the basketball game, using surface electromyography as an auxiliary tool to explore the effect of knee-free group and knee protection group on knee flexion angle, and analyze the causes of different results. The final draw for the professional basketball kneecap style and organizational structure. So as to provide a reference for the development of professional basketball kneecap. The results show that three kneecaps in both movements have a protective effect. Among them, the mean maximal flexion angle of pressurized and breathable open hole kneecap was the smallest, and the protective performance was the best. A sudden stop and turn around will make a strong twist of the knee joint to cause damage.







Keywords Knee protection Kinematics Basketball Surface electromyography Correlation

1 Introduction Obvious characteristics of modern basketball are intense. At any time, knee flexion is needed to reduce the gravity of athletes, especially to do vertical jump, sudden stop and turn, and other movements which will make the knee bear a great impact [1]. The vertical jump will make the foot hit with the ground violently, but the impact can be buffered to the knee through the foot. At present, a survey of more than ten college basketball players in Jiangsu shows that knee injury is more common in athletes; about 88.75% of basketball players have suffered different degrees of knee injury [2]. So, wearing knee pads during normal basketball games will play a certain role in the movement of the knee joint [3, 4], thus preventing the knee joint damage or reducing the degree of knee injury. Currently, there are no Y. Yan (&)  Q. Wang  Z. Jin  J. Tao Zhejiang Sci-Tech University, Hangzhou, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_47

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professional basketball knee pads. This research takes basketball knee protection performance as the object and studies whether the knee pad can effectively reduce the knee joint activity in the stop jump shot and the rebounds in the basketball game to determine the knee protection performance [5].

2 Methods 2.1

Participants and Knee Pads Information

Five athletes were recruited from basketball teams of five universities in Hangzhou for this study [mean (SD) age, 22 (3) years; height 1.75 m; weight 70 kg]. All participants were healthy and had no history of lower extremity injuries such as knee joint and ankle joint within one month prior to the test and were able to skilfully complete various movements in basketball. Through the market research and literature reading to determine three different knee pads, the parameters shown in Table 1 and Fig. 1.

Table 1 Knee pads information Kneecap type

Material

Standard sizes

Elastic knee pads

35% rubber; 55% nylon; 10% spandex 35% rubber; 50% nylon; 15% spandex 65% rubber; 5% nylon

25 cm  38 cm

Bandage knee pads Pressure ventilation breathable knee pads

Fig. 1 From left to right are elastic knee pads, bandages and pressure ventilation breathable knee pads

19 cm  45 cm  76 cm  79 cm 7.6 cm  121.9 cm

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Experimental Procedures and Measurement

The measurement parameter of the test is the maximum flexion angle of the knee joint [6]. The motion parameters of main reaction knee crown makeup. The principle of this experiment is that the ground reaction force is carried upward along the foot to the leg and knee joint at the moment of landing, body through the muscle contraction and joint flexion to buffer. The prevention of knee injury is to prevent the activity of the knee to exceed the range of activity and then reducethe knee impact on the energy buffer, thereby reducing the impact on the knee to protect the knee. The main function of the kneecap is to give a certain fixation and support to the knee. Without affecting the effect of movement, to study whether the kneecap can effectively reduce the range of motion of the knee determines the protective performance of the kneecap. The experiment is divided into two groups according to the action. The subjects were wearing tight pants, and the reflective sticker marks on the pant. As shown in Fig. 2 and Table 2. After collecting static data for 30 s twice, the dynamic points are reduced by 10 points on the basis of the static points. Because these ten points are symmetrical in the lower limbs, so there are five points on each side. The stop jump shot group data is collected for eight seconds and grab rebounds for six seconds. Each of the participants was randomly selected to wear knee pads in order to avoid the

Fig. 2 Bone point bitmap

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Table 2 Skeleton point name Name

Location

L-IAS L-IPS L-FTC L-TH1-4 L-FLE L-FME L-SK1-4 L-FAL L-TAM L-FCC L-FM5 L-FM2 L-FM1

Left anterior superior iliac spine Left posterior superior iliac spine Most lateral prominence of the greater calcaneus Cluster Left lateral epicondyle Left medial epicondyle Cluster Lateral prominence of the left lateral malleolus Medial prominence of the left medial malleolus Aspect of the Achilles tendon on the left calcaneus Dorsal margin of the fifth metatarsal head Dorsal aspect of the second metatarsal head Dorsal margin of the first metatarsal head

experimental error caused by muscle fatigue. Three valid data were collected for each knee pad under each test. In the data acquisition, the EMG signal was observed in the EMG works Acquisition software and compared with the EMG signal of the last test to see if the difference was obvious. If obvious, then re-test. When the Qualisys Motion Capture System confirms that all Marker points have not dropped during the test, and the EMG signal is not significantly abnormal, start the next test.

3 Results and Discussion 3.1

Analysis of Test Results of the Stop Jump Shot Group

The change of the flexion angle of the knee in the right leg during the stop jump shot test is shown in Fig. 3. The first peak is the maximum knee flexion angle at takeoff. The second peak is the maximum knee flexion angle during airborne motion. The last peak is the maximum knee flexion angle at the ground. It can be seen from the figure that the maximum flexion angle of the knee without knee protection is significantly larger than that of the other three knee flexions. The effect of pressure ventilation breathable knee pads is significantly greater than the bandages and flexible knee pads. SPSS software was used to make one-way analysis of variance of maximum knee flexion angle under different states of stop jump shot. The results of the analysis are shown in Table 3. Multiple comparisons between knee pads showed that there was a significant difference in elastic knee pads, bandages and pressurized breathable knee pads relative to the blank group (Elastic knee pads sig = 0.014 < 0.05, Bandage sig = 0.035 < 0.05, Pressure ventilation

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Fig. 3 Stop jump shot action angle dynamic changes

Table 3 Stop jump shot action significant results (I) Type of knee pads

(J) Type of knee pads

No kneecap

Pressure ventilation breathable knee pads Bandages Elastic knee pads **p < 0.01; *p < 0.05

Mean difference (I − J)

Standard error

Sig.

95% Confidence interval Lower Upper limit limit

6.3600*

2.05631

0.004

2.1714

10.5486

4.5278* 5.3267*

2.05631 2.05631

0.035 0.014

0.3392 1.1381

8.7163 9.5152

Table 4 Analysis result of the maximum buckling angle of the stop jump shot Type of knee pads

#1

#2

#3

#4

#5

Pressure ventilation breathable knee pads Bandages Elastic knee pads No kneecap

98.10 98.98 99.04 102.23

89.05 87.93 91.93 92.11

93.27 97.45 90.06 97.48

87.54 89.31 86.45 97.76

85.20 87.83 90.35 93.93

breathable knee pads sig = 0.004 < 0.05). Elastic knee pads, bandages and pressure ventilation breathable knee pads all have protective effect. The mean maximum knee flexion angle for each participant wearing different knee pads is calculated. The results are shown in Table 4. Conclusion: In the stop jump shot operation, the pressurized ventilation-type knee pads, elastic knee pads and bandages all have the protective effect, and the protective effect of the pressurized ventilation-type perforated knee pads is superior to the elastic knee pads; there is not much difference between the elastic knee pads effect and the bandage protective effect.

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Analysis of Test Results of Rebounding

The maximum flexion angle of the knee of the right leg in the competition for rebounding action over time is shown in Fig. 4. The first peak is the maximum knee flexion angle at takeoff. The second peak is the maximum knee flexion angle at the ground. It can be seen from the figure that the maximum flexion angle of the knee without knee protection is significantly larger than that of the other three knee flexions. Among them, the pressure ventilation breathable knee pads flexion angle is the smallest. SPSS software was used to make one-way analysis of variance of maximum knee flexion angle under different states of rebounding. The results of the analysis are shown in Table 5. Multiple comparisons between knee pads showed that there was a significant difference in elastic knee pads, bandages and pressurized breathable knee pads relative to the blank group (Elastic knee pads sig = 0.043 < 0.05, Bandage sig = 0.034 < 0.05, Pressure ventilation breathable knee pads sig = 0.001 < 0.05). Elastic knee pads, bandages and pressure ventilation breathable knee pads all have protective effect. The mean maximum knee flexion angle for each participant wearing different knee pads is calculated. The results are shown in Table 6. Conclusion: In the

Fig. 4 Rebounding action angle dynamic changes

Table 5 Rebounding action significant results (I) Type of knee pads

No knee pad

(J) Type of knee pads

Pressure ventilation breathable knee pads Bandages Elastic knee pads **p < 0.01; *p < 0.05

Mean difference (I − J)

Standard error

Sig.

95% Confidence interval Lower Upper limit limit

5.3375*

1.56166

0.001

2.1902

8.4848

3.4075* 3.2542*

1.56166 1.56166

0.034 0.043

0.2602 0.1069

6.5548 6.4015

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Table 6 Analysis result of the maximum buckling angle of the rebounding Type of knee pads

#1

#2

#3

#4

#5

Pressure ventilation breathable knee pads Bandages Elastic knee pads No kneecap

90.92 94.18 92.92 99.94

81.63 83.18 84.05 90.59

81.65 83.56 84.72 85.00

80.19 81.28 83.10 85.50

82.81 85.26 83.06 85.30

Table 7 Subjective comfort evaluation of knee pads Grade

Elastic knee pads

Bandages

Pressure ventilation breathable knee pads

1 2 3 4 5

75 83.33 28.57 0 0

25 16.67 57.14 44.44 0

0 0 14.29 55.56 100

fight rebounding action, the pressurized ventilation-type knee pads, elastic knee pads and bandages all have the protective effect, and the protective effect of the pressurized ventilation-type perforated knee pads is superior to the other two knee pads; there is not much difference between the elastic knee pads effect and the bandage protective effect. This article evaluates the subjective comfort of three protective knee pads for testing. In addition to the five basketball enthusiasts tested, five other basketball enthusiasts were selected to wear kneecaps. They did 10 consecutive squats and made subjective comfort evaluation. Subjective comfort was assessed by five grades: grade 1 (It’s very comfortable), grade 2 (It’s comfortable), grade 3 (It’s senseless), grade 4 (It’s slightly uncomfortable), grade 5 (It’s uncomfortable). According to subjective comfort questionnaire survey results obtained from pressure ventilation breathable knee pads, elastic knee pads, bandages, three subjective comfort ratings are shown in Table 7. The table shows that the elastic knee pads are slightly better than the bandages, which are far superior to pressure ventilation breathable knee pads.

4 Conclusions In the stop jump shot action and rebounding action, the three knee pads all have the protective effect to reduce the maximum flexion angle, and the protective effect of the pressure ventilation breathable knee pads is superior to the other two knee pads. In the subjective comfort evaluation, the comfort of the elastic knee pad is higher

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than the bandages, and the comfort of the pressure ventilation breathable knee pad is the worst. The research finding of this paper could be taken as a reference for development of professional basketball knee pads. Acknowledgements The project is supported by New Products In Zhejiang (2016D60SA732873, 2017D60SA731795). Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of School of Fashion, Zhejiang Sci-Tech University, Hangzhou, China. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Xing C (2013) Study on the changes of electromyography and knee joint injury in the application of technical movements of college basketball students. Beijing Sport University (S1) 2. Xu X (2010) Research on the current situation and countermeasures of knee joint injury of high level basketball players in Jiangsu Province. Suzhou University, pp 1–47 3. Zhang L, Song Z (2014) Basketball technique EMG and joint angle characteristics of lower extremity movements. Chin J Sports Med 33(7):658–663 4. Zhu H, Sun Y (2004) Analysis of knee injury in 35 college basketball players. J Jinzhou Med Coll 25(1):39–40 5. Wang S, Xie H, Cao R (2014) Research on protective clothing based on sports biomechanics. China Text Lead 1:91–93 6. Zhao R, Wang Y (2015) Protective effect of knee protection during walking and jogging. Text Res J 36(6):106–111

Study on 5-km Armed Cross-Country Training in the Plateau Hypoxic Environment Shuai Mu, Ming Kong, Huifang Wang and Hai Chang

Abstract It is a practical issue to carry out operational missions in extreme circumstances that military personnel must face. The high-altitude hypoxic environment will affect the respiratory center of participants, and high-intensity training in extreme environments makes the participants’ body become more fatigue and recover more slowly. The incidence of sports injuries will increase significantly. Therefore, it is worthwhile to study how to carry out 5-km armed cross-country training safer, more scientifically, and more effectively under the plateau hypoxic environment. The 5-km armed cross-country training of military personnel in the hypoxic environment of plateau is explored from the perspective of functional assessment and exercise physiology. The impact of 5-km armed cross-country training under the hypoxic environment of plateau will be analyzed in order to put forward suggestions. Keywords Plateau hypoxic environment Impact Suggestions



 5-km armed cross-country

Plateau training has originated in the 1950s. At present, many countries in the world send participants to plateau training and benefit from it. However, when conducting strenuous exercise in the extreme environment that is high altitude, hypoxia, and high temperature difference in the plateau area, the metabolic status is quite different from that in the oxygen-rich areas of the inland, which will directly result in increased sports injuries. The basic mode of 5-km armed cross-country training in the plateau hypoxic environment will be explored through qualitative and quantitative analysis.

S. Mu (&)  M. Kong  H. Wang  H. Chang Zhengzhou Campus, CPLA Army Artillery and Air Defence Forces Academy, Zhengzhou 450052, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_48

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1 Characteristics of Plateau Environment and Its Influence on Sports Performance 1.1

Characteristics of Natural Environment

The general characteristics of the natural environment of the plateau are low pressure, low oxygen, low humidity, strong wind and sand, long sunshine duration, big temperature difference between day and night, big temperature difference between sun and shade, high solar radiation, ultraviolet radiation, and cosmic radiation. As altitude increases, atmospheric pressure and partial pressure of oxygen will gradually decrease. The most appropriate altitude for plateau training is about 2000 m, which is widely accepted [1].

1.2

Influence of Plateau Natural Environment on Sports Performance

In the plateau environment, the changes of gravity, air resistance, and oxygen partial pressure can all affect the sports performance. For the speed programs, hypoxia almost has no effect on the performance, and only the recovery interval needs to be extended properly. Moreover, the reduction of the air resistance in the plateau is favorable for the improvement of speed program achievements. For endurance programs, when the duration of exercise is over 1 min, the adverse effects of hypoxia may exceed the beneficial effects of reduced gravity and air resistance, which will lead to decreased performance. There are no significant effects on the strength programs [2].

2 Influence of Plateau Training on the Participants 2.1 2.1.1

Analysis of Favorable Factors Favorable for the Participants to Enhance the Aerobic Metabolism

Aerobic metabolism is the basis of endurance exercise, and especially in the 5-km armed cross-country running, participants need to mobilize a lot of aerobic metabolic enzymes and myoglobin. During the training in the plateau hypoxic environment, participants first have to go through a period of hypoxia. Under this condition, participants can make better changes to aerobic metabolic enzymes and myoglobin through training. For example, the level of citrate synthase, b-hydroxyacetyl COA dehydrogenase, lactate dehydrogenase, and myoglobin,

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which is critical for the medium- and long-distance training, will increase faster than that in the plain training. In addition, plateau training can greatly promote blood-related indicators, such as blood cells and hemoglobin. Due to the special environment of plateau hypoxia, erythrocyte deformability and hemorheology will also be improved, which is favorable for the delivery of oxygen and the improvement of the energy supply to the heart [3].

2.1.2

Favorable for the Participants to Improve Exercise Ability

Training under hypoxic conditions can make the body produce stimulus-induced response, which will make the muscles generate more oxygen-carrying red blood cells. When returning to the plain after plateau training, the level of red blood cells of the participants remains high, and aerobic work ability is also enhanced. As there is more oxygen to the muscles on the plains, the participants maintain their aerobic capacity to a greater extent during the same training on the plain. Therefore, for the 5-km armed cross-country running, as long as the training intensity and methods meet the personal differences of participants, the sports ability will be improved better on the plateau than on the plain.

2.2 2.2.1

Analysis of Adverse Factors Excessive Training Intensity Will Affect the Participants’ Respiratory System

Participants can better improve their maximum oxygen uptake in plateau training, but this ability needs to be built upon the proper intensity of exercise. If the exercise is too intensive, it will render excessive pressure on the lungs, causing too frequent ventilation, which will make the participants emit too much carbon dioxide, thereby reducing the partial pressure of carbon dioxide in the blood. If this situation develops over a long period of time, the PH in the blood and spinal cord will increase, resulting in an excess of alkalinity. The participants will be prone to respiratory alkalosis in such conditions and will also get potential physical damage [4].

2.2.2

Too Frequent Trips Will Hurt the Participants’ Body

The human body needs adaptive time to convert between the plain and the plateau. Participants that live on the plain have to go through two times of external environment conversion, from the plain to the plateau and then from the plateau to the plain. Because of the influence of the external environment, the internal environment, such as the blood acid–base balance, will make changes to adapt to the

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external environment again. Theoretically, it will affect the normal operation of the nervous system, which will take some time to return to the normal fit state. If this conversion occurs too frequently, the participants’ body will get hurt.

2.2.3

High-Intensity Plateau Training Will Cause Physical Fatigue of Participants

It is hard for the participants to control the training intensity under the condition of thin air and low oxygen partial pressure, which will make the participants get fatigue easily. Besides, once the participants feel fatigue, recovery of the body will become very slow. With long-term training in this state, participants will catch fatigue symptoms and become vulnerable to injury [5].

3 Suggestions for the 5-km Armed Cross-Country Training on the Plateau 3.1

Divide Training Stages Scientifically

Plateau training includes three stages, namely the training stage of great amount of plain exercise, the stage of intensive plateau training, and the stage of intensive plain training. The training intensity of the plateau intensive training stage is determined by the training quality of the great amount of plain training. The effect of intensive training back on the plain is determined by the quality of the plateau intensive training. Plain intensive training is a continuation of the plateau intensive training stage. The duration of great amount of exercise on the plains should be relatively long, up to about 45 days, so that the basis of the body to withstand exercise load will be more abundant. The stage of plateau training should concentrate on the strength to emphasize the competition intensity, arousing the maximum speed potential of the participants. The intensity of the plain training should be slightly higher than that of the plateau training. The standard of the plain training course should be above the outline requirements. In addition to following the general rules of plateau training arrangements, the most important point is that the arrangements of the overall load should be gradually approaching or reaching the level on the plain. During the implementation process, the volume and intensity should be coordinated well in order to make the load arrangement stable, gradual, and sustainable, in case of excessive partial load and lack of overall stimulus.

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Formulate the Training Programs Seriously

The programs of segmented different-distance running should be developed seriously. The segmented different-distance running has its training purposes, but the different impact of the plateau environment on the performance of different-distance running should be considered. Yatimov, a Russian plateau training expert, summarized conscientiously the plateau training practice in Russia and formulated the training principles for different-distance running during the stage of intensity training. This program has at least the following three characteristics: First, in the new program, the speed of the segmented medium-distance running is obviously slower than that of the traditional program. The speed of rhythm running, long-distance cross-country running and other running of longer duration, is above 5 min/km. Second, in the 100–800 m training segment, the running speed is much faster than that of the traditional training program. Third, the intervals between each group and each segment are longer than those of the traditional training programs.

3.3

Carry Out the Adaptive Training Actively

Armed cross-country is a long-distance and cyclical endurance program. Endurance quality, especially aerobic endurance, is particularly important for the program. To carry out adaptive training with appropriate measures and means before plateau training can speed up adaptation and promote the plateau acclimatization, so as to improve the quality of plateau training and to make the training effect meet or exceed the expectation. Trapezoidal plateau training is in such a form, which refers to conduct training at different plateau area in a gradient way. For example, the training is first at a zone of 1400 m above sea level and then at the altitudes of 1600, 1800, 2000, and 2200 m successively. Trapezoidal pre-anaerobic adaptive training is to allow the body to adapt to different altitudes through adaptive training, with the purpose of obtaining stronger hypoxic endurance. Physical exercise under the condition of intermittent anoxia can promote the adaptation of the body to hypoxia and enhance the body’s ability of uptake and utilizing of oxygen. The body’s physiological response to hypoxia, the function of the respiratory system, and the blood’s oxygen delivering capacity as well as the metabolism of skeletal muscle will be improved. Hypoxic respirator can also be used to assist in the training.

3.4

Organize the Training Organically and Flexibly

From the plain to the plateau, the human body needs a gradual adaptation process. Plateau training should be divided into three stages: preparation period, plateau

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reaction period, and plateau adaptation period. Adaptation period can be further divided into pre-adaptation period and late adaptation period.

3.4.1

Preparation Period

The preparation period should be the 7–10 days before the time of going to the plateau. During this period, relevant data tests will be carried out for the participants, such as the physiological index tests when the participants are quiet, the tests of lactic acid speed curve at the exercise site, muscle strength, vital capacity, maximum oxygen uptake, heart rate, hemoglobin, PH value. These data will be used to compare the value changes after plateau training, in order to analyze and study the effect of plateau training and to establish the relevant database of plateau training. Training of this stage will be concentrated on endurance training in general, with almost no requirements for intensity.

3.4.2

Reaction Period of Plateau Training

In the “acclimatization” process, participants will have maladjustment symptoms to varying degrees, such as quick fatigue, slow recovery, oxygen deficiency during exercise. Therefore, collective running with a lower load (5–7 days) will be adopted during the training of this stage. In case of the danger of overloading, which is inclined to occur during the first few days after arriving at the plateau, the load of running in the first four days is low, but the times of training will be increased, with three times relaxed running each day. In order to maintain the appropriate requirements, each class will last 60–90 min. The training load will be monitored by checking the pulse. For example, the heart rate during the running training of the first five days should not exceed 140 times/min, and from the fifth day, Fartlek running will be added, with the pulse at 150 times/min or so.

3.4.3

Adaptation Period

The adaptation period starts from the second week on the plateau. Participants begin to adapt to the plateau environment somewhat. The amount of exercise can be close to the original level, but the intensity should be strictly controlled. The training gradually approaches the medium load. Training should be conducted with more times of class and a small amount of exercise. The training purpose during the time (from the fourteenth to the sixteenth day after arriving at the plateau) is to synchronize the heart respiratory system and neuromuscular system. The load will be increased gradually. After the seventh day, the training amount will be the same as on the plain, but less intense. Training courses are mainly conducted in the field, rarely in the athletic field, because it is difficult to control the training speed with time indicators, while the heart rate indicator will mainly be used for supervision.

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The normal training stage begins at the late adaptation period (after the fourteenth– sixteenth day). During this stage, participants have been fully adapted to the plateau hypoxia. Hemoglobin is not only restored but even higher than that on the plain. Blood lactic acid is not too high, either. There is no difference between training amount and intensity of this stage and that of the plain areas. In the plateau training, most of the training amount for participants is aerobic training and aerobic–anaerobic training, mainly long-distance running, Fartlek running, and long-distance variable speed running. Participants cannot adapt, resulting in no effects. The data shows that in the plateau training, control and arrangements of intensity can follow several principles: First, according to their own training level of participants, those at higher training level can afford higher intensity, and lower training level, lower intensity. Second, arrange some training that is close to the intensity of the competition for the competition goal. Third, the intensity of training before and after going to the plateau should be linked up. Before going to the plateau, there should be adequate aerobic endurance training. The plain training after coming back from the plateau should be more intense than that on the plateau. Fourth, arrange according to the body’s adaptation to the plateau environment.

References 1. Chen Y (2007) Influence of altiplano alternate training on athletes’ body function and athletics ability. Journal of Nanjing Institute of Physical Education, Nanjing 2. Dniel J, Oldrdge N. The effect of alternate exposure to altitude and sea level on world-class middle distance runner. Med Sci Sports Exerc 107–112 3. Wasserman K, Mcieroy MB (1964) Detecting the threshold of anaerobic metabolism in cardiac patients during exercise. Am J Cardial 14:844–852 4. Zhao G, Han Z (2008) Extensive training issues in altitude training. J Shandong Inst Phys Educ Sports (Feb):73–75 5. Wilber RL (2001) Current trends in altitude training. Spots Med (Apr):249–650

The Influence of Short-Time Head-Down Tilt Simulated Weightlessness on Performance of Motion Direction Judgment Duming Wang, Qipei Han and Yu Tian

Abstract Objective To explore the influence of short-time head-down tilt simulated weightlessness on the performance of motion direction judgment. Methods Eighty subjects were randomly divided into two groups. Two groups were required to judge the motion direction under the conditions of natural gravity and short-time head-down tilt simulated weightlessness, respectively. Results The main effect of motion directions is significant. The performance of judging the upward, downward, rightward, and leftward motion is different. The interactive effect between gravity conditions and motion directions is significant. Angular deviation of judging the upward motion is significantly larger under simulated weightlessness condition compared to natural gravity condition. Conclusion There is a difference in judging different motion directions. Different gravity conditions only influence specific motion direction, and perceptive deviation of the upward motion is larger under simulated weightlessness condition. Keywords Gravity

 Weightlessness  Head-down tilt  Direction of motion

1 Introduction The normal play of the astronauts’ ability is the key factor for successful completion of manned space missions. But the microgravity environment can cause changes of vestibular function and visual function, thus leading to the change of sensorimotor information, which has obvious influence on cognition function [1–5].

D. Wang (&)  Q. Han Department of Psychology, Zhejiang Sci-Tech University, No. 928, 2 Street, Hangzhou 310018, Zhejiang Province, People’s Republic of China e-mail: [email protected] Y. Tian National Key Laboratory of Human Factors Engineering, Astronaut Center of China, Haidian District, Beijing 100094, People’s Republic of China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_49

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The study found that the astronaut’s perception pattern on moving objects changed in the microgravity environment [6]. The judgment of the moving object includes both the motion speed judgment and the motion direction judgment; both have important influence on collision prediction and avoidance, grasping and capturing of moving object, interactive docking task operation, etc. For the perception of the motion speed, it has been found in study that the perception of speed is influenced by the gravity conditions, for example, Senot has found, under normal gravity condition, the trigger time for the interception behavior of moving objects from up to down is earlier than that from down to up, on the contrary under the condition of weightlessness [7]; Wang, Tian, etc., have found that the individual’s speed perception deviation in the vertical direction was larger than the horizontal direction in the horizontal flight experiment and the normal sitting experiment. In aircraft weightlessness flight experiments and head-down tilt experiments, the direction effect has a tendency to fade [8]. In the aspect of motion direction judgment, the researchers have found that it was related between the stimulation perception and the orientation of stimulation at a very early time, and the study has also shown that the neurons reacted differently to different motion directions [9– 11]. When researching the memory of motion direction, Blake et al. have found that there was systematic difference in the accuracy of different motion directions judgment [12]. Rauber and Treue have found that the subjects tended to overestimate the distance between the observed motion direction and the reference direction and named it as reference repulsion [13], while Loffler et al. have found reference attraction (the subjects tend to underestimate the distance between the observed motion direction and the reference direction) [14]. In conclusion, what is the rule of judgment accuracy in different motion directions, the existing research does not come to a unified conclusion, and corresponding researches are unavailable whether the gravity conditions will influence the individual’s motion direction judgment ability or which influences will be caused. Therefore, this study investigates the influence of gravity conditions on the motion direction judgment through the short-term simulated weightlessness condition with −6° head-down tilt bed. In the past, the stimulation mostly adopted for the research on motion directions includes straight line, gratings (grids) and random-dot patterns. In order to close to the actual task scene, single dot motion occlusion paradigm is adopted in this experiment.

2 Methods 2.1

Subjects

Eighty college students aged from 18–29 (M = 20.79, SD = 2.15), half of male and female, participated in the experiment.

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Fig. 1 Absolute value of judgment deviation

2.2

Experiment Design

The 2  4 double-factor mixing experiment design is adopted for the experiment. The independent variable is gravity conditions (the sitting posture represents natural gravity condition; head-down tilt posture represents simulated weightlessness condition), motion directions (upward, downward, leftward, rightward); wherein, the gravity conditions are the between-subjects variable, and the motion directions are the within-subjects variable. The dependent variable is the absolute value of the angular deviation, that is, the absolute value of the difference between angle A between the connecting line of the initial position and the click position and the motion direction of the target and the motion angle B (shown in Fig. 1).

2.3

Materials and Tasks

The motion direction judgment software programmed with C#. At the beginning of the program, the center of the screen is provided with a black circular target and a black annular shelter; after the screen is still 500 ms, the target randomly moves uniformly in a straight line at any angle of any direction of upward, downward, leftward, and rightward until it disappears in the inner side of the shelter; the outer edge of the shelter becomes blue and the mouse appears in the center of screen; the subjects shall forecast where the target will appear on the blue edge, click it with the mouse, and then the red dot feedback appears to be successful. The program entered the next test (Fig. 2)

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Fig. 2 Program running interface: a initial interface of test; b feedback interface of test after subject have clicked

In the experiment, there were seven motion angles in four directions of upward, downward, leftward, and rightward, respectively, −15°, −10°, −5°, 0°, 5°, 10°, and 15°, and positive values represent the clockwise direction at the motion direction.

2.4

Instruments

Mi Notebook Air notebook computer with a screen size of 12.5 inches and resolution of 1920  1080. The program automatically records the parameters. The line of view of the subjects remains horizontal with the center of the notebook screen at a distance of 50 cm. For simulated weightlessness (head-down tilt) condition, the subject shall lie on the experimental bed at −6°. Experimental parameters configuration information: The target diameter is 40px, the ring width of the annular shelter (the shelter distance) is 150px, the visible motion distance of the target is 350px (the viewing angle is about 5.78°), the motion speed of the target is 4°/s, and the visible motion time is about 1.45 s.

2.5

Procedure

The subjects should comprehend the instructions first and then start the practice. Four tests shall be carried out. The practice experiment has feedback to show the motion track of the target. In formal experiment, two judgments shall be carried out at each angle in each direction, with a total of 56 tests, the motion directions and angles are random. There is no feedback in formal experiment. When in simulated weightlessness experiment, the subject shall adapt for 3 min on the −6° experimental bed before starting formal experiment.

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3 Results After the extreme data is removed according to the “±3S” principle, the data is analyzed statistically. The results of the judgment deviation of gravity conditions and motion directions are shown in Table 1. The results of RMANOVA of 2  4 mixing design show the main effect of gravity conditions is not significant (F(1, 78) = 1.250, p = 0.267), the main effect of motion directions is significant (F(2.676, 208) = 6.404, p = 0.001), the interaction of gravity conditions and motion directions is significant (F(2.676, 208) = 3.790, p = 0.014). The further simple effect analysis shows that: in the upward motion direction, the judgment deviation under the simulated gravity condition is significantly larger than the natural gravity condition (see Table 2).

4 Discussion In the past, because of different research purposes and the experimental paradigms, the deviation results of the motion direction judgment are mostly positive and negative to indicate that the error is more biased in the clockwise direction or the counterclockwise direction, which is more difficult to intuitively reflect the trend of motion direction judgment in various directions. It is also found in this experiment that there is a difference in the motion direction judgment accuracy in four motion directions, especially in the vertical direction, the judgment deviation in the upward direction is significantly smaller than that of the downward direction, and the reason may be related to the visual movement rule. Kolev et al. have found that there is an up and down asymmetry of the gaze speed of the moving object in vertical plane Table 1 Deviation of direction judgment under different gravity condition (M° ± S°) Gravity condition

Upward

Downward

Leftward

Rightward

Natural gravity Stimulated weightlessness

1.26 ± 0.45 1.55 ± 0.56

1.66 ± 0.49 1.74 ± 0.46

1.49 ± 0.55 1.63 ± 0.63

1.61 ± 0.51 1.46 ± 0.45

Table 2 Independent sample T test on gravity conditions Natural gravity-stimulated weightlessness Upward-upward Downward-downward Leftward-leftward Rightward-rightward *p < 0.05

t

df

Sig

−2.576 −0.745 −1.076 1.426

78 78 78 78

0.012* 0.458 0.285 0.158

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[15]; Ding has found that the amplitude of the saccade distance, and the fixation time of upward motion is smaller than downward motion [16]. Similar to this, Darlot et al. and Matsuo et al. have considered that the nystagmus in the horizontal direction is generally consistent, but the nystagmus in the vertical direction is asymmetry, which means that compared with downward direction, the saccade frequency, and the gain of the upward nystagmus are smaller [17, 18], this makes eye movement tracking in the upward direction more precise, perhaps it is one of the causes of the difference in vertical motion direction judgment. When the three-dimensional space motion is represented by two-dimensional plane, for example, in the map navigation display, the upward direction means the forward direction and downward direction means the backward direction [19, 20]; therefore, the upward movement in the two-dimensional plane is generally regarded as a motion based on the centrifugal direction of itself as the center, and this kind of motion is more common in life, such as throwing, batting, and shooting aiming, the judgment of corresponding direction is the most familiar motion direction judgment, which may be the potential reason for the best performance on upward movement direction judgment under natural gravity condition in the study. Just for this reason, after changing the gravity state, the judgment of the upward motion direction is mostly influenced. This is the potential cause of a significant larger angle deviation in upward motion direction under simulated weightlessness condition compared to natural gravity condition. Generally speaking, short-term simulated weightlessness condition causes redistribution of blood, which affects the visual functions of individual and the overall influence on the motion direction judgment is negative. Under natural gravity condition, the saccade frequency and gain of the eyeball are smaller when the eyeball moves upwards [21], which may be one of the reasons for more accurate motion judgment in the upward direction. However, under simulated weightlessness condition, the inhibiting effect of gravity on the upward movement of saccade is weakened, and the upward motion judgment is negatively affected, and the judgment performance is obviously decline. For the downward motion, under simulated weightlessness condition, the saccade frequency and gain of the eyeball have a tendency to decrease, which may be advantageous in the direction judgment; however, taking into account the negative effect of unfamiliar body posture, there is no significant change in the judgment performance.

5 Conclusion The result of experiments under natural gravity condition and short-time head-down tilt simulated weightlessness condition shows: For both natural gravity condition and simulated weightlessness condition, there’s difference on upward, downward, leftward, and rightward motion judgment, and the upward direction judgment angular deviation is always less than that of the downward direction judgment;

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comparing with natural gravity condition, the direction judgment angular deviation of the upward motion is larger under the simulated weightlessness condition. Acknowledgements This work was supported by the Foundation of Key Laboratory of Science and Technology for National Defense (No. 6142222030301, No. 614222204020617, No. 9140A26070215KG57417, No. 9140C770205150C77319), and the Foundation of National Key Laboratory of Human Factors Engineering (No. SYFD170051802). Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhejiang Sci-Tech University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Chen SG, Wang CH, Chen XP et al (2015) Study on changes of human performance capabilities in long-duration spaceflight [J]. Space Med Med Eng 28(1):1–10 2. Manzey D, Lorenz B (1998) Mental performance during short-term and long-term spaceflight [J]. Brain Res Rev 28(1–2):215–221 3. Sandal GM, Leon GR, Palinkas L (2006) Human challenges in polar and space environments [J]. Rev Environ Sci Bio/Technol 5(2):281–296 4. Zhao J, Hu LN, Liang HZ et al (2010) Influence of head down tilt simulated weightlessness on electrophysiology of vision [J]. Int J Ophthalmol 10(9):1790–1792 5. Yu HQ, Jiang T, Wang CH (2016) Effects of 30 min postural change on intraocular pressure and visual performance [J]. Space Med Med Eng 29(3):195–200 6. Koga K (2000) Gravity cue has implicit effects on human behavior [J]. Aviat Space Environ Med 71(9 Suppl):78–86 7. Senot P, Zago M, Le Séac’h A et al (2012) When up is down in 0g: how gravity sensing affects the timing of interceptive actions [J]. J Neurosci 32(6):1969–1973 8. Wang DM, Gao W, Tian Y et al (2015) Influence of gravity on speed perception characteristics of human [J]. Space Med Med Eng 28(6):408–412 9. Heeley DW, Timney B (1988) Meridional anisotropies of orientation discrimination for sine wave gratings [J]. Vision Res 28(2):337–344 10. Hol K, Treue S (2001) Different populations of neurons contribute to the detection and discrimination of visual motion [J]. Vision Res 41(6):685 11. Gur M, Kagan I, Snodderly DM (2005) Orientation and direction selectivity of neurons in V1 of alert monkeys: functional relationships and laminar distributions [J]. Cereb Cortex 15 (8):1207 12. Blake R, Cepeda NJ, Hiris E (1997) Memory for visual motion [J]. J Exp Psychol Hum Percept Perform 23(2):353 13. Rauber HJ, Treue S (1998) Reference repulsion when judging the direction of visual motion [J]. Perception 27(4):393–402 14. Loffler G, Orbach HS (2001) Anisotropy in judging the absolute direction of motion [J]. Vision Res 41(27):3677–3692

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15. Kolev OI, Reschke MF (2016) Acquisition of predictable vertical visual targets: eye-head coordination and the triggering effect [J]. J Mot Behav 1–10 16. Ding JH, Lin ZH (2001) Visual smooth pursuit in different directions [J]. J Chin Psychol Acta Psychol Sin 2(12):664–670 17. Darlot C, López-Barneo J, Tracey D (1981) Asymmetries of vertical vestibular nystagmus in the cat [J]. Exp Brain Res 41(3–4):420–426 18. Matsuo V, Cohen B (1984) Vertical optokinetic nystagmus and vestibular nystagmus in the monkey: up-down asymmetry and effects of gravity [J]. Exp Brain Res 53(2):197 19. Shen F, Zhang ZJ (2002) Psychological topics on the design of virtual environment and WWW [J]. J Dev Psychol 10(3):315–321 20. Zhang J (2005) A research on navigation and spatial awareness in collaborative virtual environment [D]. The PLA Information Engineering University 21. Pierrot-Deseilligny C (2009) Effect of gravity on vertical eye position [J]. Ann N Y Acad Sci 1164(1):155

The Development of Military Helmet for Bare-Handed Combat Xiaobin Yang

Abstract In the training process, it is the key problem that the head is vulnerable which restricts the development of the bare-handed combat. For over 8 years, the author has been dedicated to the design and development of protection helmet for combat training and has made constant improvement according to the actual combat experience. The study include the close combination of the helmet body, mask, round protective cover pad and tightening belt, the wearing comfort and effective protection as well as injury prevention during the combat training. After comparison and analysis of various materials, from the angle of ergonomics, the protection mask, the ear protection design and the design of the fastening part are taken into consideration. So that the protection performance of the helmet is fully improved, and the inside surface of the mask is tightly attached with the face, which is not only comfortable for wearing but also has better performance in protection and shock reduction, and has set a foundation for the people-oriented design of helmet. The newly developed protective helmet can basically meet the training requirements with the function of really protecting the head, thus increasing the safety in during bare-handed combat, which is beneficial to the wide promotion of bare-handed combat training and can improve the battle effectiveness of the officers and soldiers. Keywords Bare-handed combat

 Protective helmet  Confrontation training

1 Purpose of Study Under the background that our army is deeply developing practical training, it is the issue worthy of our thinking how to improve the combat ability of troops and soldiers. In order to enhance the bare-handed combat skill of soldiers and improve the ability of everyone, the most important is that every soldier must strengthen the

X. Yang (&) Army Academy of Special Operations, Guangzhou 510500, Guangdong, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_50

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combat training in daily training. It is not enough to only master the skill of combat training, which is the same as talking about stratagems on paper. It must be subject to the demands of actual combat for officers and soldiers to master certain theoretical knowledge and action skills, change the method of substituting combat training practice combining with the routine practice, and establish the target of focusing on practical combat [1]. The combat ability can be strengthened day by day only by constantly exploring the experience in the practical combat. However, officers and soldiers will be easily injured during practical combat, particularly to the head. The head is the most important part of human body and governs the activity of the whole body. If the head is injured, it will influence the normal training of officers and soldiers under light situation, which is not conducive to the improvement of combat effectiveness, and even endanger the personal safety and life safety of the officers and soldiers under severe situation. Therefore, some grassroots units, in practical combat skill training, only simply learn the technical skill of single soldier and do not promote the practical combat training, which causes that the bare-handed combat ability of soldier is not really improved. Therefore, starting from the protection of head, it has the practical application value and the urgent practical needs to design the protection helmet complying with the training needs of the troops. In the past, when promoting practical combat training, the main units adopt the head protector which is used for sports training such as boxing and Taekwondo for the bare-handed practical combat of troops. Such helmet is mainly used for protecting the head and the ear, without the protection of face. The rules, striking parts, and effective score are adopted for strictly restraining the contest of the social sports; however, military combat techniques are used for wartime purposes: One is to capture captives; the other is to destroy the enemy [2]. Bare-handed combat strives for striking the crucial point with dead blow. The striking strength, speed and objective are different from the sports activity. There is a gradual discovery of deficiencies and defects during the use: 1. The protection ability of helmet for the sports training such as boxing, free combat, and Taekwondo is weak, and the protection effect to the head is poor; 2. the center of gravity of the helmet is high, and the stability and comfort after wearing are poor; 3. because there is no mask, it cannot alleviate the attack on the nose and brow, and there is no good protection to the face. The results from the above points are that the confrontation training will easily cause an impact on the head and even endanger the life safety under severe situation; secondly, helmet is designed as a whole structure, cannot be adjusted according to the head of the user, and cannot be well fixed. The shape of the helmet cannot perfectly match the head size, and the protective area is unreasonable, which influences the overall feeling of the user. The joint cannot be quickly opened and tightened; therefore, the wearing comfort and stability of the head under active state cannot be met. In comprehensive combat, the application of the wrestling and controlling method, in particular, it will easily loose when sizing and controlling the head and neck, which may influence the effect of training and competition. In order to ensure that the protective helmet meets the needs of current bare-handed combat training, the advantages and disadvantages of various helmets

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shall be fully analyzed in the research and development, and some advanced design advantages shall be adopted; then, optimization and innovation shall be carried out according to the head characteristics of Chinese soldiers and the military training requirements. The design of protective mask, ear protection, and tightening part design shall be considered from the perspective of ergonomics and ensure that the inside surface of the mask can perfectly be attached on the face. The purpose is to develop the combat helmet which is not only comfortable, but also has good anti-injury and shock-absorbing performance, so as to strengthen the protection of the head, also improve the flexibility and the enthusiasm of soldiers in the combat training, and meet the needs on practical combat training of troops.

2 Study Methods 2.1

Documentation Method

The documentation used the database of www.cnki.net and lib.cqvip.com, and referring to relevant documents on the protection helmet design and manufacturing, and collecting and sorting the design and manufacturing methods and effect of different types of helmets for reference.

2.2

Interview Method

Interview with the training personnel of the officers and soldiers can realizing the feelings of the officers and soldiers after practical combat with various helmets. Then adjusting and improving the development method according to the interview results.

2.3

Comparative Analysis Method

Test, compare, and analyze the shape and performance of protective helmet; constantly develop the new through critical assimilation of the old; and strive to maximize the practicability of helmet.

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3 Study Results A long-term follow-up study on the problems found in bare-handed combat training and practical combat of troops, the design method of man–machine engineering, and the optimized development of protective helmet is carried out for eight years. The protective helmet basically consists of helmet top, mask, helmet body, round protective cover pad, a fastening belt. The mask, helmet body, round protective cover pad, and fastening belt are not only the major factors influencing the wearing comfort of the helmet, but also have the function of ensuring effective protection during combat training and avoiding injury. Therefore, it becomes an important reference standard for the humanized design of helmet how to achieve the close combination of the above four aspects and ensure it to meet the basic requirements of humanized design [3].

3.1

Improvement of the Material Performance and Analysis of Advantages and Disadvantages of Several Helmets During Development

Helmet material is the important aspect of ensuring the safety of helmet [4]. The selection of different materials has a direct effect on the design performance of helmet, and the material selection shall follow the principle of strong bearing ability and lightweight. In the process of development, dozens types of models have been tested, several representative samples are selected for analysis, and relevant contents are shown in the following table: Type and time

Materials and upgrading

Advantage

Disadvantage

Main body: PUR— Polyurethane Mask: steel bar covered by foam Back head lace

Wide protection area

Narrow sight; heavy; steel bar is easy to break and dislocate

Top of helmet and main body: taking shape after two-time EVA foaming, artificial stitching Mask: PC Back head lace

Wide protection area; Light; easy to wear

The holes on the mask is too large; Craftsmanship is low; anti-strike level is low on the sides considering the sound hole; easy to fall off in wrestling

Mask: PC Change:

Wide protection area;

The holes on the eyes part are too large so that (continued)

Type 1 2012

Type 3 2013

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(continued) Type and time

Type 4 2014

Type 5 2015

Type 9 2016

Type 12 2017 Patent number 201721055873.8

3.2

Materials and upgrading

Advantage

Disadvantage

Reduce the size of the holes on the mask Open four holes on the top for heat rejection Back head lace changed into a magic belt

Light; more stable and tight in wearing; top heat rejection

Change: 1. Close the whole face 2. Seven heat rejection holes on the top; three internal installed sound holes on each side 3. Internal installed adjustable belt on the top and around protecting pad Change: 1. Mask radian smaller 2. 3 cm thinner on the internal position of eyes, 3-cm-wide rectangular-shape windows 3. One layer of pad close to the face in the helmet Open two holes for eyes with 5 cm wide

Light; more stable and tight in wearing; top heat rejection; good to protect the whole face

finger attack can still hurt the eyes Craftsmanship is low; top, side, and back parts are very weak to defend; easy to fall off in wrestling and side attack The number of holes is not enough so that vapor is easily produced; Top, side, and back parts are very weak to defend; easy to fall off in wrestling and side attack

Light; more stable and tight in wearing; top heat rejection

Vapor is easily produced; 3-cm-wide rectangular-shape windows affect the sight in fighting

Good view; more stable and tight in wearing; light; easy to wear; safe; good in integration

Opening eyes cause possible hurt into the eyes by finger attacks; this needs a solution from regulation or finds a way out to dismiss the vapor

Materials and Properties of Current New Helmet

Compared with modern competitive sports helmet technology, the newly developed bare-handed combat helmet has the advantages that:

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1. The whole helmet adopts Class A EVA foam, and the material of Grade A or above is foam with high elasticity and has the characteristics of less airholes, uniform thickness, eco-friendly, and odorless; EVA product is the new type eco-friendly plastic foaming material and has the advantages of good shock resistance, heat insulation, buffering, moisture resistance, and chemical corrosion resistance; it would not absorb water and is non-toxic [5]. The helmet body is provided with ear profile hole and round hole. One high-pressure Grade A EVA foam corresponding to the human ear is set on the inner side of the helmet body, and the hole at the ear can prevent the direct strike at the ear due to its shock-absorbing effect. The round hole can dissipate heat and hear the external environment sound during combat, which is beneficial to master the external information and react in time. 2. The mask is made of PC material and features high strength, high elastic coefficient, high impact strength, high transparency with high temperature resistance reaching 125° and low temperature resistance reaching −40°. In addition, its features are low forming shrinkage, good size stability, good weather resistance, odorless, without harm to human body, and sanitary and safe [6]. The face mask is developed entirely from the angle of ergonomics, is an eye–face integrated face protective gear. At the position of forehead on the face mask, there are arranged with three oval holes side by side to facilitate heat dissipation and sweat evaporation; at the position of eyes is set with two holes as aviator sunglasses at the right and left sides, which provide complete field of view for the user to clearly see the surrounding environment. Three irregular holes are arranged at the position of nose, three oval holes are arranged at the cheek, four long oval holes are arranged at the mouth position to benefit exhaust, two sides of the mask and the forehead are provided with band. The forehead is provided with a soft cushion, and the cheeks are provided with soft cushions on both sides, which can fit various face shapes. The forehead and cheeks are padded to avoid friction between the chin and the mask, which fits the face, and can prevent sweat flow into the eyes or mouth during combat. If the face or the nose has been hit or torn, it can prevent external collision again and reduce the injury. 3. The top of the helmet is divided into two layers, and both layers are set with Grade A EVA foam, wherein the outer layer is set with several round airholes for heat dissipation. The inner side is set with five fastening bands, and the other end of the fastening bands is set in five opening grooves on the round protecting cover in the middle part of the inner side of the helmet. One end of the fastening band at the opening groove is connected with the fastening rope, and user can adjust the size and height, so that the helmet can perfectly fit to the head shape; the stability, the comfort, and the flexibility are improved, which can also relieve the impact on the head during combat. 4. At the position close to the face in the front side of the helmet is set with protective pad which can effectively fix the head, prevent the head from moving forward, avoid the nose and teeth knocking the mask. The rear side of the helmet adopts thickened Grade A EVA foam with better protection to the back side of

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head, which can effectively relieve the impact to the back side of head during combat training. The inside of the helmet is made of PU material with smooth surface, which is convenient for wiping and cleaning. 5. Fastening device: It is used for fixing the helmet, and it is convenient for operating with Velcro, so that the helmet will not fall off during fierce combat, which can improve the wearing comfort and following the performance stability during the activity. After it is fastened and fixed, the helmet is firm and reliable and is convenient for fixing and unlocking.

4 Conclusion of Study Combat training is one of the important contents of troops training. It is irreplaceable to train the soldier’s courage, tenacity, fearless, and aggressive fighting spirit through bare-handled combat training. However, soldiers are often hurt during training, and even the injury may be serious, which is an important factor that restricts the development of practical combat training. The purpose of our study is how to reduce the probability and degree of injury of officers and soldiers. The protective helmet is the most important and most critical part of all combat protection gears since it protects the most important part of the body—the head. The military bare-handed combat protective helmet meets the development demands of Chinese troops on practical combat, and the development of the helmet has referred to the design advantages of other advanced helmets and is optimized and innovated according to the head shapes of Chinese soldiers. From the angle of man–machine engineering, the protective mask, the ear protection design, and the fastening part design are taken into consideration, which can completely improve the protection performance of the helmet, and the inside of the mask can tightly be attached with the face, which is not only comfortable when wearing, but also features good anti-injury and shock-absorbing performance, and has set the foundation for the people-oriented design of helmet. The military bare-handed combat protective helmet is particularly suitable for primary trainers. When the primary trainer just starts combat training, it can not only protect the head of both parties, can reduce the probability of injury during combat, does not influence the combat skill of soldiers, and can reduce the fear of being attacked; therefore, it can benefit to improve the practical combat skill of soldiers, ensuring the effect of training, and improving the safety, flexibility, and training enthusiasm of soldiers during practical combat.

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References 1. Reform and probe of actual combat training and teaching. J Mil Phys Educ Sports (2014), 33 (2):52–55 2. Organization and implementation of military combat bare-handed competition. J Mil Phys Educ Sports (2016), 35(2):18–20 3. Military helmet design based on ergonomics South East Jiaotong University 4. The creative methods research of helmet design market modernization (2010), (18):9–10 5. https://baike.baidu.com/item/EVA%E5%A1%91%E8%83%B6%E5%8E%9F%E6%96%99/ 10294117?fr=aladdin 6. https://wenku.baidu.com/view/489cecae31126edb6e1a1035.html

Study on Human Adaptability in Urban Underground Space Combat Environment Under Special Circumstances Wang Wang and Hangdong Wang

Abstract The military application value of urban underground space is becoming more and more prominent under the threat of air-sky reconnaissance and precision strike technology. In this paper, with the background that the environment of the urban underground space is destroyed, the relation between the combat environment and the human body in the urban underground space under special circumstances is studied. Through research, it is found that the environment of urban underground space mainly has the characteristics of dark, moist, low oxygen and harmful gases exist in the air, high microbial index, and so on; the combat crew is confronted with influences from aspects such as physical, psychological, and physical fitness when combating in the urban underground space, which severely restricts the normal execution of combat tasks among the combat members in the environment. According to the influence of urban underground space environment on human body under special circumstances, it is planned to provide theoretical reference for urban underground space combat research by means of scientific training methods and means, so as to improve the mental ability, physical fitness, and physical adaptability of combat crews. Keywords Urban combat environment

 Adaptability  Underground space

Foreword Urban underground space mainly includes subway, underground shopping mall, underground garage, urban sewer, underground command station, civil defense engineering, etc. With the development of urbanization, the construction of urban underground space has been increasing year by year, which can not only satisfy the basic development of the city, but also highlight the unique military application value. Under the threat of modern weapons, some important facilities related to the lifeblood of the country and army have been gradually set underground, which has become the common practice of all countries in the world. The underground space W. Wang (&)  H. Wang Special Operations Academy, Guangzhou 510500, Guangdong, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_51

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has good defense characteristics, the urban underground space is the important infrastructure of the city, and is also the important place of military operation, combat command, materials reserve, and refuge, and it fully reflects the characteristics of military and civilian integration. Under the background of the rapid development of air-sky reconnaissance navigation and precision strike technology, ground targets face increased risk of being attacked, the space of battle has been extended from the plane to three-dimensional, and underground operation has become a new platform for future combat. It is the urgent subject to study modern underground combat, and urban underground space combat is an important part of modern underground combat, and it is very important to study underground space under special situations. The urban underground space environment under circumstance refers to the facilities that destroy the normal operation of the underground space, and the environment of the underground space is quite different from the ground environment. The underground space is under closed state, and the environment is particularly bad; the physical efficiency is greatly challenged after settling in it for a long period. The paper studies the environment of urban underground space from different angles, analyzes the influences on human body in the urban underground space environment, and how to overcome the influences, thus providing theory and practice reference for future urban combat.

1 Characteristics of Urban Underground Space Combat Environment Normally, there isn’t great difference between the environment of urban underground space and the ground environment; it does not have any problem for human to work and live in the underground space, which is mainly benefited from the infrastructure such as air-conditioning system and lighting system. However, the equipment is extremely easy to be destroyed in the war. Once the facilities are lost, the environment of the underground space will change obviously, the air is not flowing, oxygen content in the air is decreased, temperature starts to change, microorganisms start to breed, and harmful gases may possibly exist, which may greatly affect the activities of human in urban underground space.

1.1

Dark and Moist

After the underground space infrastructure has been destroyed, the underground space will become dark. The suitable illuminance for human is 100 lx, and the illuminance for basically meeting the vision is 50 lx; however, the illuminance in the underground space is  50 lx. In the case of low illuminance, the nervous

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system of human body is affected correspondingly, the underground space is relatively moist in the closed state, air convection is not formed, combining the influences from soil and other factors, the humidity in the air is obviously high, which may cause uncomfortable feeling or diseases after human has settled in it.

1.2

Low Oxygen Content with Harmful Gases

When air convection is not formed, oxygen in the underground air will be consumed by substances such as underground microbes, soil layers, and materials, and oxygen content in the air is obviously reduced. In addition, the building materials or the environment in the urban underground space may also produce a series of gases which are harmful to human body, such as carbon monoxide, ammonia, hydrogen sulfide, formaldehyde, radon gas, benzene, and so on.

1.3

High Microbial Index

Under the condition of dark, moist, and poor air circulation, the urban underground space is very easy to breed a large number of bacteria, fungi, and anaerobic bacteria. Bacterial breeding is closely related to water. In general conditions, bacteria cannot grow normally if it lacks water, while underground space is dark and moist, which provides a good site for bacteria. The reason of fungus is mainly the decomposition of underground space objects or building materials in a dark environment, and fungus drifts in the air as airflow. The growth of anaerobes is mainly caused by low oxygen content in the underground space; due to the closed state, it is very advantageous for anaerobes growth.

2 Influences on Human for Combating in the Urban Underground Space The urban underground space environment under special circumstances is quite different from the urban underground space environment under normal circumstances. The underground space environment under special circumstances affects human in the aspects of oxygen, air cleaning, light, humidity, and harmful gases, which may cause the human body to generate adverse psychological problems, physical fitness problems, and functional problems in the urban underground space environment.

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Physiological Impact

Since the environment of the urban underground space is relatively special, oxygen content in the air is low, the air is cloudy, the light is insufficient, the humidity is high, and the harmful gases exist. After human has settled in it, the physiological influences on human mainly include the following aspects: first, the nervous system. In the case of insufficient oxygen supply to the brain, the central nervous system will be affected, which will cause slow response, decreased attention, dizziness, etc. Second is the circulation system. In the low-oxygen environment, the heart rate and the blood circulation is accelerated to meet the requirement of human body on oxygen. The acceleration of blood circulation mainly depends on the rapid blood pumping of the heart, and the long-term and high-load stimulation to the heart may cause myocardial damage. When the heart pumps blood under high load, the oxygen demand of the body is not satisfied, and the movement ability of the limbs is restricted to a large extent. Third is the immune system. According to the data, the short-term settlement in the semi-closed environment of tunnel, due to the factors such as special temperature, humidity, darkness, and emotion, the cellular immunity of human body will have obvious change [1]. It is shown that the reduction of humoral immunity and cellular immunity after soldiers have settled in the closed or semi-closed tunnel for 7 days” [2].

2.2

Psychological Impact

There is a study that the adverse psychological phenomenon generated to human in the underground space is caused by four points: “first is that people associate the underground space with death and burial; it will have an adverse effect on people’s psychology; second, people are afraid of collapse; third, people always think of the underground space with the moist basement with poor air ventilation; fourth, the claustrophobia of human” [3]. From the angle of campaign, the influence of urban underground space on human psychology is no less than that of other aspects, because of the narrow, closed, dark, non-discrimination, low oxygen, and unknown factors of underground space, it is extremely easy to generate psychological phenomena such as tension, depression, fear, loneliness, fatigue, restlessness, air depression.

2.3

Physical Fitness

Under special circumstances, the influence of urban underground space on physical fitness of human is obvious; under the environment with low oxygen content, the nervous system, respiratory system, circulatory system, and immune system of

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human body will be influenced. Therefore, early fatigue, slow reaction, reduced endurance, reduced speed will occur in human body. The Hypoxic environment influences the structure of skeletal muscle is enhanced. Under the low oxygen environment, the decomposition and metabolism of human body are strengthened, the density of capillary vessels is increased, and the shape of muscle is changed. The low-oxygen environment influences the exercise function of skeletal muscle. Under the hypoxia condition, the protein synthesis rate decreases, muscle fibers become slim, which causes the reduction of endurance and the maximum force of muscles. Under the hypoxia condition, in order to obtain more oxygen, the respiration, heartbeat, and circulation are accelerated, the heart load is increased, which is not beneficial to strenuous exercise; otherwise, it will cause exercise-induced hypoxia, and people will feel dizzy, chest distress, and even syncope.

3 Research on Adaptation of Human Body in Urban Underground Space Combat Environment The special urban underground space causes various physiological influences on human body. Speaking from the vision of urban combat, the urban underground space mainly causes mental, physical, and functional influences on the combat crews. Scientific training and response measures shall be formulated to solve the influences on combat personnel under special urban underground environment, thus meeting the demands of the combat crews to execute the tasks in the urban underground space.

3.1

Psychological Adaptation

In order to better adapt to the urban underground space environment, it is necessary to strengthen the psychological adaptation training of the urban underground air combat environment and improve the combat psychological quality of the combatants. The psychological adaptability training of urban underground space includes, first, the adaptation to dark environment; dark environment influences the human vision; the eyes cannot quickly adapt to a dark environment in a short time, which will influence the balance ability of human body, and is not beneficial to walking. Therefore, it is suggested to strength the adaptation of the dark environment and stay for a while when entering the dark environment, so that the vision can timely adapt to the dark environment; Second, the adaptation to fear, the urban, because the urban underground space structure is complex and dark with more potential danger factors, and the combat environment is extremely complex, which causes great challenge to the psychology of the combat crew; therefore, it requires strengthening the training on resisting fear, strengthening the simulation training of

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underground space combat and scientific psychological education to improve the ability of resisting fear; third, anti-loneliness training, because it is not allowed to speak loudly in the urban underground space, and the underground environment is relatively isolated from the outside environment, it will easily cause the lonely psychology; therefore, training on staying alone, training on independent combating, and corresponding anti-loneliness in the lonely environment are required, so as to improve the psychological quality of the combat crew.

3.2

Physical Fitness Adaptation

Physical fitness is the basic ability to support the combat crew; the reduction of physical fitness will seriously affect the skill of combat crew, so it is essential to keep the combat crew at good physical fitness in the urban underground space. Analyzing on the environment of the urban underground space, the reasons causing physical fitness reduction are mainly: low oxygen, dark and moist, air turbidity, harmful gases, and high microbial index, which results in the reduction of endurance, sensitivity, and strength of human. Scientific training shall be provided to improve the physical fitness of the human and adapt the human to the urban underground space environment under special circumstances. Endurance training. Analyzing on the environment of the urban underground space, under the condition of low oxygen content, the endurance of human body will be reduced. It is necessary to carry out aerobic training and altitude training. Aerobic training can improve the endurance of human body, while plateau training is relatively close to simulated the low oxygen content state of the underground space and can promote to increase hemoglobin, improve the oxygen-carrying capacity and improve endurance of human body. Strength training. Strength is the basic physical attribute of human body; the reduction of strength will inevitably affect the performance of skill. According to the need of the urban underground space combat, targeted strength training plan shall be formulated, the upper limb strength can be improved by using chinning, push-up, a triceps dip, rod (rope) climbing, dumbbell laterals, dumbbell bench press, dumbbell benching; core strength: sit-up, plank, side bridge, glute bridge, and 0; strength of lower limb: front raise of both arms, hock sprung with hands on head, inclined reverse crunch, box horse, jump on both sides wooden stool, leapfrog, calf raise, squatting with weight, and so on. Agility training. Agility quality refers to the ability to quickly change body position, converse action, and adapt to circumstances. It is characterized by completing the action according to circumstance, that is, the movement of the body can be changed quickly and accurately under various conditions. Agility training can adopt the methods such as rope ladder training, sound reaction training, light reaction training, quick variable direction training.

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Professional Skills Adaptation

Adapting to the urban underground space environment under special circumstances can, it is mainly to ensure that the combat crew can play the combat skills normally and complete the combat task successfully. The physiological function adaptation and fitness adaptation of human body are the basis of supporting professional skills; while emphasizing the adaptability of basic skills, more attention should be paid to the training of professional skills. The skill adaptation training of urban underground space combat can be provided by establishing simulation urban underground space combat laboratory, and the laboratory should be highly similar to the real environment so as to facilitate practical training. Simulated training can also be provided with the latest advanced technology and VR technology. The training data are collected, and the actual data of the combat training is obtained through data analysis, so as to adjust the next skill training scheme and formulate the tactical scheme.

References 1. Zhang YL (Oct 1996) Relationship of tunnel ventilation and microorganisms. J Prev Med Chin PLA 6(3):3 2. Zhang YL (Oct 2005) Short-term tunnels semi-hermetic environment affect the body’s immune function. Chin J Public Health Eng 3. Srerling R (1981) Earth sheltered housing code, zoning, and financing issues. Underground Space Center, University of Minnesota 4. Zhang H (2016) On environmental treatment of urban underground space. Shanxi Archit (42) 5. Zhang YL (2006) Observation of the effect on human of underground part-obstructed situation. Mod Prev Med 6. Zhang S (July 2005) Underground part-obstructed environment and human health. J Environ Health

Study on the Influence of Interior Decoration of Ship Cabin on Crew’s Visual Work Efficiency Hangtao Cheng, Chuan Wang and Zhe Wang

Abstract The ship “man-machine-environment” system engineering is a new discipline, and its purpose is to establish a man-centered, optimized combination, and scientific configuration in the ship’s complex human, machine, and environmental systems. Cabin environmental engineering is an important part of it, which has significant significance for improving seafarers’ quality of life on the sea, improving the daily work efficiency of seafarers, and maintaining the physical and mental health of seafarers for a long time. The cabin of the ship is the main place for the crew to work and move directly during driving, and cabin space is a microcosm of ship safety and comfort. However, the current research on ship cabins is more oriented toward functional design, and the interior decoration of the cabin is ignored. This is extremely bad for improving the visual comfort of the crew. Based on this, the influence of the interior decoration of the cabin on the visual efficiency of the crew is explored in this paper. Keywords Ship cabin

 Seafarers  Interior decoration  Visual effect

Foreword As an important part of the ship’s overall design layout, the ship cabin plays a vital role in the safety and performance of the ship [1]. In particular, the interior decoration of the ship cabin, it is directly contacted with the crew, so its design not only influences the visual, psychological, and consciousness activities of the crew, but also directly influences the working efficiency and driving safety of the crew [2]. Therefore, the interior decoration design of the ship cabin has an important effect on the crew’s visual work efficiency.

H. Cheng Naval Armament Guangzhou Office, Guangzhou 510382, China C. Wang Department of Protective Medicine, Naval Medical Research Institute, Second Military Medical University, Shanghai 200433, China e-mail: [email protected] Z. Wang (&) Beijing Institute of Astronautical System Engineering, Beijing 100076, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_52

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1 Overview of Ship Cabin The overall layout of the ship cabin directly determines the overall decoration effect and the visual sense of the ship. In which, the modeling of the work cabin facilities is an important part of the whole ship cabin decoration design, the living cabin is the main part of the whole ship cabin, the ceiling of the living cabin, the luggage case, the subdivision plate, and the partition board are the concrete manifestation of the overall effect of the living cabin, and these parts constitute the overall structure of the ship cabin. The design effect of interior decoration of ship cabin directly influences the crew’s physical, psychological, and consciousness activities. The crew not only pays attention to the practicability of each system function inside the work cabin but also pays attention to the visual sense of interior decoration. Good visual feeling can effectively relieve the tired feeling of the crew caused by longtime driving, so that the crew can release the psychological pressure during driving and ensure clear brain and safe driving.

2 Design Principles of Interior Decoration of Ship Cabin 2.1

Safety

Safety is the primary requirement of ship driving. The whole driving process of the crew includes access to work cabin, sailing, maneuvering driving, landing. During driving, the time that the crew stays in the work cabin is longest, so design of the interior decoration of the ship cabin is especially important to emphasize in safety, which requires that the design of exposed parts of the interior trim of the work cabin shall not have sharp objects, thus avoiding the crew injury and affecting driving. A safe work cabin environment can effectively relieve the psychological pressure and psychological concerns of the crew and improve the driving efficiency.

2.2

Mistake Prevention

After longtime driving, it is extremely easy to make mistakes in judgment and operation, which requires that the design of interior decoration of ship cabin should be of considerable mistake prevention. For example, the indicators, switches, and buttons in the work cabin shall be divided according to areas of functions, so that the layout of the work cabin is more reasonable, thus effectively preventing the crew from mistaken operation caused by the disordered layout [3]. For example, the position of dangerous switches shall be set as far away as possible from the

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commonly used switches, and the mistaken prevention design shall be set so that certain misoperations of the crew are invalid.

2.3

Sensory Adaptation

The environment in the work cabin causes important influence on the visual acuity and psychological activity of the crew; therefore, the design of the interior of work cabin shall ensure that the crew still has the ability to drive the ship in a complex environment. For the layout design of the work cabin, it is intended to overcome the adverse effects of driving caused by low visibility, strong light exposure, and cloud. This requires a scientific and reasonable layout of lighting facilities in the work cabin, ensuring that sufficient and bright lighting can be provided so that the crew can clearly determine the driving state without causing misjudgment due to glare. The beautiful work cabin environment can keep the crew in a vigorous state, keep a clear mind, and reduce the occurrence of misoperation.

2.4

Wide Space

The narrow space produces an oppressive feeling, and especially the ship cabin is a relatively narrow space. If the narrow space is not fully utilized during layout design, it will inevitably result in the crew’s adverse effect on the environmental space. Therefore, it is necessary to create a spacious space for the crew when designing the interior of the ship cabin; for example, the seat of the crew shall have the lift function so as to make the crew generate a sense of a wide vision and space. The wide work cabin interface can promote the crew to quickly and comprehensively monitor the operating conditions of the ship systems, and timely find failure, thus effectively reducing the driving load and relieving visual fatigue.

3 Points for Attention of Interior Decoration Design of Ship Cabin 3.1

Color

Color gives strong visual impact, harmonious color gives the calm and pleasant mood, and on the contrary, the dark and disordered color will bring the feeling of restlessness. Therefore, the beauty of color has an advantageous effect on the psychological and physiological functions of the crew and can effectively promote

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the full play of crew’s ability [4]. Therefore, the display, instrument, switch, and button shall be designed with reasonable layout in the work cabin, and the color tone shall be harmonious and regular.

3.2

Lighting

The lighting of the ship cabin mainly adopts two modes: direct lighting and indirect lighting. Direct lighting is to improve the brightness of the whole work cabin through the shape and placement of the lamp, but the disadvantage is obvious that in the narrow ship cabin, the light source is directly in contact with the eyes of the crew, which may easily cause the crew to generate the feeling of dazzling and giddiness. Indirect lighting is to gently and uniformly light the work cabin through the diffuse reflection of the work cabin surface, and the light does not directly shine on crew’s eyes. However, the light of indirect lighting is not exposed, and there is a problem of insufficient illumination, which will have a certain influence on the crew to acquire monitoring information. Therefore, how to select the lamp shape and where to install it are the key difficulties in interior decoration of work cabin, which shall ensure that sufficient brightness can be supplied to the work cabin, and the driving safety and the working efficiency of the crew will not be influenced due to direct light. First, by adopting the mode of dynamic lighting, according to the change of the degree of light and shade in work cabin, the brightness in the work cabin shall be changed during driving, thus effectively improving the comfortable visual feeling of the crew. Second, by adopting the sensitivity adjustable electronic curtain, the crew may adjust the brightness of the cabin according to the actual demands on light in the work cabin, so that the crew can concentrate the attention on the ship, quickly obtain the information of different systems of the ship, and effectively prevent the driving mistakes.

3.3

Space

The space modeling of the ship cabin is arc-shaped and streamlined to create the more tranquil and spacious space, and the crew can feel an open visual experience in the cabin. First, in the design of ceiling and side wall, the dimensional modeling effect shall be created, so that the visual space in the work cabin is expanded, and a sense of spatial form gradations is produced. Second, the instrument panel and console in the work cabin shall be designed to have a certain inclination, which can not only increase the operating space in the work cabin but also facilitate the crew to quickly obtain more favorable information for effective operation. For example,

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Quantum of the Seas, in the design of work cabin space layout, adopts the open-type channel with large arch shape and arc dome, and the top of the work cabin simulates the model of the sky to create a peaceful and wide feeling.

3.4

Material

Different from the above three categories, the interior decorative material of the ship cabin is a physiological-based psychological experience for the crew’s visual work efficiency; simply speaking, it is the comprehensive impression of the sensory organs to the material. It is shown in relevant researches that the visual work efficiency of the crew is influenced mainly by the physical characteristics and psychological perception [5] of the interior decoration material of the ship cabin. When the sunlight is moderate in the ship cabin, the crew may have different visual textures to different materials, and the main reason for this phenomenon is that the human eye is affected by the texture of the material. For example, when smooth surface and fine material are used in the interior decoration of ship cabin, the crew will feel dazzling due to the concentrated reflection of light, and when rough material is used to decorate the interior space of ship cabin, the visual work efficiency of the crew is usually mild. Viewing from the actual situation analysis, the materials widely used in interior decoration of ship cabin include metal, leather, plastic, and fabric. In order to ensure better visual work efficiency for the crew, a good texture must also be selected according to the viewing angle, in addition to suitable material adopted.

4 Conclusion In conclusion, the color, brightness, and space of interior decoration of the ship cabin have an important effect on the visual acuity and psychological activity of the crew. Comfortable tone, suitable light, and sense of a wide space play an important role for the crew to exert the capacity. Therefore, during interior decoration design of the ship cabin, it is necessary to achieve the integration of high efficiency, safety, and beauty, so as to improve the work efficiency of the crew and ensure driving safety.

References 1. Sheng J, Zhao X, Wang X et al. (2008) Research on seafarers’s organism function state and navigability. China Saf Sci J 18(1):69–73 2. Lu W, Shi L (2015) Analysis on the establishment of the psychological environment of the ship. Jiangsu Sci Technol Inf 17:79–80

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3. Yu K (2010) Study on the assessment of human-machine interface for bridge based on ergonomics. Harbin Engineering University, Harbin 4. Li Z (2014) Researches on experimentation with influence of cabin color on crew’s performance. Ship Eng 36(1):32–37 5. He Y (2009) Influences on SMS by behavior of chinese sailors and study on countermeasures. Wuhan University of Technology, Wuhan

Part VI

Research on the Machine-Environment Relationship

The Shock Resistance Research of Light Seamless Knitted Fabric Yuanyuan Wang, Zimin Jin and Yuanyuan Qi

Abstract This paper hopes to achieve protective clothing vulnerable parts of the body to research and development in shoulder, elbow pads and other protective functions and is suitable for thin summer impact seamless knitted clothing. In order to study the effect of different materials and organization on shock resistance and wearing properties of seamless knitted fabric, three factors were set up in the experimental plan: the veil, bottom yarn, and the weaving structure. By using the orthogonal method, the sample experiments were determined and a total of 25 piece of sample fabric was weaved. Then, test shock resistance and wearing properties of each sample make orthogonal analysis of each sample data and draw conclusions. Keywords Sports injuries

 Impact resistance  Orthogonal experiment

1 Introduction In recent years, the sports for all people in our country are continuously prosperous. Fitness exercise is a way to enhance physical fitness and promote physical and mental health of a way, but exercise inappropriate, it will bring sports injuries. Body protective articles began their career in the 1980s and are mainly used by athletes who regularly practice professional sports. Sports protective equipment design should pay attention to the combination with the effective exercise and thermal comfort requirements [1], and the development of impact-resistant sportswear in the new situation requires both impact resistance, but also to ensure good flexibility and breathable moisture. Sex is moving toward the thin, comfortable, and flexible development trend [2].

Y. Wang  Z. Jin (&)  Y. Qi College of Materials and Textiles, Zhejiang Sci-Tech University, Hangzhou 310018, China e-mail: [email protected] Y. Wang e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_53

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Seamless knit fabric is an all-formed fabric designed according to the curve of the human body. From yarn to garments, it achieves very few cutting and stitching. This uniqueness without side seams makes these products to have no pressure on the human body; meanwhile, also this has a high elastic body, moisture absorption, soft and comfortable features [3]. This thesis hopes to achieve the purpose of anti-impact garment through the seamless technology.

2 Establishment of Light Seamless Knitted Fabric Sample Plan In order to study the impact of different raw materials and tissues on the impact resistance and serviceability of seamless knitted fabrics, the paper first determines the level of factors, using orthogonal test to determine the sample of fabric samples, combined with seamless production process, onboard trial on the seamless circular knitting machine. If you conduct a comprehensive experiment, the sample size is too large, time-consuming, and labor-intensive. Therefore, the orthogonal scheme is used for multi-factor experimental design, the method is selected from a number of experiments a few representatives of a small number of samples to carry out the experiment, the experimental results of these data orthogonal analysis, the best Program [4, 5]. The experiment is arranged according to the orthogonal experiment scheme, and the specific experimental scheme specifications are shown in Table 1. Table 1 Each experimental sample program specifications’ table Sample

A—Veil material

B—Bottom yarn material

C—Weaving structure

#1

70D/48F DY Nylon

15D Spandex/20D Nylon Wrap Yarn

Weft flat needle

#2

70/48F DY Nylon

20D Spandex/20D Nylon Wrap Yarn

1 + 1 mockrib fabric

#3

70D/48F DY Nylon

40D Spandex/20D Nylon Wrap Yarn

3 + 1 mockrib fabric

#4

70D/48F DY Nylon

20D Spandex/30D Nylon Wrap Yarn

2  2 (mesh)

#5

70D/48F DY Nylon

20D Spandex/40D Nylon Wrap Yarn

3  3 (mesh)

#6

70D/48F trilobites Nylon

15D Spandex/20D Nylon Wrap Yarn

1 + 1 mockrib fabric

#7

70D/48F trilobites Nylon

20D Spandex/20D Nylon Wrap Yarn

3 + 1 mockrib fabric

#8

70D/48F trilobites Nylon

40D Spandex/20D Nylon Wrap Yarn

2  2 (mesh)

#9

70D/48F trilobites Nylon

20D Spandex/30D Nylon Wrap Yarn

3  3 (mesh)

#10

70D/48F trilobites Nylon

20D Spandex/40D Nylon Wrap Yarn

Weft flat needle

#11

70D/48F round hole Nylon

15D Spandex/20D Nylon Wrap Yarn

3 + 1 mockrib fabric

#12

70D/48F round hole Nylon

20D Spandex/20D Nylon Wrap Yarn

2  2 (mesh)

#13

70D/48F round hole Nylon

40D Spandex/20D Nylon Wrap Yarn

3  3 (mesh)

#14

70D/48F round hole Nylon

20D Spandex/30D Nylon Wrap Yarn

Weft flat needle

#15

70D/48F round hole Nylon

20D Spandex/40D Nylon Wrap Yarn

1 + 1 mockrib fabric

(continued)

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Table 1 (continued) #16

70D/48F trilobites Nylon

15D Spandex/20D Nylon Wrap Yarn

2  2(mesh)

#17

70D/48F trilobites Nylon

20D Spandex/20D Nylon Wrap Yarn

3  3(mesh)

#18

70D/48F trilobites Nylon

40D Spandex/20D Nylon Wrap Yarn

Weft flat needle

#19

70D/48F trilobites Nylon

20D Spandex/30D Nylon Wrap Yarn

1 + 1 mockrib fabric

#20

70D/48F trilobites Nylon

20D Spandex/40D Nylon Wrap Yarn

3 + 1 mockrib fabric

#21

70D/48F round hole Nylon

15D Spandex/20D Nylon Wrap Yarn

3  3 (mesh)

#22

70D/48F round hole Nylon

20D Spandex/20D Nylon Wrap Yarn

Weft flat needle

#23

70D/48F round hole Nylon

40D Spandex/20D Nylon Wrap Yarn

1 + 1 mockrib fabric

#24

70D/48F round hole Nylon

20D Spandex/30D Nylon Wrap Yarn

3 + 1 mockrib fabric

#25

70D/48F round hole Nylon

20D Spandex/40D Nylon Wrap Yarn

2  2 (mesh)

3 Impact Test of Light Seamless Knitted Fabric Shock resistance tests were carried out on 25 knitted seamless knitted fabric samples. The results are shown in Table 2. According to the test data of Table 2, the orthogonal analysis of the impact resistance is performed, as shown in Table 3. According to the value of K in each level in Table 3, the level of each factor and the impact resistance is plotted. The results are shown in Fig. 1.

Table 2 Fabric impact test data Sample name

Impact penetrates energy (kN)

Sample name

Impact penetrates energy (kN)

#1 #2 #3 #4 #5 #6 #7 #8 #9 #10 #11 #12 #13

110.14 56.93 45.52 105.6 98.95 49.62 49.13 95.97 95.28 87.41 48.63 97.54 97.25

#14 #15 #16 #17 #18 #19 #20 #21 #22 #23 #24 #25

112.45 45.74 111.74 108.9 111.72 50.3 42.53 105.02 112.68 50.71 44.09 89.77

460 Table 3 Shock resistance of the sample fabric orthogonal analysis table

Y. Wang et al. Factor

A

B

C

Mean white k1 Mean white k2 Mean white k3 Mean white k4 Mean white k5 Range R Optimal level

83.428 75.482 80.322

85.03 85.036 80.234 81.544 72.88 12.156 B5

106.88 50.66 45.98 100.124 101.08 60.9 C3

7.946 A2

Fig. 3.1 Shock resistance and the relationship between the levels of various factors

4 Shock Resistance Correlation Analysis of Seamless Knitted Fabric Bivariate Pearson correlation analysis of the measured fabric thickness, square weight, and impact resistance was carried out by using SPSS software, respectively, and whether the correlation existed was analyzed according to the significant data. If the significance (bilateral) value is 0.90 and over (good)

2.424 0.798 0.766 0.076

1.814 0.928 0.904 0.056

0.864 0.831 0.830

0.956 0.930 0.929

We use AMOS to load the sample data and analyze the goodness of fit. The result shows that the original model does not fit the data well. After several modifications, the revised model finally meets our requirements, and we call it the ideal model [5]; see Fig. 1. The results of the analyses on the goodness of fit of the original and ideal models are shown in Table 3.

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Table 4 Standardized total causal effect between the two groups of factors Factor

F1 (safety idea)

F2 (safety knowledge)

F3 (safety facility)

F4 (safety code)

F5 (safety rewards and punishments)

F6 (safety technology)

G1 (safety communication) G2 (manager safety performance) G3 (safety operations) G4 (leaders’ safety commitment) G5 (safety engagement of officials and soldiers)

0.666

0.142

0.000

0.000

0.483

0.000

0.191

0.041

0.000

0.897

0.691

0.000

0.243

0.077

0.282

0.783

0.803

0.104

0.239

0.000

0.000

0.000

0.900

0.000

0.316

0.190

0.000

0.218

0.872

0.000

3.2

Analysis on the Causal Relation Between the Two Groups of Factors

We load the sample data to estimate the parameters of the ideal model and get the causal effect coefficient between the two groups of factors. See Table 4.

3.3

Calculation of the Impact of Military Cultural Construction Factors on Safety Performance

According to Table 1, we calculate the weight of each safety performance factor using the following formula: Ri ai ¼ P5 j¼1

Rj

In the formula, ai is the weight of the ith factor, and Ri is the variance explained pf the ith factor (i = 1, 2, 3, 4, 5). After calculation, a1 = 0.300, a2 = 0.262, a3 = 0.203, a4 = 0.119, a5 = 0.116. The influence coefficient of F1 (safety idea) on safety performance is c1: c1 ¼

5 X i¼1

ai I1i

Analysis on the Effect of Safety Culture Construction Factors

541

In the formula, I1j is the causal effect coefficient between F1 and safety performance factors. See Table 3. After calculation, c1 = 0.363. Similarly, the respective influence of F2 (safety knowledge), F3 (safety facility), F4 (safety code), F5 (safety rewards and punishments), and F6 (safety technology) on safety performance can be calculated: c2 = 0.092, c3 = 0.057, c4 = 0.419, c5 = 0.697, c6 = 0.021.

4 Conclusion and Suggestions 4.1

Conclusion

(1) The effects of F1, F4, and F5 are 0.363, 0.419, and 0.677, respectively. These three factors have significant impacts on safety performance. Among them, F5 is the most effective factor and has the most significant impact on safety performance. (2) F2, F3, and F6 are less effective, and their impacts on safety performance are relatively weaker. (3) In regard to the influence of safety culture construction factors on safety performance factors, F1 significantly impacts on G1, F4 significantly impacts on G2, and F5 significantly impacts on G3, G4, and G5.

4.2

Suggestions

To strengthen the military safety culture construction and enhance the effect of safety work, armed forces should not only comprehensively reinforce the safety concept, safety system, safe facilities, and safety behaviors, but also highlight the key points to make the construction more targeted and effective. Specifically, forces should pay attention to the following four aspects: First, firmly establishing a scientific concept of safety—using the concept to guide officers and soldiers to behave safely and enhance their safety awareness; second, continuously improving the safety regulations—standardizing the behaviors of officers and soldiers through rules and regulations; third, improving the safety system—utilizing the system to highlight safety responsibilities and putting the safety work into practice; fourth, improving the safety knowledge, safety technologies, and safety facilities—overcoming the weaknesses to realize the overall rise in the effect of safety culture. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Artillery and Air Defense Forces Academy (Zhengzhou Campus).

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All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Wang A (2007) Safe development and accident prevention. Changzheng Publishing House, Beijing 2. Hou J (2004) Structural equation model and its application. Publishing House of Education Science, Beijing 3. Xue W (2008) SPSS and Its application. Publishing House of Electronics Industry, Beijing 4. Wu M (2010) SEM—operation and application of AMOS. Chongqing University Press, Chongqing 5. Wang X (2011) Theoretical and empirical study on quantitative measurement of safety culture. China University of Mining and Technology Press, Beijing

On Academic Evaluation Index System of Weaponry Subject Hai Chang, Bingjun Zhang, Zengjun Ji and Shuai Mu

Abstract Academic evaluation is one of the important steps in the weaponry subject conduct in the force professional academies, and it is one of the important means to test the level and quality of study of cadets. The author analyzes the problems which currently exist in the academic evaluation of weaponry subject. From the contents and function of the academic evaluation of weaponry subject, he adopts the evaluation concepts of evaluation content, evaluation subject, and evaluation means multiple dimensionalization. In the process, he adheres to the “integration” principle of combining process evaluation and end evaluation, study capability evaluation and innovation capability evaluation, qualification evaluation, and quantification evaluation. Considering the practice of weaponry subject conduct and the peculiarity of personnel education object, the author establishes the academic evaluation index system of weaponry subject, which is of great significance to forward the teaching reform, lift the class teaching quality, and promote personnel education quality. Keyword Weaponry subject evaluation

 Multiple  Dimensionalization  Academic

The weapon subject is one of the backbone subjects of military professional education for the cadets in force academies, which is one of the important ways to help the cadets to master skillfully the structure and principle of, use and maintain, and employ flexibly the weapons and equipment. In the education conduct, we must explore the weaponry subject conduct ways/methods suitable for military struggle preparedness demands and cadets’ features; reform the current academic test and evaluation methods; test comprehensively the cadets’ understanding and employment of the contents studied in multiple ways; strive to reflect roundly and objectively the cadets’ weaponry theory mastery and employment capability. Thus, H. Chang (&)  B. Zhang  Z. Ji  S. Mu CPLA Army Artillery and Air Defence Forces Academy, Zhengzhou Campus, Zhengzhou 450052, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_63

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we can improve fundamentally the current status of weaponry subject conduct, lift its pertinence, exert its functions to serve the practice, and guide the practice.

1 Problems Existed in Academic Evaluation At present, the academic evaluation of weaponry subject is solely conducted by the instructor in charge, with the class/home performance comprising 20% and the final examination achievement comprising 80%. The class/home performance is comprised of the study attitude, attendance, and homework evaluation while the final examination is conducted in the closed-book way to test the cadets’ theoretical knowledge. Such an evaluation is simple to operate and accurate to reflect the cadets’ memory and understanding of the contents studied. But, the evaluation is featured by a single subject, a stiff way, and a content biased to memorize knowledge; thus, it is difficult to evaluate the study process, excite the cadets’ activity, and creativity, result in the divorce of theory and practice in weaponry subject conduct.

2 Contents and Function of Academic Evaluation 2.1

Contents of Academic Evaluation

Academic evaluation is one of the important steps in academic education, one of the important means to test the level and quality of cadets’ study, and one of the important ways to test whether the education object is achieved [1]. In according with the force academy personnel education scenario and the subject attribute/ education object, the academic evaluation of weaponry subject may be defined as a comprehensive evaluation process conducted to learn the cadets’ study, mastery, and employment of weapons and equipment, which is guided by the education purpose of weaponry subject, conducted in a proper and effective method and way in order to collect such information of the cadets’ knowledge and behavior in the process of weaponry subject.

2.2 2.2.1

Function of Academic Evaluation Function of Guidance

The index, standard, and requirement of academic evaluation is the important basis for the instructor to conduct teaching reform, establish teaching mode, design

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teaching process, and select teaching methods. They are also the important basis for the cadets to be guided to build a scientific study concept, establish study process, detect study problems, adjust study strategy, improve study ways/methods, and optimize study process.

2.2.2

Function of Excitation

Academic evaluation is one of the important ways for the instructor to design teaching creatively, construct interactive class, fulfill teaching tasks better, achieve teaching goals, and teaching objects. It is also one of the major means to excite the cadets’ desire and motivation of study, self-study and creative study [2].

2.2.3

Function of Promotion

Academic evaluation may facilitate both parties of education to learn and understand each other mutually, promote the instructor to detect teaching problems, perfect teaching process, improve teaching methods; facilitate the cadets’ to learning and understanding of teaching object and requirements, teaching strategy selection and teaching ways/methods, and to reflect study process and to explore study; facilitate to promote a better interactive between teaching and studying, between academic evaluation and teaching/studying conduct.

3 Construct “Multiple Dimensionalization/Integration” Principle of Academic Evaluation System for Weaponry Subject 3.1 3.1.1

Adhere to Multiple Dimensionalization Evaluation Multiple Dimensionalization of Evaluation Contents

Considering multiple loops in the teaching process of weaponry subject conduct, and multiple facets in the studying process, such as study attitude, attendance, discipline, class interaction, theoretical knowledge level, theory employment capability, practice capability, conduct a multiple-dimensional evaluation of the study attitude, study process, study capability, study qualification and effect, and practice capability.

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Multiple Dimensionalization of Evaluation Subject

The instructor is the subject of the teaching conduct, the provider of the teaching contents, the designer/executor/manager of the class teaching process and step, whose guidance function in academic evaluation must be exerted; the cadets are the subject of the studying conduct, who have the most direct knowledge and comparison of their own and their classmates’ study attitude, study behavior, study efficiency, and thus, whose subject role in academic evaluation need be determined [3]. Therefore, there are multiple-dimensional subjects existed in academic evaluation, which help to prevent and overcome the tendentiousness and one-sidedness of academic evaluation due to single evaluation subject.

3.1.3

Multiple Dimensionalization of Evaluation Way

Academic evaluation of weaponry subject must guarantee the unification of evaluation contents, standard, and requirements, and at the same time, respect the difference between individual cadets. Based on the difference of interest, capability and specialty, etc. Between individual cadets, we must set multiple-dimensional test items and stipulate corresponding evaluation standard and requirements, and conduct evaluation in such ways as written test, live-equipment operation, oral test, innovation practice, with self-evaluation and other evaluation, qualification evaluation, and quantification evaluation.

3.2 3.2.1

Adhere to Integration Evaluation Adhere to Integration of Process Evaluation and End Evaluation

Evaluate the cadets’ theory level with the end close-book written examination, and at the same time, set the steps of the teaching process into corresponding evaluation items, put them into the evaluation system with a given weight, pay attention to such study processes as cadets’ class study, thinking training, innovation practice activity; in order to make cadets transform their study concept, correct their study attitude, change their “no earnestness” study habit, promote their initiative, participation, efficiency and quality of study, exert the function of guidance of academic evaluation.

3.2.2

Adhere to Integration of Study Capability Evaluation and Innovation Capability Evaluation

Consider study capability and innovative thinking capability in the evaluation system; that is, pay attention to the cadets’ capability to raise/explore/resolve

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problems as well as their capability of digesting and absorbing theoretical knowledge. Encourage cadets to testify the theories, lift the level of perceptual knowledge, reflect the process of theory study, deepen the theoretical knowledge, promote the level of theoretical thinking and theoretical study, and exert the function of guidance of academic evaluation.

3.2.3

Adhere to Integration of Qualification Evaluation and Quantification Evaluation

Evaluate all the items of the cadets’ study process with varied ways; that is, evaluate quantitatively the level of mastering and employing weapon theoretical knowledge, as well as the feeling, attitude, value, sense of cooperation, creativity, etc. manifested the in study process [4]. Consideration must also be given to the facts and value, unity, and development of subject in the process of academic evaluation, in order to make academic evaluation more scientific, which may satisfy the actual situation of cadets’ study, help cadets to realize the problems and shortcomings in their study, improve the way of study, lift the quality of study, facilitate the development of cadets, exert the function of excitation, and promotion of academic evaluation.

4 “Multiple Dimensionalization/Integration” Index System of Weaponry Subject Academic Evaluation Considering the actual situation of weaponry subject, in accordance with the subject goal, propose all evaluation indexes of academic evaluation, define the detailed contents/evaluation standard/evaluation subject of all evaluation indexes; in accordance with the effect that each evaluation index may produce on the quality, effect and goal of weapon subject, determine the weight of all indexes in the evaluation system. Full consideration must be given to the feasibility of the actual operation process; we suggest four (04) level-I indexes (study process, theoretical knowledge, practice process, practice achievement), eight (08) level-II indexes (study attitude, attendance, class interaction, homework, level of theoretical knowledge and capability of employing theoretical knowledge, communication capability and cooperation level, practice capability, practice achievement) [5] for the academic evaluation of weapon subject, and determine the evaluation subject and the index weight of each index, as shown in Table 1 where class interaction refers to the cadets’ process and status to participate in study, trying to test the class discipline, note taking, question answering, class discussion; level of theoretical knowledge refers to the close-booked examination at the end of a term, trying to test a cadet’s level of the theoretical knowledge of weaponry; communication capability and

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Table 1 Index and weight of “multiple dimensionalization/integration” academic evaluation for weaponry subject Level-I index

Weight

Level-II index

Evaluation subject and weight

Study process

0.4

Study attitude

Instructor Cadet Instructor Cadet company Instructor Cadet Instructor Cadet Instructor

0.6 0.4 0.5 0.5

Instructor Cadet Instructor Cadet Instructor Assistant instructor

0.5 0.5 0.6 0.4 0.6 0.4

Attendance

Class interaction Homework Theoretical knowledge Practice process

0.4 0.1

Level of theoretical knowledge and employment capability Communication capability and cooperation level Practice capability

Practice achievement

0.1

Practice achievement

0.6 0.4 0.6 0.4 1

Weight

Total weight

0.3

0.12

0.1

0.04

0.3

0.12

0.3

0.12

1

0.40

0.5

0.05

0.5

0.05

1

0.10

cooperation level tries to test a cadet’s communication and cooperation with other members in the practice group; practice achievement refers to a cadet’s practice achievements when he participates in various innovative practice activities, such as practice summary reports, papers, practical invention. The evaluation index system calculates the academic achievements with the 100 scale, regarding 100 points as full mark, over 90 points as excellent, 89–80 points as good, 79–70 points as average, 69–60 points as pass, below 59 as fail. In the actual operation, the quantification evaluation is conducted to check the level-II indexes by the evaluation subjects, weighted by the evaluation subjects, scored and weighted again according to each level-II index and then multiplied by the total sequential weight and summed to score the total academic evaluation.

5 Conclusion Due to the peculiarity of the academic goal and academic contents of weaponry subject, we must base the academic evaluation on the theory of multiple intelligences, the revolutionary reform of study in the IT context, and the difference between the individual study subject; adhere to the multiple-dimensional evaluation

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concept, construct the “multiple dimensionalization/integration” comprehensive academic evaluation system for weaponry subject, which is of great significance to advance the teaching reform of weaponry subject in force academies, to lift continuously the schooling level and the personnel education qualification, to promote comprehensively the quality of subject conduct, to enhanceg the cadets’ capability of “competent to fight and fight to win”.

References 1. Lu X, Li W (2013) On goal, path and strategy of pattern transformation of graduate class academic evaluation. Educ Prof 4:175–177 2. Liu S (2011) Current status and reform strategy of academic evaluation in China’s colleges and universities. Sci Educ Mercury 10:10–12 3. Luo H (2008) On the theory of multiple intelligences-based evaluation of students in professional schools. Hebei Normal University, pp 17–31 4. Kou W, Xia L (2013) On innovation of evaluation pattern of professional education students’ capability and quality. Acad Armed Mil Police 6:48–49 5. Han Y, Han Y (2017) Analysis and prospect on China’s academic evaluation for vocational education. Vocat Educ Res 3:36–38

Analysis and Monitoring on Training Intensity of Single Unit Based on Oximeter RAD-57 Cheng Jin, Di Liu, Genhua Qi, Zhibing Pang, Haitao Zhao and Zhaofeng Luo

Abstract Objective Through experiments, we master method of utilizing Oximeter RAD-57 to scientifically monitor and deploy equipment training intensity of human beings and make contribution to the man–machine training. Method Collecting a large number of data and deploying contrastive analysis through experiments of single unit. Result By comparing the data, masters the training intensity and the relationship between the specific indicators. It provides a new method for fatigue monitoring of man–machine training. Conclusion The utilization of Oximeter RAD-57 can monitor and guide training intensity more scientifically, as well as allocating intensity more reasonably. Keywords Pulse

 Blood oxygen saturation  PI  Training intensity monitoring

1 Foreword The intensity of military training, also known as military training load, covers training in aspects of military stamina, technical ability, psychology, and intelligence in a broad sense [1]. Currently, our military is in a crucial period of military training transformation. In order to improve the information construction of our military, continuously improve the quality of military training, reduce the non-combat reduction caused by training, enhance the overall quality of individual in combat effectiveness, scientific supervision and regulation on military training intensity appears to be significantly crucial and urgent. Single unit operation mode, which takes accounts for the majority of time in general training, is very typical in military training. Work performance improvement is the ultimate goal of training; during this process of improvement, training intensity has become one of the most active factors [2]. On the basis of the scientific training intensity control, we can C. Jin (&)  D. Liu  G. Qi  Z. Pang  H. Zhao  Z. Luo CPLA, Army Artillery and Air Defence Forces Academy, Zhengzhou Campus, Zhengzhou 450052, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_64

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also increase training amount reasonably, so that the training intensity and training quantity can be organically combined, and the quantitative changes can be qualitatively changed [3]. The efficiency of man–machine combination will be improved so that training effect will be improved.

2 Three Types of Index Definitions Based on Oximeter RAD-57 Oximeter RAD-57 is developed and produced by the USA based on handheld oximeter of American aerospace science and technology, and it can authentically achieve its monitoring on arterial blood oxygen, effectively solve the drawbacks of the original method of weighted average of arterial and venous blood oxygen and become the international “gold standard” of blood oxygen parameters. The design which is specific to the circumstance of body motion interference and low perfusion makes the instrument still be accurately measured during one’s body movement. It can also monitor human body continuously, noninvasively in real time, which eliminates the invasive one’s issues of that the invasive one is poorly tolerated, and its repeatability can be easily affected. Objective evaluation of the effect of body movement and timely understanding of the state of the body is conducive to the scientific development and adjustment of training programs. Fast, real-time, noninvasive, on-site testing captures more of the key physiological states and physiological processes.

2.1

Pulse

Pulse is also known as arterial pulse, normal pulse, and heartbeat is consistent; the normal adult pulse is about 60–100 beats per minute. Under reasonable training intensity, one individual’s exercise load should be between 65 and 85% of one’s maximum heart rate. Calculation method should be as follows: Maximum Exercise Heart Rhythm = 220 − Age; Reasonable Exercise Load Heart Rate Upper Limit = Maximum Exercise Heart Rhythm * 85%; Reasonable Exercise Load Heart Rate Lower Limit = Maximum Exercise Heart Rhythm * 65%;

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Blood Oxygen Saturation

The circulatory system of human bodies is operated by the heart, lungs, blood vessels, and blood together. Oxygen and nutrient supply metabolism are achieved in human body through blood (red blood cells), if there is an error occurred in oxygen supply system, the body function capability will decrease, and if the circumstance is pessimistic, it will lead to functional failure of the tissues, organs, and even death. (The better the circulatory system of the body is, the stronger the body will function). Red blood cells are responsible for supply and metabolism oxygen and nutrient, to be more specific, hemoglobin, which accounts for 32% of the red blood cell component, is a tool of tissue metabolism. The number and quality of red blood cells determine the strength of the body function. Blood oxygen saturation reflects changes in respiratory function and arterial oxygenation, and calculation method should be as follows: Blood Oxygen Saturation = Oxygenated hemoglobin/(Oxygenated hemoglobin + Deoxyhemoglobin); Generally, blood oxygen saturation should at least be more than 94%, if not, it will be considered as oxygen deficiency.

2.3

Perfusion Index (PI)

The perfusion index (PI) reflects the situation of “limb pulsatile flow,” which is also known as blood perfusion ability. The larger the pulsating blood flow is, there will be more pulsating component, so that the greater PI value is. If the peripheral blood flow perfusion is more sufficient, capillary blood flow will be greater, so that there will be more oxygen in the muscles. If the amount of physical activity is extremely huge, cardiac output will not keep up with it, which will lead to the constriction of small blood vessels, so that the PI value will decrease. Normal range of PI is from 0.3 to 7, athletes’ ones can be as high as 20 or more.

3 Statistics and Analysis of Experimental Data 3.1

Test Subject

The subjects are 10 male operatives aged from 19 to 24 who are under good body condition.

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Experimental Method

Experimental equipment is a kind of shoulder-mounted barrel equipment, under the mode of single unit operation, and the operators need to carry the equipment on their shoulders, aim at the moving cursor, and press the shooting button. The equipment weighs about 33 lb, which is divided portable packing status and operation unfolded status. The method used in this experiment is as follows, under the condition of in place and 100 m maneuver states, respectively, switch the equipment from portable packing status to operation unfolded status, make three shots in a row to the moving cursor, and collect personal data through Oximeter RAD-57. One individual’s aiming and shooting result will be recorded by simulation equipment through the form of variance automatically, so that the smaller the results are the better.

3.3

Experimental Data

According to Table 1, the average pulse, blood oxygen saturation, and PI are 78.8, 98.7, 4.8, respectively (Table 2). According to Table 3, the average pulse, blood oxygen saturation, and PI are 93.3, 98.4, 4.7, respectively. According to Table 4, the average D-value of pulse, blood oxygen saturation, and PI are 14.6, −0.3, −0.1, respectively. According to Table 5, the average pulse, blood oxygen saturation, and PI are 133.8, 97.7, 3.5, respectively. According to Table 6, the average D-value of pulse, blood oxygen saturation, and PI are 55, −1, −1.3, respectively. From the comparison of the data obtained from the two training forms, with regard to the pulse, it shows an increasing upward trend, but is below the upper limit of exercise load heart rate, which proves that the strength of the training will not cause overloaded injuries to the human bodies. According to the lower limit value of exercise load heart rate, some specific individuals’ training amount can be increased appropriately. With regard to the blood oxygen saturation, it shows a slight downward trend, but the indicators are within the normal range, changes are slight and subtle, which proves that the index has little effect on training fatigue. With regard to PI, it shows that under the circumstances of in place aiming, changes of the index are slight. However, in the 100 m maneuver aiming case, the amount of the decreasing values increases, according to the characteristics of the indicator, given the fact that if the physical activity amount of the operator is so high which is beyond the keeping up speed of cardiac output, the training strength will leave so much pressure on the operator, the emergency situations may easily occur.

Date of birth

1991.1 1996.9 1996.12 1992.6 1996.6 1994.12 1992.7 1994.4 1993.3 1995.2

No.

1 2 3 4 5 6 7 8 9 10

170 173 177 175 173 177 168 173 173 175

Height

65.1 67.3 61.9 66.7 55.7 71.7 52.9 69.5 61.6 71.5

Weight

Table 1 Operator basic data collection

4.9 4.2 5.1 4.9 5.1 5.0 4.5 5.2 5.1 5.0

4.9 4.2 5.1 4.9 5.1 5.1 4.5 5.2 5.2 5.0

Vision 124/77 147/81 121/80 117/81 123/70 132/63 102/61 124/78 105/71 122/80

Blood pressure 4192 4416 4213 4230 4484 3757 3428 4429 3568 4891

Vital capacity 59 64 86 58 78 56 68 55 67 57

Stage index 14″23 14″80 14″53 14″13 13″30 13″29 14″20 14″78 16″30 13″31

Century sprint 80 80 75 76 78 68 80 96 80 75

Pulse 98 98 98 99 100 97 99 98 100 100

Blood oxygen saturation

7.5 7.0 5.5 2.4 2.8 7.4 4.0 4.7 3.0 3.7

PI

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Table 2 Experimental Experimental project

Initiation Temperature

Humidity

End Temperature

Humidity

In place 100 m maneuver

29.7 31.6

45.6 47.7

28.3 32.2

52.1 39.9

Table 3 Three index values (In place aiming) No.

Pulse

Blood oxygen saturation

PI

1 2 3 4 5 6 7 8 9 10

109 101 104 83 102 97 67 102 82 86

99 100 99 99 99 97 98 98 98 97

4.1 6.3 6.4 2.9 2.1 6.0 5.8 4.2 1.6 7.2

Table 4 Comparison (In place aiming) No.

Pulse D-value

Blood oxygen saturation D-value

PI D-value

Shooting results

1 2 3 4 5 6 7 8 9 10

29 21 29 7 24 29 −13 6 2 11

1 2 1 0 1 0 −1 0 −2 −3

−3.4 −0.7 0.9 0.5 −0.7 −1.4 1.8 −0.5 −1.4 3.5

55 44.5 6.5 29 94 75.7 118 21 93 7.3

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Table 5 Three index values (100 m maneuver aiming) No.

Pulse

Blood oxygen saturation

PI

1 2 3 4 5 6 7 8 9 10

136 141 134 131 127 142 121 135 124 147

96 96 98 98 100 97 98 97 99 98

4.7 3.9 4.3 1.6 2.2 4.9 4.4 2.2 1.5 5.3

Table 6 Comparison (100 m maneuver aiming) No.

Pulse D-value

Blood oxygen saturation D-value

PI D-value

Shooting results

1 2 3 4 5 6 7 8 9 10

56 61 59 55 49 74 41 39 44 72

−2 −2 0 −1 0 0 −1 −1 −1 −2

−2.8 −3.1 −1.2 −0.8 −0.6 −2.5 0.4 −2.5 −1.5 1.6

11.3 26 128.3 79 239 28.7 22.3 54.7 135.3 18.3

Finally, by using analysis of variance (ANOVA), we know that pulse and PI have a significant effect on the training intensity of the operator; on the contrary, blood oxygen saturation does not have significant effect on it.

4 Conclusion Changes in human biology during military training are regular, and different training intensities have different effect on human bodies [4]. Through this experiment, a large number of experimental data are collected, and through comparative analysis, we basically master the training intensity monitoring method based on Oximeter RAD-57, and quantify the training intensity, as well as being able to intuitively control the operator’s physical condition. Under the situation that the operators’ bodies are ensured to be in normal load conditions, we have a basis to

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control the training amount and reasonably distribute training intensity. We make sure that our training is effectively varied from individual to individual, so as to improve training effectiveness and quality. Through scientific control of training intensity during the training, it is possible to decrease non-combat downsizing and have a positive effect on the ultimate enhancement of military’s combat effectiveness [5]. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhengzhou Campus, CPLA Army Artillery, and Air Defence Forces Academy.All subjects who participated in the experiment were provided with and signed an informed consent form.All relevant ethical safeguards have been met with regard to subject protection. Provided relevant documents to the publisher.

References 1. Liang J (2010) Military training intensity of scientific regulation and control. J Mil Inst Phys Educ 2. Chen Y (2010) Analysis of exercise training intensity. Anhui Sports Sci Technol 3. Zhang H (2015) For track and field training intensity and training awareness. 100 forums 4. Liang J (2004) Special issue of intensive training of physiology and physiology. In: “Hunter” set of training articles, published by the General Staff Second Edition 5. Liang J (2009) Military training intensity of scientific regulation and control theory and methods. Military Science Press

Research on Field Rescue Based on Expedient Material Zhingbing Pang, Huawei Li, Mingming Sui, Kunyuan Hu, Zhaofeng Luo and Shuai Mu

Abstract The objective of this research is to explore the specific method of using expedient material to carry out field rescue under field environment, so as to facilitate the modular use of expedient material, to effectively reduce casualties caused by disability and to lay the foundation of saving the lives of the casualties in the most reasonable way. The research uses the methods of literature search, simulation operation, data analysis and analytical investigation of the special environment of war, and combined with the equipment and materials carried, puts forward innovative ideas. The results put forward the necessity of modularizing the expedient material in the field rescue and further expand the innovative application ideas that need to be studied. The application of this research approach that puts forward can be used to use expedient material to carry out quick and accurate self-help and mutual aid in the face of future battlefield or unexpected situations. It is of great significance to promptly save the lives of the wounded, reduce disability, decline the psychological trauma of the wounded, consolidate the will to fight, as well as for further treatment and rehabilitation of the wounded. Keywords Expedient material

 Field rescue  Applied research

1 Introduction Battlefield rescue refers to a series of rescues that decrease the casualties to the minimum due to timely rescue, exsanguination and bandaging of wounded combatants during actual combat and training [1]. In the future battlefield, because of the use of all kinds of information weapons, injury treatment tasks will become more difficult. In addition to the necessity of the battlefield medical staff with effective, proficiency basic war injury treatment technology, officers should also improve their ability to assist each other. Under field conditions, the medical staff Z. Pang (&)  H. Li  M. Sui  K. Hu  Z. Luo  S. Mu CPLA, Army Artillery and Air Defence Forces Academy, Zhengzhou Campus, Zhengzhou 450052, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_65

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cannot follow up the rescue in time due to the limited number of staff. For example, medical personnel will not be with the team so as to not affect the task of the combat unit, and the medical equipment can also be limited. In order not to affect the task, the medical staff must use expedient materials to promptly complete self-help and mutual aid. In other special circumstances, such as earthquakes, typhoons, mudslides and other natural disasters, a large amount of rescue equipment is required, and a large number of personnel will be waiting for the rescue, presenting a highly urgent situation. If the expedient material can be timely used in the rescue through modular modification, although in the future battlefield personnel injuries are inevitable, self-help and mutual aid must be strengthened, and rescue equipment must be promptly protected, medical rescue pressure will still be greatly reduced, the wounded, rescue equipment and battlefield environment will be fully used, people and equipment will also be integrated. Therefore, the paper puts forward the research approach of the application of the expedient material in wartime rescue in the field environment.

2 Significance of Research Human-machine-environment system engineering is an engineering science that utilizes the ideas and methods of engineering to reveal the rules of human-machine-environment interrelations and ensure the optimal combination of human-machine-environment system engineering [2]. Under the guidance of human-machine-environment system engineering theory, the characteristics of these three are fully combined and integrated, and the utilization rate of equipment therein has been greatly improved. Human-machine-environment system engineering theory provides a theoretical support for the innovative ideas of applying expedient material to war-injured patients under the field environment. At the same time, the innovative ideas and follow-up practices of this application also give to human-machine-environment systems engineering theory Provide a strong proof, the significance of the research is presented in the following six aspects.

2.1

The Need for War-Wounded Rescue in Modern Battlefield Environment

The ferocity and cruelty caused by the modern war might result in unimaginable psychological burden. Psychological killing on the battlefield becomes more and more obvious, making the modern war injury shows a trend of diversification. With the large-scale modern air strikes on the battlefield, it has become difficult to distinguish between the front and rear, as well as wartime and peacetime. Injured people and impacted region are further enlarged without non-fixed tendency, and

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the number of wounded in a short period increase rapidly, so this undoubtedly puts forward higher requirements to the organization and management of rescue task. And since the number of casualties increased dramatically, at the same time as the professional medical aid workers improve the efficiency of rescue, more effective rescue methods is to use all the available expedient material for self-help and mutual aid when the rescue staff and equipment cannot be put in place in time.

2.2

The Need for Squads to Perform Task Separately

In the military training life of the army, squads are often dispatched to perform tasks separately, such as reconnaissance squads, assault squads, vigilante squads, with lean personnel, simple task, as well as life and medical self-protection equipment. Therefore, in the event of personal injury or even life-threatening situation, they must save ourselves. As a result, taking advantage of all available facilities for quick and prompt battlefield rescue is of great significance to save the wounded, reducing disability, regaining combat power, consolidating the will to fight and further treating and rehabilitating the injured.

2.3

The Need to Deal with Unexpected Injuries in Everyday Life

Accidental injuries occur when people are unprepared; in exceptional circumstances, such as earthquakes, typhoons, mudslides and car accidents, accidental injuries may occur without medical personnel on site or far from the city; when the medical equipment is not sufficient, the means of self-help and mutual aid on the expedient material can be used to protect their own lives or save others in time. For example, although the rescue of Wenchuan Earthquake in 2008 was launched in time, in the face of such a huge disaster area and numerous wounded people, there were still many people whose injury was exacerbated because of the inability to receive assistance in time, and some were amputated and even lost their precious lives. So in special circumstances, when faced with the accidental injury, the timely use of expedient material can not only prevent the deterioration of injury but also reduce the pressure on rescue workers.

2.4

The Need to Avoid Secondary Harm in War

The brutality and intensiveness of the information war are unmatched by any previous war. In the process of rescuing the injuries, the time–effect relationship is

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fairly obvious. If rescue measures are taken at a certain time, the treatment effect is obvious, and if the treatment opportunity is lost, the treatment effect is obviously decreased or even lives might be lost [3]. Seventy per cent of death on the battlefield was due to “second death” caused by late battlefield rescue (excessive bleeding, wound infections, respiratory dysfunction, asphyxia, shock, water and electrolyte imbalances, etc.). This fully shows that if there are advanced medical technology and proper rescue methods on the battlefield, more attention is paid to the most precious “golden time” of the 60 min after the trauma, the principle of “seamless education” is emphasized, the implementation of basic life support is ensured within 10 min, the wounded is sent to the designated medical institution within 1 h, and the death toll will be greatly reduced. With the continuous advancement and reform of the world’s military pattern, the injury caused by high-tech weapons is more complicated and the treatment is more difficult. The future war-wounded treatment will be characterized by immediate medical treatment and rapid evacuation [4].

2.5

The Need to Improve the Overall Combat Effectiveness of the Armed Forces

At present, the army demands that “to firmly establish the sole criterion of combat effectiveness”, actual combat training should be conducted and combat effectiveness should be built. Soldiers should learn from the training ground at first, then conduct exercises in the exercise ground and finally carry out real-life combat operations in the future battlefield. From the training field to the future battlefield, treatment personnel, treatment environment and mental state during rescue change greatly, which will inevitably lead to late follow-up of medical staff, or separate performance of the task force. If there are no any good self-aid and mutual aid equipment, irreparable trauma might occur to the wounded both psychologically and physically. Therefore, the application of the equipment will provide strong support to effectively and comprehensively enhance the combat effectiveness of the armed forces.

2.6

Effective Use of Materials and Equipment Carried by Soldiers

During the World War I, about 10 million people died on the battlefield and more than 20 million people were wounded. During World War II, a total of about 50 million people died as a result of the war in all the belligerent countries, with the number of casualties far exceeding that of World War I. This fully shows that the weapons of modern warfare increasingly advanced and the lethality increased. It is

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even more important to vigorously carry out self-help and mutual aid on the battlefield. The previous experience of revolutionary wars has shown that about 50% of casualties in wartime are rescued by themselves or others beside them, and that there is ample equipment available to each soldier for use, such as belts, strings, food bag, kettle straps, grenade bags straps, gun straps, shoelaces, wooden stools, campstools. All of the above materials can be used to fix the fracture.

3 Application Approaches For battlefield rescue in the field environment, we must improve the dynamic integration of the man-machine-environment system so as to fully improve the battlefield rescue capabilities. Three basic principles should be followed: first, scientifically determine the handling order; second, take the initiative to protect the wounded; third, combine standard and expedient materials. Means for transporting the wounded is the key to timely treatment of war injuries. At present, mainly means for transporting the wounded are stretcher, suspenders and skateboards. Among them, the stretcher is the most significant tool for transporting the wounded. The stretcher is convenient, quick and effective to rescue the sick and wounded. It can effectively protect the wounded against secondary damage in the transit process, and to add combat effectiveness for the troops in time, to ensure continued combat and to complete the task timely [5]. Some modular structures, whose length and width can be adjusted according to the height, weight and other parameters of the injuries, can be combined into a stretcher to facilitate the transport of the injured and into a fixed deck to prevent fractures of the second injury. The followings are some specific analysis of applied research of the most common daily life campstool.

3.1

Combined Plywood

Fracture first aid is to use the most simple and effective method to save lives, protect the limbs and promptly transfer them for proper treatment as soon as possible in order to prevent fractures from injuries in surrounding tissues, blood vessels, nerves and so on during the transport process and to reduce the activities of fractures, so as to reduce patient’s suffering [6]. In case of fracture, we can break down all parts of the campstool, use different parts of the fracture as the combined plywood according to the location and extent of the patient’s fracture and tie with the rope of the campstool. It is also important to protect the fracture end from resulting in more damage to soft tissue, blood vessels, nerves or internal organs. Fixing fracture also has an analgesic effect, can prevent shock and ensure the combat effectiveness of the unit to be replenished promptly.

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Combined Stretchers

Stretcher is the most effective wounded-carrying equipment. Transforming the campstool into rescue stretcher by releasing the legs of several campstool, relaxing the rope according to the injury body appropriate, docking several campstools with each other as a whole, fixing through rivets and making the rope bear stress sufficiently without allowing other parts of the stretcher contacting directly with the wounded, can effectively relieve the pain of the wounded. In addition, using another two pairs of seat belts to prevent the casualty from falling down the stretcher is favourable for the troops to ensure the safety of the wounded when transporting them during war operations in complex terrain, to effectively ease the injury of the wounded, to have them treated in time and to guarantee the transport security, so as to reduce disability and mortality.

3.3

Combined Beds

When the casualties do not need to be transported or the ground conditions are rather harsh, the stretchers can be opened and placed on the ground to form a camp bed to facilitate the patient’s rest, so as to ensure that the wounded people can resume their combat effectiveness promptly and continue to carry out their tasks.

4 Conclusion The battlefield rescue of information warfare has put forward a new research topic on the concept of “wounding”. Battlefield rescue technology mainly based on surgery is challenged. Battlefield rescue technology is turning to a new model of combination of internal medicine and psychological treatment technology to adapt to modern war injury treatment. In modern warfare, psychological disorders account for about 20–30% of the total casualties. Active use of expedient material to implement ward aid can effectively alleviate the psychological pressure of the wounded in order to assure that the injured wounded can be promptly restored. Combining with field surgery, it is necessary to analyse the innovative ideas from diverse situations to meet the needs of actual combat. Under the guidance of man-machine-environment system engineering theory, it is important to fully combine the characteristics of people, equipment and environment dynamically and give full play to the maximum utilization of equipment. Because of the universality, portability and rapid functional conversion of the expedient material, it is of great significance to improve the speed and effectiveness of the battlefield rescue.

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References 1. Shen X, Yang L (2017) Practice and experience in strengthening field ambulance training. Military health department of Public Security Frontier Sergeant School 2. Pang Z (2017) Research on the shelter of man-machine-environment in the field. Air Defense Artillery Academy 3. Cheng H, Chen W (2006) Analysis of the time-effect relationship of war injuries treatment. Armed Police Medical College Department of Health and Education 4. Guo X (2012) Research progress of battle stretcher transport stretcher. People’s Liberation Army 150 Hospital 6 5. Zhang G (2009) First aid and nursing knowledge. Jindun Publishing House 6. Mao Y, Li Q, Zhu B (2000) Classification of psychological war kill under high-tech conditions. People’s Military Medical

Research on the Training of Air Observation Post Operator Haitao Zhao, Genhua Qi, Zhibing Pang, Cheng Jin, Honglei Li and Hongyan Ou

Abstract The observation post is an important part of the reconnaissance and an early warning network. It plays an important role in making up the low altitude area of radar reconnaissance. This paper expounds the importance and necessity of the observation post for the reconnaissance and an early warning network, and analyzes the existing problems in the present stage from the aspects of equipment, operator, and survivability. According to the current situation, it analyzed the requirements of observation posts on human from the perspective of operators. Finally, it is also suggested that we should carry out scientific and efficient training from four aspects of operation selection, theoretical training, extreme condition training (Kong et al. in J Mil Phys Educ Sports, 2017 [1]), and diversified training. Keywords Observation post

 Training

1 Importance of Air Observation Post The air defense operations, the first stage, are an early warning. Without the guarantee of it, the air defense operations cannot be carried out smoothly. With the development and renewal of the reconnaissance and early warning equipment, the performance of the early warning radar is increasing, which greatly improves the efficiency of the reconnaissance and an early warning. But this also causes the commander’s reliance on an early warning radar. Once the radar equipment has a problem or the performance is hindered, it will have a great impact on the whole reconnaissance and an early warning. In recent years, with the exercises process of the air defense forces, the importance of reconnaissance and early warning has been highlighting. At the same time, the effectiveness of early warning radar equipment placed in complex terrain H. Zhao (&)  G. Qi  Z. Pang  C. Jin  H. Li  H. Ou CPLA Army Artillery and Air Defence Forces Academy, Zhengzhou Campus, Zhengzhou 450052, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_66

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has attracted attention. The effectiveness of the equipment is limited because the enemy is mostly using low altitude and ultra-low altitude penetration. The air observation post can effectively make up the blind area of radar detection in low altitude and ultra-low altitude. Because the equipment used for the air observation post is less affected by the terrain, it is usually used with the reconnaissance radar network. But there are also problems in the air observation post.

2 Problems in Air Observation Post Current 2.1

Low Functional Integration

At present, the observation equipment for the air observation post is mainly based on the manual optical equipment. Though there are post radar and acoustic reconnaissance equipment, there are a few equipment relatively, which is not enough to support the use of air defense observation posts for most air defense forces. At present, the air defense forces are fighting fast. Jamming and anti-jamming are accompanied by the whole combat. The equipment that is single function and inconveniences restricts the effect of the observation post.

2.2

Reconnaissance Effectiveness Influenced by the Personnel Operational Ability Greatly

Because the equipment is single function and low automation, battlefield reconnaissance and surveillance basically depend on the personnel operation. Therefore, the personnel operation level has become a restriction on the function of observation posts directly. The personnel operation of skilled can find air targets at long distance. They rapidly complete the related tasks, the news report and provide valuable information for the rear. Instead, it will procrastinate time transfer time of information and even miss air target, thus causing serious consequences.

2.3

Poor Viability

The first task of the observation post is to find the air target. It is usually equipped with light weapons such as rifle, and its defense ability is poor. When encountering enemy ground, it has to be quickly retreated only; founding low altitude targets (such as helicopter), it has to give up the attack, even under favorable conditions. Although there are many problems with the air observation post, the decisive factor in the battle is man. The problem of equipment and weapons can be

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strengthened through time only, but the operation level of personnel is an efficient way to improve the effectiveness of air observation posts present. So, we must strengthen the operation ability training of operators.

3 Requirements of the Observation Post Operator At present, the equipment used by the reconnaissance inspector for the air observation post is the equipment of positioning and optical reconnaissance almost. There are three requirements for the operator.

3.1 3.1.1

Human Physiological Visual Basis Limit Discovery Ability [2]

There is a visual limit for human eyes. For observers, the ability is used to discover for human, and it is the ability to find objects with a different contrast. It is clear that the higher the contrast of the air targets to the background, the farther the distance is, the higher the probability of the target is found.

3.1.2

Limit Resolution Ability [2]

There are many objects in the air, but we have to find the target. When two spots on the space plane are close to each other, observers cannot distinguish them at a certain distance. At this point, the angle of two points relative to the human eye is the limit resolution.

3.1.3

Ability to Continue to Focus

The time for a person to concentrate is limited. Observers need to concentrate on a certain period of time in order to respond to the targets appearing in the field quickly, especially if they receive incoming targets in specific directions. More persistent attention is good for the observers to monitor the air for a long time and to identify the air targets timely.

3.1.4

Attention Scope [3]

Attention scope is the number of objects that a person can perceive or recognize at the same time, which indicates the scope of perception. At the same time, the wider

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the attention span, the more the object of perception. For observation posts, attention scope is of positive significance for observing multiple goals at the same time.

3.2

Expert in One Thing and Good at Many

Expert in one thing is to master the professional and technical performance, to meet the prescribed standards. Good at many is to learn and master the other two or more professional technologies which are closely related to the major. It is one of the effective measures to improve the combat effectiveness of troops. For observation operator, it is not only to master one professional skill but also to master all kinds of skills to carry out reconnaissance tasks, so as to ensure that we can accomplish tasks under extreme conditions.

3.3

Good Physical Quality

At present, the automation of weapons and equipment gradually increased. In general, the requirements for the physical fitness of the personnel have been reduced. Since the observation post is usually located in the area where the motorized equipment cannot be directly reached, for the observation post operators, the observation operators often need to carry weapons and equipment to the place. And after it is in place, it is necessary to complete the equipment deployment and camouflage quickly and complete the following tasks. It has a high requirement for the physical ability of the operator.

4 Scientific Training to Improve the Quality of the Operator The observation post seems to be simple, but it is the final line of the early warning. A group of well-trained and well-executed observation post operators can not only complete the task of reconnaissance and early warning network but also play an unexpected role when radar and other electronic weapons are jammed. Therefore, it is necessary to strengthen the comprehensive training for the operator of the observation posts. Training is carried out in the following four aspects.

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Operator Selection for Visual Ability

Operator selection is a basic work, which can greatly improve the training efficiency of observation post operators. Since operator uses optical equipment to complete their task, it is particularly important for the visual requirements.

4.1.1

Visual Acuity

Visual acuity reflects the limit discovery ability of human eyes. It is human’s own ability. It can only be adjusted within a certain range. Being the better visual acuity, the operator has an advantage in completing tasks. Usually, inspecting the visual acuity uses the corresponding visual acuity chart, such as the international standard visual acuity chart, ring-shaped eyesight table, and the log acuity chart.

4.1.2

Duration of Concentration

When the operator concentrates, it will improve the accuracy of the operation and reduce the error of the operation. It is necessary to check the duration of the attention of the operator. Detecting the duration of attention usually makes the operator focus on a certain job while judging operational errors. As time goes on, operator’s attentional decline will lead people to make errors, and the number of the errors is increased. This process can detect the duration of a person’s concentration of attention.

4.1.3

Time for Visual Resolution [4]

For seeing a target and forming a visual image, it takes a certain amount of observation time. The length of the time is related to the brightness of the target itself; the brighter the target, the shorter the time. On the contrary, for the objects with low brightness, it needs more time to observe the target. In the task for the observation post, most of the targets are close, even lower for the bright background of the sky. The shorter the visual resolution of a person is, the more beneficial it is to the discovery of the target.

4.2

Theoretical Training

Theoretical training is the main method to improve the basic theoretical quality of the observation post operator. In the process of placing the post, commander only places the post and operator at a certain range within the region by far view or

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topographic map. But the specific location in the range is judged by the operator. In this process, choosing the right place is crucial to better completion of the observation task. Therefore, the corresponding theoretical training of operators, who has better local judgment ability, is an important task for the better. Theoretical training should be used in a flexible manner, instead of the traditional classroom instruction. With the operators having the basic quality, the training can be the way of questioning and discussion in order to enhance the ability of operators who use the basic principles flexibly and make the operators dispose of situation in practice accurately and flexibly.

4.3

Training Under the Limit Condition

Under the current training mode, operator can quickly achieve the standards of their equipment. But the actual combat environment is complex and changeable. The task of operator is more complex and arduous. Therefore, in normal training, a variety of complex conditions should be set up in order to reach the standard of extreme training. It is mainly for operator training and includes three levels [5]: The first is the basic physical capacity. It is the basis for military operations. In regular training, the operator should be able to complete the corresponding physical standards. The second is the operating skill under the extreme physical conditions. It is the basis for the completion of military operations. In the condition of extreme physical conditions, the body control ability of the human to the limbs will decrease significantly. It will lead to a sharp decline in skill level and reduce the efficiency of the completion of the task. When the physical and technical skills of the operators reach a relatively stable level, it needs to be an integrated training with the physical and technical skills. First of all, the operators should consume a large amount of physical energy, then do the skilled task, and test the level of the operators in this state. Though repeating practice, it is good for the operators to master the operating method which is fit for himself under the limited physical condition, and for improving the stability of the equipment operation. The third is the thinking judgment ability of the skill operation under the limited physical condition, which is the basis for the good completion of the military operation. Although a lot of resources are needed to improve the intelligence level of operators, it can produce more benefits and even get great effects. Therefore, in the training process, it should simulate the corresponding battlefield environment and enable the operators to judge and deal with the situation under the extreme conditions, so that they can adapt to the high-intensity operation environment and provide an intelligent guarantee for the best effect.

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Improve the Comprehensive Ability of Specialty by Diversified Training

The observation post has not only observation equipment, but also communication equipment, positioning equipment, and other types of equipment. Through the related exercises in recent years, it is found that the operators of each observation post are relatively inadequate for completing the task of observing low-altitude airspace. Therefore, this requires the operators not only to confine to a single professional or similar professional but also to achieve “expert in one thing and good at many.” Each post in accordance with the configuration requirements, the operators can use all the equipment. In doing so, one is able to reduce the difficulty of assignment of observation posts; the two is to increase professional redundancy and enhance reliability; the three is to reduce the probability of detection and improve viability.

References 1. Kong F, Sun Z, Kong W (2017) Enlightenment of “Hell Week” extreme training—take the PAP falcon commando as an example. J Mil Phys Educ Sports 2. Li S, Nie J, Li H (2010) Effectiveness analysis on eyeballing optical reconnaissance under a typical atmospheric condition. Infrared Laser Eng 3. Guo Q, Zhang Y, Tong Y (2015) The study of influencing factors of the attention span of the military flying personnel. Med J Air Force 4. Wen L, Zhao A, Wei X, Wu C, Li H (2009) The relationship between the time threshold of visual acuity and visual acuity. Prog Mod Biomed 5. He Z, Pang Z, Yang R (2010) Study of the performance evaluation of “incorporate human physical-performance, craftsmanship and brainpower” feasibility in military training. In: Proceeding of the 10th conference on man-machine-environment system engineering

Application of Crisis Intervention After Aircraft Mishap Qingfeng Liu, Xiaochao Guo, Fei Peng, Wanli Lou, Duanqin Xiong, Lei Yang, Yu Bai and Yanyan Wang

Abstract Objective To study the critical incident stress reactions of aircraft mishap and the application of an intervention program in order to reduce the negative psychological impact and promote recovery. Methods The design is case–control study based on general practitioners’ medical records. A crisis intervention program was developed to cope with stress of aircraft mishap and applied after an accident. The crisis impact was measured by interview; data review and intervention effectiveness were analyzed. Results The most popular symptoms within 72 h include worried, anxious, sleep problems, disturbed appetite. Heart rate, white blood cells count, and urine protein concentration of a survival pilot through ejection increased immediately following the accident though he claimed very mild discomfort. CISM intervention included 2 defusings for 50 people, 2 CISDs for 12 people, and 2 individual counselings for 2 people. Conclusion Stress reaction occurs after aircraft mishap, and intervention program should be activated as early as possible.



Keywords Aircraft mishap Crisis intervention agement Self-organizing system



 Critical incident stress man-

Q. Liu  Y. Wang (&) School of Biological Science and Medical Engineering, School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China e-mail: [email protected] Q. Liu  X. Guo  F. Peng  D. Xiong  L. Yang  Y. Bai  Y. Wang Institute of Aviation Medicine, PLAAF, Beijing 100142, China W. Lou Air Force Flight Test Bureau, Xi’an 710089, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_67

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1 Introduction Stress response occurs when a person faces a serious traumatic event or a perceived threat above one’s coping ability [1]. It is generally believed that this response can impact psychological and emotional functions, and then lead to maladjustment or low performance. These stress reactions are normal and adaptive in the extreme situation and occur in the healthy people. However, the unresolved stress reaction from an exceptionally stressful critical incident may prolong and lead to posttraumatic stress disorder (PTSD). So, stress should be mitigated and resolved as quickly as possible in order to prevent or reduce the development of posttraumatic stress reactions or disorders [2]. It is far easier to handle and resolve stress reactions than to cure PTSD. Aircraft mishap is a typical critical incident that may impact both physical and mental healths of unit members and the army’s morale [3]. In many countries, critical incident stress management (CISM) preventive services must be provided to unit and community members affected by aircraft mishap [4, 5]. In Cerritos air crash of August 1986 [6], the CISM interventions program benefited the rescuer stress recovery and utilization of critical incident stress debriefing (CISD) increased dramatically since then. Over the past decades, CISD has become the primary methods of reducing distress experienced by emergency service workers engaged in critical incidents. In this study, we have developed an CISM program for military critical incident and applied it in an aircraft mishap to test the effectiveness and practice.

2 Methods 2.1

CISM Program

2.1.1

Theory Basement

Crisis intervention and psychological education should be done after an aircraft accident. We developed an aircraft mishap crisis intervention program based on CISM and human body self-organization theory. CISM is a systematic and comprehensive approach to mitigate stress, which is a subset of crisis intervention field with a history almost over 50 years. It has been Air Force policy in many countries providing preventive services to unit facing potentially traumatic events or coping with stress after traumatic events. Human body self-organization theory developed by Yu [7] is a health medical model which aims for restoring overall health status. According to the theory, human body is described as a powerful self-organizing system based on the systemic theory, which presents the ability to move by itself toward the ordered structure. Self-organization means keeping physical and mental health status,

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adapting to new environments, and self-healing to illness. Stress reactions were divided into three classes referring to Seyle’s stress theory: physiological stress reaction, overload stress reaction and failure stress reaction. From a psychological point of view, critical incident stress reaction is overloaded stress reaction that goes beyond the self-organization and the intervention must be done to help for recovery of ordered structure. So, the psychological task of crisis intervention is to strengthen self-organization ability and prevent the possible failure stress reaction. The CISM program for aircraft mishap has the goal to: prepare the individuals for potentially critical events, help the affected people to cope with stress, and prevent the development of a posttraumatic stress disorder.

2.1.2

Contents of CISM

The program consists of six parts: pre-exposure preparation, immediately rescuer intervention, psychological measurement, CISD and defusing, individual counseling and follow-up or referral. Pre-exposure Preparation (PEP). PEP is a basic course aiming to teach aviation psychology and stress management. It emphasizes that feeling stress is normal feeling in abnormal situations. Effective and ineffective approaches were made clear. In each flying unit, everyone should receive the course. The course is conducted by the assigned aviation psychologist and the flight surgeon of the unit or other psychologist severed for the army. Immediately rescuer intervention. At least one of the rescuers, often the leader or the flight surgeon, must be qualified members psychological consultant or have received general intervention skills training. The rescuer must avoid the additional stress and trauma on the survivor. Emotion stabilization technology can be used during rescuing. Crisis Measurement. The affected people are classified into five levels according to the intensity of mishap and the involvement: a. The first level includes the experienced aircraft mishap closely, such as the survivor (aircrew), the seriously injured, the relative of the dead. b. The second level includes the individuals affected by the incident moderately, such as the other aircrew in the squadron, the maintenance group, the rescuers. c. The third level includes the individuals involved in the incident mildly, such as the other aircrew in the unit. d. The fourth level includes the other individuals in the unit. e. The special individual who has avoided the accident by chance may feel guilt. The psychological measurement include but not limited to interview, records review, observation, psychological test such as 90 Symptom Checklist (SCL-90), 16 Personality Factors Questionnaire (16PF), Simple Coping Style Questionnaire, Beck Anxious Inventory (BAI), Beck Depression Inventory (BDI), Posttraumatic Checklist (PCL), Flight Cognition Ability Test Battery, etc.

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Other data related to stress reaction also should be collected. CISD and defusing. They are group process intended to help prevent or mitigate long-term mental problems after the accident. In CISD, the participants talk about the accident led by a CISM-trained psychologist through a seven-step structure developed by Mitchell [8]. CISD is no longer a psychological therapy even though psychologist or medical providers are leading the team. It aims to let individuals understand the stress reactions and to identify the signs and symptoms. It also aims to promote effective and avoid ineffective coping styles. The first-level individuals, the second-level individuals, and the special individuals should receive CISD. Defusing is briefing for large groups of people after a critical incident. It aimed to explain the stress reactions and provide information against rumors. The third-level individuals should receive defusing, and the fourth-level individuals could attend defusing by themselves. Individual counseling. Psychologist should identify the individuals who need further counseling during overall intervention process including interview, psychological measurement, CISD and defusing. Individual counseling should be done to these individuals or others who seek counseling. Follow-up or referral. After the crisis intervention, assigned psychologist should advise the unit leaders and flight surgeons for necessity of further follow-up according to the intensity of acute stress reactions and the effectiveness of CISM program. If necessary, an advice should be given to flight surgeons for referral to neurological/psychiatric and/or psychotherapy. The flight surgeon decides the referral.

2.2

Aircraft Mishap

A fighter crashed during a two-plane formation maneuver in day training. The crashed aircraft was wingman, and the pilot survived after a successful ejection and was rescued after two and a half hours. There are no other ground damage and hurt. The weather condition was clear, and the pilot’s excessive manipulation may have caused the accident. The study was approved by the Logistics Department for Civilian Ethics Committee of Beihang University.

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3 Results 3.1

Crisis Measurement

People affected are classified. Class B aircraft mishaps with no ground injured have moderate affect to unit psychological state and morale. All the people are affected into five categories and only 1 people in the first level and 2 people in the second level (Table 1). The stress reaction intensity was measured by an interview with the health management officer in charge of the task, the unit commander, the flight surgeon. Records reviewed include heath records, result of psychological test done before and medical diagnosis data of the survived pilot, general data of accident. The stress reaction intensity is moderate. The morale is mildly affected. The most popular symptoms in the unit within 72 h include worried, anxious, sleep problems, disturbed appetite. No further psychological tests are recommended to all unit members. The pilot survived through ejection injured very mildly. He could recall the mishap, ejection and rescue process. The stress reactions are intensive though he claimed very mild discomfort impact. The most symptoms are: (a) high intensive nervous, too excited and hyper-alerted when he was rescued, sleep disturbed in the hospital, selective detailed statement of the mishap, the ejection and rescue process; (b) some avoidance symptoms and guilt for the leader and the aircraft; (c) physiological and psychological stress reactions are obvious. Heart rate, white blood cells count (WBC count), neutrophile granulocyte count (NG count), and urine protein concentration increased immediately after the accident and recovered within 48 h (Figs. 1, 2 and 3). Other biochemical indexes of blood and urine are normal. A rescuer developed symptoms such as fatigue, hyper-alert and sleeping disorder and asked for help initiatively. Table 1 Classification of people affected No.

Categories

Individuals

Amounts

Proposed intervention

1

First level

Survived pilot

1

2

Second level Third level Fourth level Special level

Flight surgeon, pilot in another plane Other pilots, maintenance group Other ground individuals

2

CISD, individual counseling CISD

None

0

3 4 5

Many Many

Defusing or CISD Psychological education by unit None

580 Fig. 1 Heart rate change following aircraft mishap (CI: critical incident, HR: heart rate)

Fig. 2 WBC count and NG count change following aircraft mishap (CI: critical incident, WBC: white blood cells, NG: neutrophile granulocyte)

Fig. 3 Urine protein concentration change following aircraft mishap (CI: critical incident, NP: urine protein)

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Crisis Intervention

CISM intervention includes 2 defusings for many people, 2 CISDs for 12 people, and 2 one-to-one individual counseling for 2 people. Emotion stabilization technology, normalization technology, and relaxation technology were used during intervention procession where needed.

4 Discussion Stress reactions have been widely accepted in medical and psychological fields since first coined by Hans Selye. Stress reactions where intensity depends on the intensity of stressor and psychophysical status of the individual generally occur on four levels, cognitive, emotional, physical, and behavioral. Though physiological and biomedical changes are an important evidence for stress, but most studies are done on animals or in experiment context and rarely done on human, especially pilots during serious accident. In this study, we have got the evidence and set up the stress–time curve. It is useful to study the regular pattern of stress reaction following critical incident. Taylor and Frazer [9] categorized the victims involved in an aircraft mishap into six types which are primary victims, secondary victims, tertiary victims, quaternary victims, quinternary victims, and sesternary victims. These categories included almost all people affected by an aircraft mishap. Figley and Kleber [10] simply classified the affected people into primary victims and secondary victims. Sheng and Liu [11] argued that three-level categories could be practical in crisis intervention after aircraft mishap and psychological education should cover all three types of people. However, we thought that five categories could be adaptive to military aircraft mishap crisis intervention. Primary people in each category also had been listed in program. Over the past decades, using CISD increased dramatically in disaster crisis intervention. CISM program was popular in aviation industry including military aviation. However, some researchers [12] argued that CISD just had a high degree of perceived satisfaction and lacked empirical evidence to support its effectiveness. In some cases, the participants could be hurt by CISD. Mitchell [13] argued that untrained practitioner caused the negative outcomes. CISD skill training is necessary and important. In practice, many evidences of effective crisis intervention are subjective and form case study. The effectiveness of our program is proved by symptoms mitigation and positive feedback from the participants and military leaders. Our findings and human body self-organization theory support the early intervention on crisis. The results of physiological and biochemical indexes show the stress reaction increased rapidly after the accident and peaked in 5–8 h. Self-organization ability may destroy almost when the accident occurred. The early

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intervention within 24 h, even 8 h after the accident, will help the self-organization ability recovery which may benefit the stress resistance. Despite a case study, evidences of stress reaction are clear. Stress reactions occur after aircraft mishap and the perceived stress extent may disagree with the physiological and biochemical indexes. The intervention program should be activated as early as possible following the critical incident. Although not all people affected were provided psychological service due to short time, the effectiveness of the CISM program is acceptable. Acknowledgements This work is supported by the Logistics Research project of PLA, No. CKJ14L015.

References 1. Auerbach S, Kilmann P (1997) Crisis intervention: a review of outcome research. Psychol Bull 84:1189–1217 2. Petrie S (2006) Early interventions after critical incidents-application. In: Human dimensions in military operations-military leaders’ strategies for addressing stress and psychological support. Meeting proceedings RTO-MP-HFM-134, paper 43. RTO, Neuilly-sur-Seine, France, pp 43-1–43-8 3. North Atlantic Treaty Organisation (2008) Stress and psychological support in modern military operations. Rato-TR-HFM-081, pp 1–372 4. HQ USAF/AFMOA (Col Schall D) (1999) Air force instruction 44-153, critical incident stress management, pp 1–28 5. Willkomm B (2006) Preparing the German air force for deployment-the stress concept of the general surgeon. In: Human dimensions in military operations-military leaders’ strategies for addressing stress and psychological support. Meeting proceedings RTO-MP-HFM-134, paper 36. RTO, Neuilly-sur-Seine, France, pp 36-1–36-4 6. Hokanson M, Wirth B (2000) The critical incident stress debriefing process for the Los Angeles county fire department: automatic and effective. Int J Emerg Ment Health 2(4): 249–257 7. Yu MS (2013) System life disease route. Med Philos 34(3A):1–5 (Chinese) 8. Mitchel JT (1983) When disaster strikes … the critical incident stress debriefing process. J Emerg Med Serv 8(1):36–39 9. Taylor AJW, Frazer AG Psychological sequelae of operation overdue following the DC10 aircrash in Antarctica. Victoria University of Wellington Publications in Psychology, No. 27 10. Figley CR, Kleber RJ (1981) Beyond the “victim”: secondary traumatic stress. In: Kleber RJ, Figley CR, Gersons BPR (eds) Beyond trauma. Plenum Press, New York 11. Sheng ZH, Liu QF, Sun MZ et al (2010) A case of crisis intervention after aircraft accident. Flight Surg 38(4):169–171 (Chinese) 12. Ostrow LS (1996) Critical incident stress management: is it worth it? J Emerg Med Serv 29–36 13. Mitchell JT, Everly GS (1997) The scientific evidence for critical incident stress management. J Emerg Med Serv 86–93

Missile Maintenance Management Using Data Flow Analysis and Discrete Event Simulation Fang Liu, Jinshi Xiao, Jun Huang, Qiang Zou and Haoting Liu

Abstract The data flow analysis and the discrete event simulation are utilized to assist the decision making of missile maintenance management. In contrast to the traditional qualitative methods, first the association and the similarity analyses are used to mine the inner relationship between the real-time data flow and the historical data flow. The Apriori algorithm and the Dynamic Time Warping (DTW) algorithm are utilized to help the user to detect the abnormity of the equipment maintenance data flow and evaluate the working performance of the project group. Second, the discrete event simulation technique is employed to model the process of stochastic event of the missile maintenance management. As a result, the user can understand, analyze, and monitor the event change state of the whole maintenance process. And the user can also decide how to allot the limited resource to different project groups scientifically. Some experimental results have proved the validity and effectiveness of proposed methods.



Keywords Intelligent decision Project management Similarity analysis Discrete event simulation



 Association analysis

F. Liu (&)  J. Xiao  J. Huang  Q. Zou College of Weaponry Engineering, Naval University of Engineering, Wuhan 430033, China e-mail: [email protected] H. Liu School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China H. Liu Beijing Engineering Research Center of Industrial Spectrum Imaging, Beijing 100083, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_68

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1 Introduction With the development of modern science and technology, the engineering project [1] has become more and more complex than ever before. Multiple flows coexist in one mission and many technique requirements are demanded in one management process. As a result, the scientific management and evaluation of the engineering project bring out a new challenge to system user. The user has to make decisions [2] from time to time to achieve the final target. The project scope management, the plan management, the cost management, and the quality management, all require the user to decide when, where, and how to solve a problem correctly and rapidly. Many methods have been proposed to solve the intelligent decision of project management. In [3], the authors used the Markov chain to solve the IT project management issue. In [4], a Bayesian network was employed to build the risk management decision support system. In [5], the authors extended the Bayesian networks to solve the soft project management of multi-criteria environment. After some researches, it can be found the current researches still omit an important fact: The data flows exist extensively in the engineering project, so the data flow analysis technique can be used to assist user to make decisions. In this paper, two techniques are used to assist user to make decision quantitatively. On the one hand, the association and the similarity analyses [6] are used to analyze the data flow. The Apriori algorithm [7] and the Dynamic Time Warping (DTW) method [8, 9] are employed to evaluate the cost flow in a missile maintenance management problem. On the other hand, the discrete event simulation [10] is utilized to model some events with stochastic factors of that task above. Different from the continuous simulation, the state variables of the discrete event simulation will change according to the probability model with the evolution of time.

2 Intelligent Decision-Based Project Management Method The diagram of the intelligent decision-based missile maintenance management method is shown in Fig. 1. The full life circle of this task can be divided into four phases: the concept phase, the programming phase, the implementation phase, and the ending phase. In the first phase, the user needs to analyze the maintenance needs and decompose the project into submissions. In the second phase, the user needs to set up the essential conditions for the submissions. In the third phase, the user has to implement all missions. In this phase, we propose to utilize the discrete event simulation technique to assist user to understand the mission and make decision. In the last phase, the user will finish the project. During the project, with the lapse of time, some data flow, such as the human cost or the whole cost of project, will change constantly. So the association and the similarity analyses can be used to evaluate the working performance of project groups and detect abnormity.

Missile Maintenance Management Using Data Flow Analysis …

Event 3

Event 2

Event 1

Event 4

Discrete event simulation of the project steps

Mission 1 startup

Project analysis

Mission 1 implementation

Mission N Project startup decompose

Plan change Project ending



Control & feedback …

Human cost

1

1 i N Ti



Total cost

Concept phase

585

Ti

Programming phase

Association analysis of the data flow Implementation Ending phase phase

Fig. 1 Diagram of the intelligent decision-based missile maintenance management method

3 Data Flow Analysis Method The association analysis [11] is to find the inner relationship between different data flows. For example, the relationship between the data flow of project cost and that of the employee work time can be built by that method. The classic association analysis algorithms include the Apriori algorithm and the FP-tree algorithm [12]. The Apriori algorithm extracts the frequent sets from the candidate sets by removing sets with support values which are less than the minimum support value. While the FP-tree algorithm uses the frequent pattern tree structure to mine the complete set of frequent patterns. In this paper, the association can be computed by these steps below (see Fig. 2): (1) The important points of series is calculated. (2) The vectors of the important points are quantized to get some codes. (3) The Apriori rule is used to find the association between different codes. In this paper, because the user needs to know the similarity level between the historical data and the real-time data, the similarity of the multiple data flow is analyzed here. Generally, the familiar similarity measurement techniques of data flow include the Euclidean distance and the Dynamic Time Warping (DTW) methods. The DTW method can search a dynamic programming which uses the flexibility in the sequence alignments. Because of this merit, its performance is better than that of the Euclidean method. The computation method of DTW is

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Original data

a

b j

c k

e

d l

m

n

abcdefgchia jklmnoepk

f

g c

o

e

h

i p

Association rule ???

Quantized a vectors k Apriori analysis

Fig. 2 Association analysis of the data flow using Apriori algorithm

shown by (1). The algorithm of the association and the similarity analyses is shown by Table 1. ffiffiffiffiffiffiffiffiffiffiffiffiffi1 0 v u K u 1 X A DTWðQ; CÞ ¼ [email protected] t wk K k¼1

ð1Þ

where the warping path w = {w1, w2, …, wk, …, wK} is a contiguous set of matrix elements Dnm which defines a mapping between Q and C; K is the number of set.

Table 1 Data flow analysis algorithm of the missile maintenance management

Algorithm: The data flow analysis technique Input: 2 set of data flow {y11, y12, …, y1k}, {y21, y22, …, y2k} Initialize: The corresponding parameter of the Apriori algorithm and DTW algorithm Do for: i = 1, 2, …, k 1. Calculating the important points of these series; 2. Creating the vector of the important points; 3. Quantizing the vector by their slope and creating the granule coding description of the data flow; End of for Utilizing the Apriori and DTW algorithms to find the association and similarity of the granule coding of the data flow; End Output: The result of association description like Fig. 2 and the computation result of formula (1)

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4 Discrete Event Simulation Method The discrete event simulation method is a powerful tool to understand the behavior of a project. This technique can be found in many applications such as the supply chain simulation [13] or the production development process modeling [14]. Since the modeling method of the discrete event simulation can describe the actual process, the difficulties of this method include the flow analysis of event and the probability estimation of the state variables. Regarding the first problem, the literature [15] presented a method which considered the object, the event, and the activity, to describe the event modeling problem. Regarding the second problem, the authors in [16] discussed the probability estimation problem of the event execution and proposed a probabilistic map of the output space to solve this problem. The general flowchart of the discrete event simulation from the decision maker point of view is shown in Fig. 3. For a complex engineering project, the decision process can be decomposed into different sub-decision missions, while each submission can be simulated by a simple discrete event simulation method.

Sequential Simulation Sub Mission i

Parallel Simulation

Sub Mission i+1

Mission Start Sub Mission n

Sub Mission j



Sub Mission k

Sub Mission m

Mission

Bayesian Network

Start Set Initialization

Invoke Initialization

Event Update

System Update

Random Variables N

Is simulation over? Y Result Output

Stop

Fig. 3 Discrete event simulation method for decision process of missile maintenance management

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From Fig. 3, among these submissions, the sequential style and the parallel style [17] can be found everywhere. The division of these styles is decided by the modeling complexity of the discrete event simulation. The Bayesian network can be used to select the proper decision result for the parallel style. When modeling the discrete event for a submission, the setting simulation clock and the generation of random number are needed.

5 Experiments and Discussions To show the validity of our proposed techniques, we use some engineering data sets of a missile maintenance project to test them. All the simulation models are implemented by c code on our PC (2.40 GHz, 2G RAM).

5.1

Application of the Data Flow Analysis Method

In this paper, the Apriori algorithm and the DTW algorithm are employed to analyze the correlations and the similarities of the cost data flow. The algorithm is assessed by the methods below: (1) The Apriori analysis results of the cost data flow between different project groups for the same mission are computed. By this means, the association patterns of these project groups can be found. As a result, the working efficiency and performance of different project groups can be deduced. (2) The DTW analysis results between the historical cost data and the current real-time cost data are calculated so that the abnormal situation of the real-time cost data set can be monitored. Figure 4 shows the association analysis results of some corresponding data. Fig. 4(a) shows an example of two cost data of a corresponding mission for different project groups, e.g., group A and group B; (b) shows the sketch map of the association patterns between the data set of group A and that of group B, respectively. From Fig. 4, it can be seen the cost data set of group A and group B have some common association patterns when the project groups process the same task. Thus, it can be deduced that each project group has some fixed strategies to solve problems. As a result, these association patterns can be regarded as an index to evaluate the performance of other project groups. The user can also learn how to organize a team with different project groups scientifically by theses analysis results. Figure 5 shows the DTW analysis results of some cost data set. In Fig. 5(a), (b) are the real-time and the standard historical cost data, respectively; (c) is the calculation result of the dynamic time warping routine of data set in (a) and (b). One of best characters of DTW is that it can be used to compare the similarity of data set even if their data length is different. However, its computational complexity is always high than many traditional methods. From Fig. 5, it can be seen that the

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(a)

(b) Association Pattern of Data I Association Pattern of Data II Fig. 4 Association analysis results of different project groups

data set (a) has a good similarity with data set (b) because most part of the shape of the dynamic time warping routine is close to a line. Thus, the user can use the DTW method to evaluate the abnormal situation of a project intuitively.

5.2

Application of Discrete Event Simulation Method

In this paper, since the complex project management task has been decomposed into many small simple tasks, only a single server queue model [10] is utilized here. The single server queue model supposes all the events are independent and identically distributed. This system uses the first-in and first-out manner to advance its simulation scheduling. In this paper, it is supposed that the probability distribution of the working efficiency of engineer satisfies the exponential distribution, while the arrival probability of event fulfills the Gaussian distribution. A missile maintenance task is utilized to build the discrete event model. So the decision strategy and the time arrangement method of the complex project can be simulated by this application case. After the application of proposed method, the decision error rate of user can be decreased more than 17%.

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Fig. 5 Similarity analysis result of different project data set for the missile maintenance management

6 Conclusion In this paper, the data flow analysis method and the discrete event simulation technique are utilized to solve the intelligent decision problem for the missile maintenance management. The Apriori algorithm, the Dynamic Time Warping method, and the discrete event simulation technique of single server queue model are utilized to assist the user to make decision. In the future, the data visualization technique and other artificial intelligence methods will be employed to solve the intelligent decision task in our research problems.

References 1. Reusch P, Khushnood M, Kaufmann SV (2011) Concepts on competences in project management. In: IDAACS, pp 884–889 2. Liberatore MJ, Pollack-Johnson B (2009) Quality, time, and cost tradeoffs in project management decision making. In: PICMET, pp 1323–1329 3. Shen HZ, Zhao JD, Qiu RG (2008) A group decision-support method for IT project management based on Markov chain. In: ICSMC, pp 862–866 4. He XC, Kang H (2010) A risk management decision support system for project management based on Bayesian network. In: ICIME, pp 308–312 5. Noothong T, Sutivong D (2006) Soft project management using decision networks. In: ISDA, pp 1124–1129

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6. Srivihok A, Mongkolsripattana S (2008) Association rule mining for project performance measurement of technology transfer centers in Thailand. In: DEST, pp 265–269 7. Pratt KB, Fink E (2002) Search for patterns in compressed time series. Int J Image Graph 2:89–106 8. Zhou JY, Yu KM (2008) Balanced tidset-based parallel FP-tree algorithm for the frequent pattern mining on grid system. In: SKG, pp 103–108 9. Niennattrakul V, Wanichsan D, Ratanamahatana CA (2009) Accurate subsequence matching on data stream under time warping distance. In: ECTICON, pp 752–755 10. Law AM, Kelton WD (2000) Simulation modeling and analysis, 3rd edn. McGraw-Hill Press, New York 11. Pan F et al (2008) Quantitative association analysis using tree hierarchies. In: ICDM, pp 971–976 12. Han JW, Pei J, Yin YW, Mao RY (2004) Mining frequent patterns without candidate generation: a frequent-pattern tree approach. Data Min Knowl Discov 8:53–87 13. Blanco EE, Xu Y, Gralla E, Godding G, Rodriguez E (2011) Using discrete-event simulation for evaluating nonlinear supply chain phenomena. In: WSC, pp 2255–2267 14. Li WL, Moon YB (2009) A simulation study of mutual influences of engineering change management process and new product development process. In: WSC, pp 2940–2950 15. Wagner G, Nicolae O, Werner J (2009) Extending discrete event simulation by adding an activity concept for business process modeling and simulation. In: WSC, pp 2951–2962 16. Leow-Sehwail YP, Ingalls RG (2010) Estimating the probability of an event execution in qualitative discrete event simulation. In: WSC, pp 1133–1144 17. Li CH, Park AJ, Schenfeld E (2011) Analytical performance modeling for null message-based parallel discrete event simulation. In: MASCOTS, pp 349–358

Key Chain Buffer Setting Method for Uncertainty of Project Duration Fenglin Zhang and Xingming Gao

Abstract Project duration uncertainty has become a problem of project progress analysis. In particular, the duration of some project processes is in a very large range. In order to solve this problem, this article measures the uncertainty coefficient of the process based on the entropy method and calculates the definite duration of the project process. Then, this article introduces the project risk coefficient red line, based on the relative risk coefficient to establish the key chain buffer and non-key chain buffer setting model, setting the project buffer to calculate its duration. Combined with the example and compared with the shear-paste method, it proves that this method is more scientific, reasonable, and effective. Keywords Progress analysis Uncertainty

 Entropy weight method  Buffer

1 Introduction Centering on the project schedule management, a lot of theories have emerged. PERT and CPM and CCPM are three typical methods that appear simultaneously in project schedule management. Many scholars conduct in-depth research on the duration of uncertain projects.

F. Zhang (&)  X. Gao College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Street, Nanjing, Jiangsu 211106, People’s Republic of China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_69

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2 Related Research Work Chen et al. [1] proposed the calculation of the size of the key chain buffer. Xu et al. [2] introduced the improved buffer settings based on the key chain into the buffer setting method. Peng et al. [3] proposed a key chain project scheduling method based on differential evolution to minimize the project duration and realize the scheduling optimization of key chain projects. Zhang and Li [4] objectively analyzed the advantages and disadvantages of the key chain method. Zhang et al. [5] introduced the idea of real option in the process of project buffer allocation. For the indefinite duration, this article sets the duration of each project as the interval number. This article aims to estimate the duration of uncertainties and estimates the uncertainty of each working procedure by entropy method. Based on this, the definite duration of the working procedure is calculated. Subsequently, this article introduces the project risk coefficient red line, based on the relative risk coefficient, established key chain buffer and non-key chain buffer setting model, set the project buffer to calculate its duration, making the result more accurate and practical.

3 Key Chain Buffer Setting Method for Uncertainty of Duration 3.1

Build the Initial Indicator Matrix

Under the premise of pre-designed evaluation rules, we set up the uncertainty data of n evaluation indexes in m steps to form the initial evaluation index data matrix: R ¼ ðrij Þmn

ði ¼ 1; 2; . . .; m; j ¼ 1; 2; . . .; nÞ

ð1Þ

rij is the i step of the j index of the evaluation data. We normalized it to get R ¼ ðpij Þmn , the normalized formula is: rij pij ¼ Pm

i¼1 rij

3.2

ð2Þ

Index Entropy Calculation

According to the evaluation data, we calculate the entropy of the j index in the evaluation system:

Key Chain Buffer Setting Method for Uncertainty …

hj ¼ k

m X

pij ln pij

i¼1

3.3

595

  1 k¼ ln m

Entropy of the j Indicator 1  hj P xj ¼ n  nj¼1 hj

0  xj  1;

n X

ð3Þ

! xj ¼ 1

ð4Þ

j¼1

Using the weighted average method, the Shannon value of a single process is calculated: Hi ¼ k

n X

pij ln pij xj

ð5Þ

j¼1

When the project activity time obeys logarithmic normal distribution, the Shannon value is: Hi ¼

 1 1  þ ln 2pr2 þ l 2 2

ð6Þ

Combined with Eq. (5), we can get the number of uncertainties in the project activity: n P 1 2

r ¼ ð2pÞ e

j¼1

kpij ln pij xj 12l

ð7Þ

  Let the project duration of each process is T ¼ tl ; tu , of which tl is the minimum duration, tu is the maximum duration of the project, the duration t is:   t ¼ tl þ r tu  tl

3.4

ð8Þ

The Key Chain Buffer Settings Based on the Uncertainty

For the setting of the project buffer, taking the risk factors into consideration, the project risk factor is combined with PB and FB. The buffer theory of many research projects is based on the average time of half the duration, and cutoff half of the durations and uncertainties of each process as a buffer and finally summed up the buffer of uncertainties in each process.

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  Qi ¼ Ti0  Ti  ri

ð9Þ

The key chain determines the duration of the entire project, having a decisive effect on the progress of the project. Therefore, the calculation of the key chain project buffer and the non-key chain import buffer must be treated differently. When the risk coefficient of the process duration reaches a certain critical value, it should attract the attention of project managers. Based on the risk red line, this paper calculates the relative coefficient of the risk of each process, and finally multiplies the coefficient by half of the cutoff period to calculate the project buffer under the condition of uncertainty. This article adopts the expert investigation method. According to the expert’s risk assessment of the key chain process and non-key chain process of the project, the red line of the risk of each process is finally weighted averagely. Recorded project risk coefficient of ri, the project risk red line of Ri, then the project process risk relative coefficient of Pi: Pi ¼

ri Ri

ð10Þ

In the key chain buffer management, the estimated duration is set at 50% of the probability to complete and treated it as the most likely completion time of the process, and the difference from the most pessimistic time is the safety time. When uncertain factors exist, the most pessimistic time depends on the probability of occurrence of uncertainties, and the impact factor is expressed as the relative risk coefficient Pi of the project process. Taking the product of safety time and risk relative coefficient as the buffer demand of each process, the size of the project buffer is equal to the sum of the buffer requirements of all the jobs in the key chain. The import buffer of the non-critical chain is equal to the sum of the buffer requirements of all the jobs in the key chain. Let the key chain project has m processes, and the duration of each process is ti, and the risk relative coefficient of each process is Pi, then the key chain of the project buffer Ti is: Ti ¼

m 1X ðti ð1 þ Pi ÞÞ 2 i¼1

ð11Þ

4 Case Analysis A company has gathered the advantages of modern construction resources, and initially occupied part of the construction market share. According to the statistics of the project department, only 20% of the large number of projects can be completed on time, and the trial production and renovation are successfully carried out. Many projects have delays in their implementation, so the company has focused on project progress management in recent years. Table 1 is based on Xing He Jiayuan

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Table 1 Xing He Jiayuan casting concrete pool project work list Work name

Code

Preceding activity

Back closely activity

Duration

1 2 3 4 5 6 7 8

A B C D E F G H

– A B A D C C, E F, G

B, D C F, G E G H H –

3–5 4–6 1–3 3–5 3–6 5–8 8–12 2–4

Table 2 Process uncertainty factor evaluation index value Code

Resource

Process

Demand

Environment

Technology

A B C D E F G H

0.9 0 0.60 1 0.43 0.32 0.32 0.90

0.13 1 0.34 0 0.44 0.34 0.28 0.32

0.62 0 0.43 0.12 0.43 0.14 0 0

0.55 0.42 0.52 0.48 0.41 0.40 0.45 0.40

0.32 0.80 0.32 0.08 0.42 0.42 0.30 0.43

2 cast-in-place concrete pool project as an example. We called the work name Construction preparation, Earth excavation, Cushion, Material preparation, Component processing, Warehouse preparation, Template reinforcement installation, Pour concrete as 1, 2, 3, 4, 5, 6, 7, 8.

4.1

Project Process Buffer Settings Based on Cut-Paste Method

For the indefinite duration of the process, we used the average as its definite duration and then combined with the shear-paste method to set the project process buffer. The key chain is: A–D–E–G–H. The duration of the project is 19 days. The project buffer is 6.5 days.

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Project Process Buffer Setting Based on Entropy Method

According to the degree of influence and occurrence probability, the indicators shown in Table 2 can be determined. Based on this, the evaluation matrix A, B, C, D, E, F, G, H is used as the evaluation object, and five uncertainty factors are used as evaluation indexes to establish and form the original data evaluation matrix X, as shown in Formula 11. 0

0:9 B 0 B B 0:60 B B 1 X¼B B 0:43 B B 0:32 B @ 0:32 0:90

0:13 1 0:34 0 0:44 0:34 0:28 0:32

0:62 0 0:43 0:12 0:43 0:14 0 0

0:55 0:42 0:52 0:48 0:41 0:40 0:45 0:40

1 0:32 0:80 C C 0:32 C C 0:08 C C 0:42 C C 0:42 C C 0:30 A 0:43

ð12Þ

We use the software MATLAB to compose the program of entropy weight method and run the program to get the coefficient of uncertainty of process activity, the results are shown in Table 3. We called the uncertainty coefficient as UC. The calculation shows that the key chain of the project is A–D–E–G–H, and the non-critical chains are A–B–C–F–H and A–B–C–G–H. Based on the expert judgment method, the project risk red line of the key chain is 0.5, while the project risk red line of the non-key chain is 0.6. By the Formulas (10) and (11), project duration is 17 days, and the project buffer is 6 days. The import buffer from process B–C to G is 1 day. The import buffer imported by F into H is 1.5 days. In the actual operation of the project, Xing He Jiayuan cast-in-place concrete pool project actually run 16.5 days, and the completion of the quality of the test is good. It completed the project with quality and quantity while shortening the construction period. This example shows that the project procedure buffer setting method based on the entropy method is better than the cut-and-paste project buffer setting method. Table 3 Process activity uncertainty coefficient Code

A

B

C

D

E

F

G

H

UC

0.252

0.192

0.284

0.21

0.287

0.316

0.265

0.247

Key Chain Buffer Setting Method for Uncertainty …

599

5 Conclusions This paper presents a new project uncertainty model. Due to the uncertainty of the project itself and the environment, the entropy method is used to evaluate the project risk and the project duration is determined. Then the project buffer and import buffer are set up based on the key chain method and the relative risk coefficient. Based on the existing key chain management methods, this paper provides a new solution to the problem. The project buffer is calculated based on the different uncertainties of the project. The example proves that this method is more scientific, reasonable and effective. The main problem of this paper is the selection of the uncertainty evaluation index of the duration of the project process. It also depends on the experience of the supervisors of project managers and experts. Therefore, how to choose a more suitable evaluation index system will be the next research direction.

References 1. Chen H, Zhe X, Jing Y (2015) Calculation of key chain buffer size based on duration distribution and multi-resource constraints. J Syst Admin 24(2):237–242 2. Xu X, Han W (2007) How to set up the key chain import buffer. Ind Eng Manag 05:51–55 3. Peng W, Jin M, Xu H (2013) Key chain project scheduling method based on differential evolution. J Syst Manag 22(06):855–860 4. Zhang J, Li R (2013) Review and comment on research review of key chain project scheduling methods. Control Decis 28(09):1281–1287 5. Zhang M, Chen R, Tang W (2009) Buffer pre-distribution model of key chain project under uncertainty returns. Ind Eng Manag 14(04):54–59

Flight Test Risk Mechanism with Man-Machine-Environment System of Civil Aircraft Yuanyuan Guo, Youchao Sun and Longbiao Li

Abstract The processes of flight test are compulsory for manufacturers and authorities to assess the airworthiness of civil aircraft. The test risk exists in all kinds of systems and parts. It is significant to identify test risk for safety. The process of test risk management has been established including identifying potential test risk modes, selecting crucial test risk modes, and listing major inspection projects. The deeper risk mechanism in each flight test project has been determined by analyzing multi-failures. The failure situations include: (1) the failures are independent of each other; (2) the catastrophic consequences are caused by independent failures; (3) the dependent failures are caused by others; (4) the dependent failures belong to common mode failures. The causal chain and common mode failure has analyzed failures reasons; the fault tree and events chain has obtained conditional probability of unacceptable consequence; the expanded fault tree and Markov method have improved risk accuracy. According to the airworthiness requirements, the acceptance of corresponding risk level from major inspection project can be determined to decrease test risk, comply with regulations of airworthiness. Keywords Civil aircraft ment Risk mechanism



 Airworthiness  Flight test  Man–machine–environ-

1 Introduction The purpose of flight test is to testify the aircraft’s operational safety. Many inspection projects will be checked by the flight test outline. It is significant to identify and assess test risk for the upcoming operational safety of civil aircraft. The international researchers have carried on relevant research in flight test guide and Y. Guo (&)  Y. Sun  L. Li College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_70

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risk assessment. Federal aviation administration issued many related advisory circulars including flight test guide [1], aircraft ice protection [2], performance and handling characteristics in icing conditions [3], and aeroelastic stability substantiation [4]; the regional risk assessment methods for engine parts have been jointly developed by the United States southwest research institute, Rolls-Royce, General Electric and Pratt and Whitney; Federal aviation administration issued “Safety risk management policy” (Order 8040.4A) [5] and “Transport aircraft risk assessment methodology handbook” [6] to analyze the details of different risk and assess the risk level for operational transport aircraft; subsequently, Violette et al. have established the risk assessment model for operational transport aircraft [7]; the authors in this paper have supported the failure risk assessment method of civil aircraft based on Monte Carlo method [8]. In this paper, the process of flight test risk management will be established in the terms of potential test risk modes, crucial test risk modes, and major inspection projects. The test risk mechanism will be analyzed into four-type failure situation by fault trees, causal chain, Markov method, etc. Compared with the airworthiness requirements, the risk degree during flight test will be determined in advance to decrease the loss of human and aircraft resources.

2 Process of Test Risk Management The process of risk management can be divided into four major sections, as follows (shown in Fig. 1).

3 Risk Identification During Flight Test 3.1

Man-Machine-Environment System in Risk Analysis

Man-machine-environment system of civil aircraft means human, aircraft, and operational environment. The factor resources are shown in Table 1. According to the potential outcomes of flight test happened before, there are 14 types of potential flight test risk models, including runway departure, aircraft stalled, engine failure or abnormality, aircraft out of control, tail into ground, tire fired, birds strike, landing gear stuck, heavy landed, pilot-induced oscillation, structural damaged, fluttered, flight test out of control with ice, engine damaged or extinguished. Based on the potential test risk modes, ten types of crucial test risk modes have been determined by occurrence probability and severe degree, including runway departure, aircraft stalled, engine failure or abnormality, aircraft out of control, birds strike, landing gear closed, structural damaged, fluttered, flight test out of control with ice, engine damaged or extinguished.

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Fig. 1 Process of risk management Table 1 Categories of flight test risk Categories

Factor resources

Human

Error from test pilot, maintenance personnel, air traffic manager, and airport personnel Failure from parts, aero-engine, and aircraft Influence from natural and social environment

Aircraft Environment

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Table 2 Major inspection projects Risk modes

Probability, severe degree

Inspection projects

Runway departure

Probable, catastrophic

Aircraft stall

Probable, catastrophic

Engine failure or abnormality Aircraft out of control Tire fired

Remote, catastrophic Remote, catastrophic Remote, hazardous

Birds strike

Extremely remote, catastrophic

Landing gear stuck

Remote, catastrophic

Heavy landing

Remote, catastrophic

Braking landing gear and steering nose wheel Taxiing and taking off in the direction of the sun’s non-direct pilot’s eye Testing in the maximum hard and dry runways with visual flight weather Conducting brief familiar with flight process in rescue team Wind speed is not greater than 5 knots Checking tires, struts, and brakes Monitoring excessive pitch tendency Monitoring brake and tire temperature Equipping ground crew with fire extinguishers, fire axes, spare wheel/tires and brakes, cooling fan, and heat shield gloves Limiting maximum take-off angle of attack Keeping the wing level as far as possible after leaving the ground Checking the horizontal maneuvering ability Limiting maximum wind speed Auxiliary power system remains open Checking the control characteristics Ground monitoring flight control, hydraulic system Equipping tire cooling facilities and fire extinguishing facilities Clearing the runway Monitoring tire temperature trend Checking traffic control or bird strike warning in flight notifications Testing in the visual meteorological conditions Investigating the meteorological conditions and bird activity Applying for airport bird repellent service Switching on the available external lighting Testing for landing gear on the ground Placing emergency landing gear according to flight manual Monitoring the drop rate and the trajectory of the aircraft

3.2

Major Inspection Projects

Eight types of major risk modes and inspection projects have listed in Table 2.

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4 Risk Mechanism with Diverse Failures The test risk is the probability expected to occur that an exposed aircraft will be fatally injured caused by the failures. Equation (1) is used to calculate the test risk constituted by frequency of expected failures occurrence, corresponding conditional probability, and injury ratio. The frequency of expected failures occurrence can be obtained between failure times and test times with different kinds of parts by historical data. The conditional probability is related to the inspection complexity, effectiveness of maintenance, redundant design, and relationship of different multi-failures which can be acquired by empirical data. The conditional probability also can be determined by test data or Monte Carlo method when the type of aircraft is in the development process if there is no data available. The injury ratio can be obtained by statistical analysis. R¼FwS

ð1Þ

Where R is the flight test risk; F is the frequency of expected failures occurrence; w is the conditional probability; S is average probability exposed fatal injury. Based on the statistical method of observation, the conservative upper limit can be estimated by the chi-square test as Eq. (2). h i. F  v2a;2ðr þ 1Þ 2TI

ð2Þ

where r is the number of historical failures; TI is the total flight hours.

4.1

Relationship of Multi-failures

Many kinds of failures will have happened at the flight test process for civil aircrafts. The relationship between multi-failures can be divided into two types, independent failures and dependent failures. The independent failures may result in catastrophic outcome caused by single failure or multi-failures. The fault tree has determined frequencies, logic relationship, and occurrence reason of multi-failures. There are two types of dependent failures: causal dependent failures and common cause failures. The causal chain has described the logic relationship of causal dependent failures; common cause failures can be stated by fault tree and Markov method.

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Independent Failures

(1) Single Failures The test risk with i multi-failures is the summation of all kinds failure risk with each part in the aircraft, which can be calculated by the following Eq. (3). RIS ¼

n X

Ri

ð3Þ

i¼1

where RIS is the independent risk with many single failures, i is the number of failures. (2) Combined Multi-failures The catastrophic consequence is caused by independent failures rather than single failure. The failure of aircraft is composed by j independent failure of parts with the probability PA, PB, etc. The test risk will be the risk product of every different failure, which can be shown in the Eq. (5). RI1 ¼

N Y

! Pj

wS

ð4Þ

RI1i

ð5Þ

j¼1

RIC ¼

n X i¼1

where, RI1 is the risk with one consequence caused by combined failures; RIC is the risks with i consequences in this situation.

4.3

Dependent Failures

(1) Causal Failures The failures of components are caused by others. The events chain has established to obtain the conditional probability of unacceptable consequence caused by related components. Two unsafe outcomes A and B have been determined at the causal chain in Fig. 2. For example, the probability of unsafe outcome A occurring is the product of the probability of occurrence PC and PA1, PA2, PA3. The corresponding injury ratio is SA. The test risk can be obtained by Eq. (6). " RDC ¼ F  PC 

4 Y f ¼1

! PAf

 SA þ

2 Y

! PAf



f ¼1

where, f is the development phrase of causal failures.

3 Y f ¼1

! PBf

#  SB

ð6Þ

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Fig. 2 Causal chain of parts failure

Fig. 3 Expanded fault tree with common mode failure

(2) Common Mode Failures The failures belong to common mode failure, the expanded fault tree and Markov method have improved the accuracy of risk calculations. 1. Expanded fault tree S means the failure of subsystem, and the A, B mean the failure of parts. Minimal cut set should be {A, B} without regard to common mode failure; Minimal cut set would be {A′, B′}, {A′, CAB}, {B′, CAB}, {CAB} with common mode failure. Supposed that the failure probability of parts A, B are P(A), P(B), the dependent failure probability of parts A, B are P(A′), P(B′), the failure probability without regard to common mode failure is P(CAB), shown in the Fig. 3. The failure probability of system S without common mode failure is, PðSÞ ¼ Pð AÞPðBÞ; the failure probability of system S with common mode failure is, P0 ðSÞ ¼ PðA0 B0 [ A0 CAB [ B0 CAB [ CAB Þ. 2. Markov method The possible transition diagrams of common mode failures with two dependent parts (A and B) have shown in Figs. 4 of which U means that the part operate normally, D means that the part stop to work. The failure rates of parts A and B are k1 and k2 ; repair rates of them are l1 and l2 . The common mode failure rate is k12 and its repair rate is l12 , which means that two dependent parts operate normally or stop to work at the same time. The test risk with h common mode failure system can be determined as Eq. (8).

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Fig. 4 Transition diagrams of common mode failures with parts A and B

RDC1 ¼ F 

k  Y h¼1

RDCC ¼

 P0 ðSÞh  S

n X

RDC1i

ð7Þ

ð8Þ

i¼1

where RDC1 is the risk with one consequence caused by common mode failures; RDCC is the risks with i consequences in this situation.

5 Conclusion The risk identification and mechanism of civil aircraft during flight test have been presented. Fourteen types of potential risk modes have been obtained from human, aircraft, and environment factors, including runway departure, aircraft stalled, engine failure or abnormality, aircraft out of control, tail into ground, tire fired, birds strike, landing gear stuck, heavy landed, pilot-induced oscillation, structural damaged, fluttered, flight test out of control with ice, engine damaged or extinguished. Ten types of crucial risk modes and eight types of inspection projects have been listed from potential risk modes. Risk mechanism with diverse failures has been divided into dependent failure and independent failure, including single failure, combined multi-failures, causal failures, and common mode failures. The corresponding calculation of each failure modes has been supported to assess the flight test risk level. This paper provides theoretical basis for more accurate calculation of the flight test risk and further operational safety. Acknowledgements This work is supported by the National Natural Science Foundation of China, No. U1333119; Defense Industrial Technology Development Program, No. JCKY2013605B002; Civil Aircraft Special Foundation of Ministry of Industry and Information Technology, No. MJZ-2017-J-98; Postgraduate Research & Practice Innovation Program of Jiangsu Province, No. KYCX17-0273; Fund of Shanghai Engineering Research Center of Civil Aircraft Health Monitoring, No. GCZX-2015-05.

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References 1. ANM-110 (2012) Flight test guide for certification of transport category aircrafts. Federal Aviation Administration, Washington 2. Aviation Safety—Aircraft Certification Service, Aircraft Engineering Division (2006) Aircraft ice protection. Federal Aviation Administration, Washington 3. ANM-110 (2014) Performance and handling characteristics in icing conditions. Federal Aviation Administration, Washington 4. ANM-115, Transport Airplane Directorate (2014) Aeroelastic stability substantiation of transport category airplanes. Federal Aviation Administration, Washington 5. Transport Airplane Directorate (2011) Transport airplane risk assessment methodology handbook. Federal Aviation Administration, Washington 6. AVP-1, Accident Investigation (2017) Safety risk management policy. Federal Aviation Administration, Washington 7. Violette G, Safarian P, Han N (2015) Transport aircraft risk analysis. J Aircraft 52:395–402 8. Yuanyuan G, Youchao S, Longbiao L (2017) Failure risk assessment method of civil aircraft based on Monte Carlo method Acta Aeronautica et Astronautica Sinica 38:201126

Residual Risk Assessment of Civil Aircraft for Airworthiness Requirements Yuanyuan Guo, Youchao Sun and Longbiao Li

Abstract In this paper, to evaluate the acceptability of candidate corrective actions and monitor the risk variation during civil aircraft operation, the process of determining residual risk has been established including current risk level, acceptable degree, time limit of candidate actions, and optimal corrective actions. There are two crucial key points, that is, risk assessment and candidate actions. Risk assessment can be obtained through probabilistic damage tolerance (PDT) or Monte Carlo simulation (MC), of which PDT including occurrence probability, size distribution, stress uncertainty and detection probability, MC including risk levels, flight conditions, and risk factors. Candidate actions include regular maintenance or replacement, maintenance by fixed interval or service age, change the maintenance cycle, and redesign or refit, etc. Compared with the risk guidelines of civil aircraft, the priority of candidate corrective action will be decided to optimize the maintenance processes. The risk in decision making can be formulated by the residual risk to enhance the civil aircraft safety.







Keywords Civil aircraft Residual risk Corrective action Airworthiness requirement Probabilistic damage tolerance Monte Carlo method





1 Introduction Risk is the process of carrying out inspection requirements for aircraft maintenance, airworthiness and operational regulations, and plan maintenance inspection requirements from manufacturer’s recommendations by civil aviation operator or user according to aircraft configuration, operating environment and maintenance experience. It is the combination of compliance schedule and corrective actions which needed to alleviate identified unsafe occurrences. It is no longer considered to Y. Guo  Y. Sun (&)  L. Li College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_71

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be unsafe while it is being addressed by a developed guidelines of Advisory Circular. The residual risk is the risk after the corrective actions being accomplished. The worldwide researchers have carried on relevant research in risk assessment of flight safety and aircraft technology. Federal aviation administration issued relevant advisory circular ‘Damage tolerance for high-energy turbine engine rotors’ [1]; the regional risk assessment for engine parts have been jointly developed by the US southwest research institute, Rolls-Royce, General Electric and Pratt & Whitney, providing a probabilistic risk forecasting and management tool for engine manufacturers; a risk analysis methodology for wear-out issues in transport airplane has been established for analyzing the risk increment of aircraft and fleet in the late operational period [2, 3]; the risk assessment process with different corrective actions is presented to predict the occurrence of the failure and assess the failure risk [4]; aircraft manufacturing industry adopted safety management system that has been verified in order to prevent aircraft accident [5]; During routine inspections, upon discrepancy detection, some actions have been taken in order to correct the problem and avoid the loss of airplane structural strength [6]; a risk prediction methodology for mistuned integrally bladed rotors using geometric mistuning models has been proposed and validated with a large population of rotors [7]; the authors in this paper have supported the failure risk assessment method of civil aircraft based on Monte Carlo method [8]. At present, a wealth of experience at international study has been accumulated on airplane risk assessment based on assessment system and data acquisition. In this paper, the process of residual risk assessment will be enacted through determining the current risk level, time limit of corrective actions, various corrective actions. The risk calculation mainly relies on probabilistic damage tolerance and Monte Carlo simulation.

2 Process of Residual Risk Assessment The process of residual risk assessment including four steps is shown in Fig. 1. Step one: There are two effective methods to assess the current risk of civil aircraft, that is, probabilistic damage tolerance for aero-engine rotor risk assessment and Monte Carlo simulation for aircraft risk assessment. Probabilistic damage tolerance includes occurrence probability, size distribution, stress uncertainty, and detection probability; Monte Carlo simulation includes determining risk levels, flight conditions, and risk factors. Step two: Compared with the risk guidelines, if the risk level is acceptable, then end the process; if not, the time limit of candidate actions should be calculated. Maximum acceptable residual risk is less than 10−9/flight hour. Step three: residual risk calculation. The candidate actions should be formulated such as regular maintenance or replacement, maintenance by fixed interval or

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Fig. 1 Process of residual risk management

service age, change the maintenance cycle, and redesign or refit. To reasonable balance between cost and risk, these alternative measures need to be compared in terms of time, materials of inspection equipment, and labor, etc. Risk factors of corrective actions need to be calculated. The priority of different corrective actions

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will be determined according to the airlines benefit. If the alternative measures may reduce same risk, they will be prioritized in accordance with the cost. Step four: After evaluating these candidate corrective actions, recalculate and assess the risk acceptance. The optimal corrective actions will be chosen and used to optimize the maintenance processes. Corrective action implementation needs to be monitored in future. In many cases, the initial actions are not sufficient to reduce the risk to acceptable levels and may require subsequent countermeasures. The above assessment process can be used in the initial or subsequent measures. Follow-up measures may be more complete to understand the problem of failure events and the factors affecting them. Initial measures are based on limited or partial data, and subsequent measures are usually based on more complete information.

3 Time Limit of Corrective Actions The time should be determined to confine the operational time of aircraft and correct the latent failure in the life span. The appropriate exposure time for each envisioned failure can be calculated to make the overall risk meet the target for life span. At present, the public acceptable catastrophic probability is 1  10−7/flight hour. When a certain failure occurs in the aircraft, it is necessary to assess the possible risk. The higher the risk is, we need to take corrective action in a short time; the lower the risk is, we can take corrective action over a relatively long time. According to the European Aviation Safety Agency Research, three-fourth catastrophic risk is the basic design risk, and one-fourth catastrophic risk is unpredicted risk in the entire life in case there are unforeseen circumstances. The number of unpredicted individual failures will not exceed 10 times over the life span. Therefore, each catastrophic failure risk can be expressed by Eq. (1). 1 1 Rl ¼ 107   Tf  4 10

ð1Þ

where Rl is catastrophic risk limit; Tf is designed service life. The exposed time of failure is the time to formulate the corrective actions, which can be determined by probability of catastrophic event. Tp ¼

Rl P

ð2Þ

where Tp is exposed failure time; P is probability of catastrophic event. Figure 2 described the relationship between the probability of catastrophic event and the exposed time of failure. When the probability of catastrophic event is less than 1  10−9, no actions need to be taken; when the probability is greater than

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Fig. 2 Exposed time limit of corrective actions

2  10−6, the airplane should be on ground or back to the base; when the probability is between 1  10−9 and 2  10−6, the corrective action needs to be completed in the corresponding time.

4 Residual Risk Calculation 4.1

Probabilistic Damage Tolerance

Based on probability damage tolerance, the uncertainties of residual risk include maintenance frequency, probability curve of detection, material properties, loading conditions, geometric shape, defect probability, random defect size, damage of shape and position. The stress intensity factor changes with these uncertainties. The aircraft structure is divided into finite regions if there is at most one crack in each region. The regional failure risk can be calculated by determining the occurrence probability of defects in each region, of which the relevant defect parameters include the occurrence probability, size distribution, stress uncertainty, and detection probability. The incidence and probability size distribution of defect are described by transcendental curve about internal defects. The cumulative distribution function of defects is randomly generated by Monte Carlo method. According to the curve of Advisory Circular 33.14-1, the larger the defect size, the fewer the defects. When the defect area is smaller, the number of defects decreases sharply with the increase

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of size; when the defect size exceeds a certain number, the trend of decreasing the number of defects tends to be gentle. The probability density of regional stress is determined subsequently. Defect detection probability is related to detection method and defect size. The more advanced the detection means, the larger the defect size or area, the higher the probability of defects being detected.

4.2

Monte Carlo Simulation

Based on the Monte Carlo simulation, the residual risk assessment is applying to aircraft failure. Risk calculation is related to the risk level, risk factor, and risk criteria. There are six main steps. (1) The risk level of the aircraft failure event needs to be determined; (2) The risk factor C of the aircraft failure needs to be calculated. The risk factor Fi of different risk levels will be obtained according to the incident risk level. Suppose that total number of aircraft failures during the simulation is Ni (i = 1, 2 …), then the risk factor Fi is

Fi ¼ Ni  C

ð3Þ

(3) The flight risk will be calculated by risk factors. Compared with the risk criteria, the failure needs to take measures will be determined. The risk factor and flight risk of aircraft failure will be calculated again by Monte Carlo simulation after taking different corrective actions. (4) In view of the failure, the measures to reduce risks are formulated, and the model is used again to calculate the risk factors of aircraft failure and each flight risk.

5 Conclusion In this paper, the process of residual risk assessment has been established for safe operation of civil aviation, including determining risk level by two methods such as probabilistic damage tolerance and Monte Carlo simulation, making the risk acceptance, formulating the time limit of corrective actions, and enacting the optimal corrective actions by several candidate actions, which will guide the aircraft maintenance progress, enhance the civil aircraft safety, comply with the regulations of airworthiness, and ensure the continued operational safety.

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Acknowledgements This work is supported by the National Natural Science Foundation of China, No. U1333119; Defense Industrial Technology Development Program, No. JCKY2013605B002; Civil Aircraft Special Foundation of Ministry of Industry and Information Technology, No. MJZ-2017-J-98; Postgraduate Research & Practice Innovation Program of Jiangsu Province, No. KYCX17-0273; Fund of Shanghai Engineering Research Center of Civil Aircraft Health Monitoring, No. GCZX-2015-05.

References 1. ANE-110 (2017) Damage tolerance for high energy turbine engine rotors. Federal Aviation Administration, Washington 2. Transport Airplane Directorate (2011) Transport airplane risk assessment methodology hand-book. Federal Aviation Administration 3. Violette G, Safarian P, Han N (2015) Transport aircraft risk analysis. J Aircr 52:395–402 4. Longbiao L, Suyi B, Youchao S (2015) Risk prediction of aero-engine based on failure statistics data. J Nanjing Univ Aeronaut Astronaut 47:559–565 5. Lee K, Kim J (2015) Roles of safety management system (SMS) in aircraft development. Int J Aeronaut Space Sci 16:451–462 6. Arjun R, Nicoletta F, Karen M (2016) Analysis of helicopter maintenance risk from accident data. American Institute of Aeronautics and Astronautics SciTech Forum 7. Henry B, Brown M, Slater C (2015) A prediction methodology for mistuned IBRs using geometric mistuning models. In: 17th AIAA non-deterministic approaches conference, 1144–1161 8. Yuanyuan G, Youchao S, Longbiao L (2017) Failure risk assessment method of civil aircraft based on Monte Carlo method. Acta Aeronaut Astronaut Sin 38:201126

Airworthiness Safety Construction of Civil Aircraft Based on Operational Data Yuanyuan Guo, Youchao Sun and Longbiao Li

Abstract After strict type certification of civil aircraft, there is still likely to encounter failure or unsafe condition caused by standards compliance, design or manufacturing defect, operational or environmental conditions. The various operational data reflect aircrafts’ performance. In this paper, characteristics of operational data of civil aircraft have been analysed including flight delay information, service difficulty report, performance monitoring data, engine failure monitoring data, and parts remove data. The operational data of civil aircraft have been analysed by process failure mode effect analysis and criticality analysis, Weibull distribution, etc. based on these operational data, and the relevant safety condition has been carried out by five types of methods including function hazard analysis, fault tree analysis, zone safety analysis, common mode failure, and subsystem hazard analysis. Through these characteristics and analysis method of operational data, the safety system of civil aircraft has been constructed to ensure the future safety operation. Keywords Civil aircraft

 Airworthiness  Operational data  Safety construction

1 Introduction The organic combination of safety analysis method and operational data of civil aircraft are crucial for safety management in this process. Society of Automotive Engineers issued ‘Safety assessment of transport airplanes in commercial service’ to support diverse basic safety assessment methods in 2003 [1]; federal aviation administration issued guidance material for safety analysis [2]; federal aviation administration issued ‘Monitor safety–analyse data’ in 2012 to guide the monitor data application for safety and updated ‘Safety management system manual’ in Y. Guo  Y. Sun (&)  L. Li College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_72

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2014 [3, 4]; the safety management system is a formalized and proactive approach to system safety, including safety analysis and risk mitigation process, which is divided to describe system, identify hazards, analyse risk, assess risk, and treat risk. Wenkuei has established the risk assessment modelling in aviation safety management [5]; Milan has approved an assessment of risk and safety in civil aviation [6]; Yi and co-authors have an research on safety risk status monitoring method for SDR [7]. In this paper, the current mainstream aircraft operational data have been researched, including flight delay information, service difficulty reports, performance monitoring data, engine failure monitoring data, parts removing data. Combined with appropriate safety analysis method, the safety analysis system has been established based on operational information collection, data processing, and evaluation.

2 Safety Analyses of Operational Data The aircraft safety level has been analysed by variable safety analysis method based on operational data, including causal analysis, process failure mode effect and criticality analysis, function hazard analysis, fault tree analysis, zone safety analysis, subsystem hazard analysis, and common mode failure analysis.

2.1

Flight Delay Information

The flight delay information includes delay or cancellation, delay time, event description, ATA chapter information. Combining critical analysis and process failure mode effect and criticality analysis, the data of flight delay information have been pre-processed. Main influence factors for safe operation of civil aircraft are divided into human, aircraft, environment, and management. The inheritance relationships between flight delay event and flight delay mechanism have been determined by causal analysis. According to the flight delay information, the event analysis process has been established, including human error, aircraft failure, environment influence. The flight delay effect and severe degree can be obtained referred to the causal analysis outcome. The corrective actions need to be given and enacted continuously to ensure the acceptable delay events happened. The safety analysis of flight delay information is shown in Fig. 1.

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Fig. 1 Safety analysis of flight delay information

2.2

Service Difficulty Reports

Service difficulty reports include event description, parts’ service time/cycles. The safety analysis of service difficulty reports is shown in Fig. 2. According to the system tasks, design goal, and service needs, the system functional listing has been determined. Compared with service difficulty reports, the system functional failure can be given including loss of function, functional bias, or timing deviation of function. Considering the functional failure reason and influence, the severe degree can be ranked according to four types that are catastrophic, serious, medium, and negligible. The aircraft failure probability and relative risk level can be given subsequently to monitor the aircraft operational safety level. There are four types of event severe degree: (1) class I—catastrophic, such as APU fire, engine separation, loss of thrust of aero-engine. (2) class II—serious, such as runway departure, loss of cabin pressure, serious casualties.

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Fig. 2 Safety analysis of service difficulty reports

Table 1 Risk parameters of service difficulty reports Relative probability

Relative probability index

Categories of severe degree

Severe degree

Risk level

Acceptance

0 0.05).

3.2

Performance of Simulated Combat Tasks

The performance indexes of simulated combat tasks included the time from air target appearing to be captured, the time of completing attack, results of attack, and the total time of finishing all attack tasks. The results of descriptive statistics are shown in Table 3, and the results of significance test of difference are in Table 4. Among the six color schemes in Table 3, the time from air target appearing to be captured in scheme No. 2, No. 3, and No. 5 was relatively shorter, and No. 1 was longer. For the time of completing attack, scheme No. 5, No. 3, and No. 1 were relatively shorter, and No. 6 was relatively longer. For the results of attack, hit rate of scheme No. 6 was the lowest, and the No. 3 and No. 4 were the highest. For the total time of finishing all attack tasks, scheme No. 3 and No. 5 were relatively shorter, and No. 6 was relatively longer. The results in Table 4 suggested that in the six color schemes, above four performance indexes were not significant (p > 0.05).

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Table 3 Results of descriptive statistics in simulated combat tasks (n = 91) Test menus

Color scheme Color scheme Color scheme Color scheme Color scheme Color scheme

1 2 3 4 5 6

Time from air target appearing to be captured (s)

Time of completing attack (s)

Results of attack Hit No Hit (n) hit rate (n) (%)

Total time of finishing all attack tasks (s)

157.68 142.10 143.63 154.07 145.17 154.40

103.12 118.35 102.40 105.40 98.00 127.54

235 235 234 233 225 224

260.81 260.46 242.04 259.47 243.18 281.95

20 20 15 16 21 31

92.16 92.16 93.97 93.57 91.46 87.84

Table 4 Results of significance test of difference in simulated combat tasks (n = 91) Time from air target appearing to be captured F Sig

F

0.406

2.094

3.3

0.845

Time of completing attack Sig

Total time of finishing all attack tasks F Sig

v2

Sig

0.064

1.115

8.070

0.152

0.351

Results of attack

Results of Alerting Information Response

In simulated route flight tasks, there was one warning and one caution message randomly appearing. When pilots noticed the messages, they should respond rapidly by pressing on the specified button according to the arrow’s direction. The results of descriptive statistics are shown in Table 5, and the results of significance test of difference are in Table 6. Among the six color schemes in Table 5, for the response time of pilots to warning messages, scheme No. 5 was a little short, and No. 1 was the longest. In the rate of correct response, scheme No. 3 and No. 5 were the highest, and No. 1 was the lowest. For the response time of pilots to caution messages, scheme No. 3 was the shortest, and No. 6 was the longest. In the rate of correct response, scheme No. 5 was the highest, and No. 1 was the lowest. The results in Table 6 suggested that in the six color schemes, the response time and correct response results of pilots to warning messages were not significant (p > 0.05). For the caution messages, the response time was significant (p < 0.01), and correct response results were not significant (p > 0.05).

3.4

Results of Pilots’ Subjective Evaluation

After the simulated tasks, experiment procedure automatically entered in subjective evaluation interface. The pilots were required to evaluate the color scheme with

6

5

4

3

2

2.13

2.00

2.07

2.05

2.06

75

76

74

77

74

71

10

6

9

6

11

14

2.30

Color scheme Color scheme Color scheme Color scheme Color scheme Color scheme

1

Warning message Response Result of response time (s) Correct Leakage response (n) (n)

Test menus

88.2

92.7

89.2

92.8

87.1

83.5

Rate of correct response (%)

Table 5 Results of descriptive statistics in response to alerting information (n = 91)

2.27

2.08

2.14

2.02

2.07

2.12

78

76

75

75

76

72

7

6

8

8

9

13

Caution message Response Result of response time (s) Correct Leakage response (n) (n)

91.8

92.7

90.4

90.4

89.4

84.7

Rate of correct response (%)

632 D. Xiong et al.

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Table 6 Results of significance test of difference in response to alerting information (n = 91) Warning message Response time F

Sig

Result of response v2

0.541

0.745

5.255

Caution message Response time Sig

F

0.386

3.135

Sig

Result of response v2

Sig

0.009

3.599

0.609

Table 7 Rate of excellent and good with pilots’ evaluations (%) Test menus Color Color Color Color Color Color

scheme scheme scheme scheme scheme scheme

1 2 3 4 5 6

Index 1

Index 2

Index 3

Index 4

Index 5

83.3 92.9 89.1 79.5 81.7 85.8

78.8 87.0 77.1 55.4 62.2 67.0

90.5 90.5 78.3 55.4 67.0 65.8

82.3 78.8 74.7 62.6 74.3 68.2

83.5 84.7 75.9 57.8 71.9 76.4

Table 8 Results of significance test of difference in pilots’ evaluations Index 1 v2

Sig

Index 2 v2

Sig

Index 3 v2

Sig

Index 4 v2

Sig

Index 5 v2

Sig

23.060

0.083

44.168

0.000

57.511

0.000

16.173

0.371

33.119

0.005

excellent, good, medium, and bad, and they could write their suggestions. There were five evaluation indexes. They were differentiability of discovering and identifying important information, rationality of display element when matching colors, harmony of menu colors, comfortability of longtime flight (fatigue), and dazzling or not. The rate of excellent and good of descriptive statistics is shown in Table 7, and the results of significance test of difference are shown in Table 8. Among the six color schemes in Table 7, for the rate of excellent and good index 1, scheme No. 2 and No. 3 were the highest, and No. 4 and No. 5 were the lowest. In the index 2, scheme No. 2 was the highest, and No. 4 was the lowest. In the index 3, scheme No. 1 and No. 2 were the highest, and No. 4 was the lowest. In the index 4, scheme No. 1 was the highest, and No. 4 was the lowest. In the index 5, scheme No. 2 and No. 1 were the highest, and No. 4 was the lowest. The results in Table 8 suggested that in the six color schemes, pilots’ evaluation results of index 1 and index 4 were not significant (p > 0.05), but it was significant for index 2, index 3, and index 5 (p < 0.05).

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4 Discussion 4.1

About Simulated Flight and Combat Tasks

According to the performance of simulated route and combat tasks, all performance indexes were not of absolute advantages, and there was no significance. From this point, every color scheme would have no important effect on simulated task performance. The reasons might be as follows: The simulated tasks in this experiment were simple; especially the participants were all mature pilots in combat army. When pilots accomplished these simulated tasks, they only needed simple operation, and the different colors of information had no obvious effects on their performances. So, these performance indexes appeared not significant in six color schemes. In fact, there might be many factors that could impact on pilots’ recognition of color coding, such as mental workload and task type [4]. So, some factors about color coding should be researched.

4.2

About Response to Alerting Information

The alerting information in this study is chose from GJB1006-1990 [5]. According to the response of alerting information, scheme No. 1 was a little worse than other colorful schemes in response time, response results, or correct response rate. These results suggested that colorful display of alerting information was beneficial to pilots to rapidly identify and respond to them correctly. And scheme No. 3 and No. 5 had superiority.

4.3

About Pilots’ Subjective Evaluations

In the subjective evaluation, for the rate of excellent and good, scheme No. 2 was the highest in index 1, 2, 3, and 5. And the results of significance test of difference suggested that scheme No. 2 was better than other schemes in index 2, 3, and 5. Among scheme No. 3 to No. 6, scheme No. 3 was in the ascendant. At the same time, scheme No. 1 is relatively high in index 3 and index 4. From the results of subjective evaluation, pilots appraised the monochrome messages better except for alerting information. This result might be related to pilots’ flight experiences. Pilots participated in the experiment had used HUD, and the information in HUD was displayed in green. They were used to observe the color, and when they observed the information by colorful display, they might be not adapted it. So, they would not entirely accept the colorful system with see-through displays from their hearts.

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5 Conclusions Based on the results in this study, according to above analysis and discussion, the conclusions are as follows: (1) In the simulated tasks, the performance indexes are not significant in six color schemes. (2) It is beneficial for pilots to rapidly identify and correctly respond to the alerting information when they are displayed in red and yellow. (3) From pilots’ heart, they prefer scheme No. 2 and No. 3 which are displayed in different colors. (4) Scheme No. 2 and No. 3 are recommended as the best color schemes, but this conclusion is only primary, and verifying researches should be conducted later. Compliance with Ethical Standards The experimental study was approved by the Academic Ethics Committee of Institute of Aviation Medicine PLAAF. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. SAE ARP4032A-2007 (2007) Human engineering considerations in the application of color to electronic aircraft displays 2. Post DL, Geiselman EE, Goodyear CD (1999) Benefits of color coding weapons symbology for an airborne helmet-mounted display. Hum Factors 41(4):515–523 3. Xiong D, He Q, Guo X et al (2017) Study on color coding requirements for see-through displays in simulated aeromarine flight. In: Long S, Dhillon BS (eds) Man-machine-environment system engineering, vol 67. Lecture Notes in Electrical Engineering. Springer, Singapore, pp 575–582 4. Zhang L, Zhuang D, Wan-Yan (2009) The color coding of information based on different mental workload and task type. ACTA ARMAMENTARII 30(11):1522–1526 5. GJB1006-1990 Alerting, aircrew station, general requirement for. Authorized by the National Defense Science,Technology and Industry Commission on January 26, 1991

Application of the Grey Clustering Evaluation Model in Risk Level Assessment of Merchant Ships Feng Li and Hong Yi

Abstract With the increasing numbers of merchant ships voyaging all over the world, a rise in maritime accidents emerges. As a consequence, it is necessary to assess the risk level of ships. In this article, a ship risk level assessment method is constructed, which is based on the grey clustering evaluation model. The major risk index is divided into three groups: ship/management, environment and crew. Meanwhile, the grey level of risk is low risk, moderate risk and high risk. The whitenization weight functions of different grey level are established by the grey clustering evaluation model. By using this model, the effectiveness of the method has been validated through practical cases. Keywords Risk level

 Grey clustering  Whitenization  Risk index

1 Introduction Nowadays, maritime transport plays a vital role in world trade. Ships engaging in seaborne transport increase rapidly. Consequently, traffic density at sea becomes higher than decades of years ago, especially in the areas around water lanes. Meanwhile, maritime accidents have been rising recent years. European Maritime Safety Agency [1] found that in each year the number of marine casualties and incidents reported has continued to increase and the total number of reported marine casualties and incidents is 12,591 in 2016. For the purpose of assessing the overall safety performance in the maritime domain, maritime community has developed series of risk assessment measures. International Maritime Organization (IMO) applied Formal Safety Assessment (FSA), which can be used as a tool to help in the evaluation of new regulations for maritime safety and protection of the marine environment [2], Paris Memorandum F. Li (&)  H. Yi The School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_74

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of Understanding on Port State Control (Paris MOU) developed a new inspection regime (NIR); the NIR established the concept of the Ship Risk Profile, which is based on type of ship, age of ship, performance of ship’s flag; performance of the recognized organization(RO); performance of the company responsible for the ISM management; number of deficiencies and number of detentions [3]. Meanwhile, academic research has been carried out in this domain. Some researchers improve risk assessment effectiveness by using PSC data [4–7]. Balmat et al. [8, 9] evaluate maritime risk by means of fuzzy logic approach, which divides ship risk into three groups, namely static risk factor, meteorological risk factor and risk factor related to the ship’s dynamic. Li KX et al. [10] develops a ship safety index which can generate a relative ship risk score using binary logistic regression method and a dataset. Bao and Huang analyse maritime risk using artificial neural network and fuzzy inference system, respectively [11, 12]. However, risk assessment system in the maritime safety domain is an uncertain system containing partially known information and partially unknown information. Grey system deals with uncertain systems with partially unknown information through generating, excavating and extracting useful information from what is available [13]. Grey clustering evaluation model has been applied to decision support, risk assessment in the industry, transportation, environment and management field [14–17]. Meanwhile, the structure of grey clustering is flexible; it can mix various factors in different dimension and can assess risk dynamically. Based on the advantage of grey clustering, this article uses the improved grey clustering evaluation model introduced by Liu et al. [18] to assess risk level of merchant ships.

2 Constructing Risk Level of Merchant Ships 2.1

Risk Index of Merchant Ships Analyse

Merchant ships’ voyage on the sea faces various threats, from “hard” equipment to “soft” management. According to the “human, machine, environment and management” theory, the risk of merchant ships can be divided into three categories in general, namely ship/management, environment, management and crew. Risk of ship/management is a combination of ship risk itself and management risk. It has five risk indexes. Considering ship itself is a complex architecture, the reliability of ship decreases along with ship’s age increases. Therefore, the first risk index is the ship’s age. The flag performance indicates the overall management level of flag nation that the ship registered. The performance of recognized organizations (RO) means the quality of construction and maintenance level of ship. The performance of company has a close tie with the management level of ship. As a consequence, the performance of flag, RO and company are another three risk indexes. The number of deficiencies inspected by PSC is a vital index directly related to ship’s management level on scene. Hence, it is the last risk index in this category.

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Environment risk includes natural environment and traffic environment. Natural environment mainly contains weather conditions, such as fogs, winds, current, width and length of water lane. Traffic environment mainly means traffic density. Therefore, there are four vital risk indexes in this category, namely visibility, wind force, current speed and traffic density. Crew risk is the direct factor contributing to maritime accidents. It is widely acknowledged that 80% of maritime accidents are due to human error. Crew error, as one of the most vital human error, is a contributing factor concerning risk of merchant ships. However, there are a crowd of types of crew errors, such as crew fatigue, education background, crew workload, crew collaboration and the effect of vibration, noise, rolling and pitching of ships. The article selects the service year index (SYI) as the crew factor and reciprocal value of SYI as the risk index which can reflect the overall of crew risk level. SYI ¼

  1 SYac SYa1 SYa2 SYa3 þ þ þ 4 10 8 7 6 RSYI ¼

1  100 SYI

ð1Þ ð2Þ

SYac indicates the average service years of captains, chief engineer. SYa1 indicates the average service years of chief officers, second engineers. SYa2 indicates the average service years of second officers, third engineers. SYa3 indicates the average service years of third officers, fourth engineers. Based on index analysed above, the structure of risk index of merchant ships is established (Fig. 1).

Fig. 1 Risk index of merchant ships

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Grey Class and Criteria of Merchant Ships Analyse

The purpose of risk level assessment of merchant ships is to identify high-risk ships so as to facilitate risk management in maritime safety domain. In general, the safety level, that is to say the grey class, can be classified into high risk, moderate risk and low risk. Concerning the risk index established in Sect. 2.1 and the three grey classes, based on statistics, questionnaire survey, on-scene research, the risk level assessment system of merchant ships is constructed in Table 1. Note that if data exceeds the upper edge of high risk level, it is treated as the upper edge.

Table 1 Risk level assessment system of merchant ships Category

Risk index

Unit

Low risk

Moderate risk

High risk

Description

Ship/ management

Ship age

Year

[0, 5]

(5–25]

(25–40]

In general, a ship less than 5 years can be treated as a new ship and more than 25 years can be treated as an old ship

Flag performance

Rank number

[0, 42]

(42–85]

(85–130]

According to Paris MOU, ranking of excess factor of flag performance

RO performance

Rank number

[0, 10]

(10–29]

(29–50]

According to Paris MOU, ranking of excess factor of RO performance

[0, 2]

(2–5]

(5–10]

According to the criteria made by Paris MOU, the low and very low performance of company made by Paris MOU is treated as high risk in this article

Company performance

Environment

Crew

Number of deficiencies



[0, 1.5]

(1.5–4.5]

(4.5–10]

According to statistics of Paris MOU and surveys

Visibility

1/ m * 1000

[0, 1]

(1–2]

(2–10]

According to regulations made by China MSA

Wind force

Wind force

[0, 6]

(6–9]

(9–12]

According to regulations made by China MSA and surveys

Current speed

m/s

[0, 1.25]

(1.25–4.75]

(4.75–10]

According to research made by Huang [15] and surveys

Traffic density

Numbers of ships per day

[0, 200]

(200–500]

(500–700]

According to research made by Huang [15] and surveys

RSYI



[0, 25]

(25–50]

(50–100]

According to Eq. 2 in this article

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3 Architecture of the Grey Clustering Evaluation Model The grey clustering model is a method which divides observational objects into pre-determined classes according to whitenization weight functions [13, 18]. Liu et al. [18] establish a grey clustering evaluation model based on mixed centre-point triangular whitenization weight function, using a mix of upper measure whitenization weight functions, lower measure whitenization weight functions and triangular whitenization weight functions. By contrast, the model is proved lower deviations. This article uses the concept of this model, and the step is carried out as below. Step 1: Analyse the system and determine the parameters, including Objects X: X ¼ fxi g (i = 1, 2, 3, …, n) Criteria Y: Y ¼ yj (j = 1, 2, 3, …, m) Grey classes K: K ¼ fk1 ; k2 ; k3 ; . . .ks g The range of the values of criterion j in terms of grey class k is ½aj ; bj . Divide each ranges of the criteria j into s grey classes. Confirm break points of k1j and k1j of grey class number 1 and s in terms of criterion j, which is the two edge of

the grey class. In the same time, confirm centre-point value k2j , k3j , ks1 j , in term of criterion j. Step 2: Calculate the whitenization weight functions of the jth criteria with respect to the kth grey class fjs ðÞ with Eqs. 3, 4 and 5. h i x 62 aj ; k2j h i x 2 aj ; k1j h i 1 2 x 2 k ; k 2 1 ; j j k k

8 > 0; > > < fj1 ð xÞ ¼ 1; > > 2 > : kj x j

fjk ð xÞ ¼

8 > 0; > > > < xkk1

j

j ; kkj kk1 j > > k þ 1 > > : kkþj 1 xk1 ;

kj

kj

h i ; kkj þ 1 x 62 kk1 j h i x 2 kk1 ; kkj j h i x 2 kkj ; kkj þ 1

h i x 62 ks1 j ; bs h i xxkj ð1Þ s fjs ð xÞ ¼ xk ð2Þx x 2 ks1 k ð1Þ ; j ; kj j j > h i > > : 1; x 2 ksj ; bs 8 > 0; > > <

ð3Þ

ð4Þ

ð5Þ

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Step 3: Calculate critical value xj in term of criterion j. in this article, because of sufficient information is not available, mean value is adopt. xj ¼

1 j

ð6Þ

Step 4: Calculate the clustering coefficient of the jth criteria with respect to the kth grey class rkj . rkj ¼

m X   fjk xij  xj

ð7Þ

j¼1

xij means the observation value of the object i with respect to criteria j. Step 5: Confirm grey  class  of object. Find out max1  k  s rki ¼ rk i ; it draws a conclusion that object i can be categorized into grey class k*.

4 Case Study and Analysis Taking a container ship belonging to a shipping company as a case, the relative date is shown in Table 2. According to Paris MOU NIR, the ship belongs to low-risk ship. Using the method introduced by the article, the calculating process is carried out by software made by Nanjing University of Aeronautics and Astronautics. The clustering coefficient in scene 1 is [0.5214, 0.4786, 0.0000], and the biggest clustering coefficient is 0.471, so the risk level of the ship is low risk. It is in accordance with the conclusion of NIR. Moreover, the model provides a dynamic assessment method. As far as we know, the conditions of ship sailing on the sea change all the time and the risk level differs. The clustering coefficient in scenes 2 and 3 is [0.3313, 0.4037, 0.2651] and [0.7713, 0.2287, 0.0000], respectively. The risk level of the two stages is moderate risk and low risk. The result indicates that risk level becomes worse accompanied by dynamic index, namely environment, crew index becomes worse, the reverse situation is true as well as. At the same time, even though two scenes are on the same level, it can find out the better one through comparing the biggest clustering coefficient. In this example, the safety level of scene 3 is better than scene 1.

35

35

35

3

3

3

Scene 1 Scene 2 Scene 3

Flag performance

Ship age

Scene

8

8

8

RO performance

Table 2 Risk data of the container ship

3.5

3.5

3.5

Company performance

1

1

1

Number of deficiencies

0.8

2.5

1

Visibility

3

12

7

Wind force

0.6

4

1

Current speed

50

400

300

Traffic density

20

90

31.3

RSYI

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5 Conclusion Grey clustering evaluation model is a suitable measure to assess risk level of merchant ships. The method takes into various indexes into consideration, including the ship/management index, such as ship age, flag, RO and company performance and number of deficiencies, the environment index, such as winds, current, visibility and traffic density, the crew index indicated by RSYI. The index introduced in this article contains the major factor-related maritime risk. As a consequence, the quality of assessment result is guaranteed. Using the model, the risk index can be evaluated. Furthermore, with the change of time and place of ships, the change of risk level can also be found out. In addition, the comparison of risk in the same risk level proved to be effective. Therefore, this model suits for the risk management of maritime organizations, such as administration bureau and shipping company.

References 1. European Maritime Safety Agency (2017) Annual overview of marine casualties and incidents. 2016 Lisboa 2. International Maritime Organization (2015) Revised guidelines for formal safety assessment (fsa) for use in the imo rule-making process. London 3. Du B (2015) A study on flag state performance evaluation based on PSC inspection. Dalian Maritime University, Dalian 4. Cariou P, Wolff F-C (2015) Identifying substandard vessels through port state control inspections: a new methodology for Concentrated Inspection Campaigns. Mar Policy 60: 27–39 5. Yang Z, Yanga Z, Yinb J (2018) Realising advanced risk-based port state control inspection using data-driven Bayesian networks. Transp Res Part A 110:38–56 6. Sun Z (2015) Research on PSC targeting model based on intelligent optimization algorithms. Dalian Maritime University, Dalian 7. Zhong S (2015) The study of ship’s safety conditions based on PSC inspections. Dalian Maritime University, Dalian 8. Balmat J-F, Lafont F, Maifret R et al (2009) MAritime RISk Assesment(MARISA), a fuzzy approach to define an individual ship risk factor. Ocean Eng 36:1278–1286 9. Balmat J-F, Lafont F, Maifret R et al (2011) A decision-making system to maritime risk assessment. Ocean Eng 38:171–176 10. Li KX, Yin J, Fan L (2014) Ship safety index. Transp Res Part A 66:75–87 11. Bao J, Liu Z, Huang T (2010) Ship risk assessment model. J Dalian Marit Univ 36:11–13 12. Changhai H, Shenping H, Yanbin H et.al (2011) Design and simulation of real-time dynamic risk assessment system for single ship based on FIS algorithm. Navig China 34:68–73 13. Liu S, Hu M, Jeffrey F et al (2012) Progress of grey system models. Trans Nanjing Univ Aeronaut Astronaut 29:103–111 14. Delgado A, Romero I (2016) Environmental conflict analysis using an integrated grey clustering and entropy-weight method: a case study of a mining project in Peru. Environ Model Softw 77:108–121 15. Huang Y (2015) Safety assessment of navigation based grey fixed weight cluster in Tianjin port areas. Dalian Maritime University, Dalian

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16. Ding L, Fan J, Liu Y (2017) Method of safety evaluation for system group based on grey clustering. Comput Sc 44:372–376 17. Lv C, Wu Z, Liu Z et al (2017) The multi-level comprehensive safety evaluation for chemical production instalment based on the method that combines grey-clustering and EAHP. Int J Disaster Risk Reduction 21:243–250 18. Liu S, Yang Y, Wu L (2015) Grey system theory and application, 7th edn. Science Press, Beijing

Research on Metacognitive Training Method of Six-Degree-of-Freedom Observation and Control Jie Li, Jiayi Cai, Weifen Huang, Liwei Zhang, Jing Zhao, Yanlei Wang, Xiang Zhang and Qianxiang Zhou

Abstract In the used metacognition theory, a metacognitive training method is designed including six steps of picture reading, picture description, etc. This method is also designed including the forms of thinking report, self-question, and behavior show. The verification experiments were made between the two training groups of metacognitive and conventional, analyzing cognitive test scores, operation performance, and questionnaire result. This method can improve the recognition and decision ability. By further, it can be applied in training missions of six-degree-of-freedom observation and control. Keywords Metacognition

 Six-degree-of-freedom  Training method

1 Introduction For manned spaceflight, China will continue to carry out the task of space station construction, operation, and space material supply, which cannot be done without the support of rendezvous and docking technology [1]. Before the first manually controlled rendezvous and docking of China, a great deal of six-degree-of-freedom observation control training was carried out to the operators, and the operators were required to master corresponding knowledge and skills. The new training method is introduced into six-degree-of-freedom observation control training as the supplement to the existing training methods, which can not only improve the cognitive skill of the trainees but also monitor the learning strategy and the cognitive control process of the trainees and improve the self-learning ability.

J. Li (&)  J. Cai  W. Huang  J. Zhao  Y. Wang  X. Zhang China Astronaut Research and Training Center, Beijing 100094, China e-mail: [email protected] L. Zhang  Q. Zhou Beihang University, Beijing 100193, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_75

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2 Research Status The concept of metacognition is put forward by Flaval for the first time, which exists in the back of cognitive activities and is the cognition of cognitive process itself, including three parts: knowledge, experience, and strategy. Metacognition knowledge is the process and result of cognition and the knowledge of controlling the cognition process. Metacognition experience is an emotional experience with cognitive activities, most likely to occur in a state when the thinking activity is high [2]. Metacognition strategy is to monitor, regulate, and control cognition activities [3]. In the intelligence model proposed by Sternberg, American scholar, it emphasizes the function of metacognition component, “metacognition plays a dominant role in the whole intelligence activities, plays an important role in regulating cognition activities, and its development reflects the gap between individual intelligence and thinking” [4]. The experiments of scholars Trainin and Swanson [5] show that the metacognition and common cognition ability are used as the independent processing process; in the complicated cognition, the combination of cognition ability and metacognition can achieve better training and learning effect. In the six-degree-of-freedom observation control training, the trainees receive the information from the instructor in a visual, tactile, and auditory manner and extract the past memory information through the brain to form new memory. The operation behavior is a series of results of input, coding, storage, and extraction of information; the trainees accept the external visual feedback, with the original learning experience, judge and correct their own learning state, thus making the operation reach the predetermined requirement.

3 Study on the Training Method of Metacognition Through three kinds of means such as thinking report, self-questioning and behavior display, the paper analyzes the perception, judgement and decision-in the process of image cognition, designs three stages and six-step metacognition training method.

3.1

Metacognition Training Stage

The six-degree-of-freedom observation control metacognition training is divided into three stages: basic training, core training, evaluation and examination. (1) Basic training: By testing the cognitive ability of spatial cognition and psychological rotation, the trainees are instructed to correctly treat the advantages and disadvantages of their cognition and to enhance the understanding of self-personality.

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By consciously enhancing the relative spatial position of two aircrafts, it helps to understand the relationship between image display and actual aircraft position and attitude from the principle. The knowledge, experience, and strategy of metacognition are trained to enhance their self-monitoring and adjusting ability during the cognition process. (2) Core training: Guiding the trainees to carry out autonomous training of image cognition, using the metacognition core training method and the procedures, and carrying out questioning and answering according to the training steps, and improving the cognitive ability of images through language expression and behavior display; in addition, the monitoring right of the training process is handed over to the trainees to determine whether the cognition operation strategy selected by them is appropriate. (3) Evaluation and examination: Guiding the trainees to make reasonable evaluation on the ability and achievement and develop the self-learning ability; promoting the trainees to rethink the learning process, adjust the learning objectives, and form effective learning strategies.

3.2

Metacognition Core Training Methods and Procedures Design

(1) Analysis of Image Cognition Process The trainees store relevant information such as handle control, image cognition, and operation experience imparted by the instructor in long-term memory and store the information related to the operation situation, the experience of correct or wrong operation into working memory. The longtime memory and working memory form an information storage library. The cognition includes three stages: First, perception stage focusing on image information capturing, receiving, and selecting corresponding display interface information; second, judging stage focusing on information matching, extracting the judgment rule of image information from the memory, matching the information received during the sensing stage, and making judgment on the relative spatial orientation; third, decision-making stage focusing on operation decision, judging according to the spatial altitude of two aircrafts, extracting the memory on the rule of the operation and control strategy from the information storage library, and then making the decision. (2) Metacognition Core Training Methods and Procedures This paper designs the metacognition core training procedures including picture reading, picture retelling, model demonstration, operation decision-making, execution demonstration, and review. The first step is to read pictures. Corresponding to image perception, the trainees receive information and enter into the sensory memory as a basis for judging the relative position and altitude relationship; the second step is picture retelling. Characterizing the image situation, enhancing the understanding of the image information through information retelling, and monitoring whether the judgment basis of image is reasonable or not. In addition, the

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Table 1 Information machining model and training step Information machining model

Training step

Metacognition strategy

Image apperceive Orientation judge

Picture read Picture description Model demonstration Operation decision Execution demonstration Review check

Apperceive Token Monitor Plan Execution, monitor Review

Operation decision

received information enters working memory and is compared with the image recognition rule in the longtime memory, and the spatial position relation and model of two aircrafts are formed in the brain; the third step is model demonstration. The key point is to display the three-dimensional space model formed according to the second step. That is, to arrange the physical models of two aircrafts according to the relative position relation, and monitoring the spatial altitude relation formed in the cognition; the fourth step is the operation decision. Aiming at planning, the control decision is made according to the judgment of the current relative position relation and the handle operation rule in the longtime memory; the fifth step is demonstration. Through model demonstration, the change and movement of model are monitored and interpreted; the sixth step is review. Reviewing the whole process and comparing it with the correct answer, if it is correct, summarizing the successful experience, and if there is a problem, summarizing the cause of problem and forming new working memory; see Table 1.

4 Verification Experiment on the Validity of Metacognition Training Method 4.1

Experimental Method

A total of 22 trainees, male, aged from 20 to 30, without experience on six-degreeof-freedom control. The trainees are divided into two training groups to receive the training with metacognition method and conventional method, respectively. Every trainee completes the static image interpretation and dynamic operation for 5 rounds and 35 times.

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Table 2 Experiment Indices Index

Description

Picture cognition performance Process Data Result Data NASA_TLX

Ability of judge and decision to static picture information Docking time and fuel of dynamic operation Difference at the time of docking Subjective evaluation result of time pressure and performance behavior

4.2

Experimental Indices

The experimental indices are shown in Table 2.

4.3 4.3.1

Data Processing Image Cognition Performance

See Fig. 1. Conducting the atlas identification test for the teams of conventional cognition group and metacognition group, the obtained image cognition ability test performance was P > 0.05; before training, there wasn’t significant difference in image cognitive ability of two groups. After the cognitive training and conventional training are adopted, respectively, the test result is P < 0.05; the performance on image recognition test of the metacognition group is obviously higher than that of the conventional group. In addition, after the metacognition group is trained, the metacognition experience is enriched, and is more confident when facing difficult pictures. It means that static cognition ability of the trainees can be effectively improved by metacognition training method.

4.3.2

Performance Indices

See Fig. 2. There aren’t significant differences in the mean docking time, position deviation, and altitude deviation between the two groups. However, the fuel consumption of the metacognition group is superior to that of the conventional training group. According to the analysis, the metacognition training has a certain effect on the monitoring of cognition activities of the trainees; the control to the handle is more accurate, and the fuel during dynamic operation process is saved.

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Fig. 1 Frontal and latter grades of graph cognition between two groups

4.3.3

NASA_TLX Indices

The time pressure is used to measure the difference between the actual time for the trainee to complete the task and the specified time of the task. If the trainee is unable to complete the task within the specified time, the time pressure is generated. The time pressure of the metacognition group is significantly lower than that of the conventional training group (P < 0.05), which is higher than that of the

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Fig. 2 Performance result between two groups

conventional group (P < 0.05) in performance; see Fig. 3. After analysis, the metacognition group strengthened the monitoring and adjustment of the cognition activities in the training and deepened the understanding on the image interpretation rule and the operation method of handle, so the time pressure was significantly smaller than that of the conventional group.

5 Conclusions and Prospects Based on the analysis of image cognition performance, operation performance, and NASA_TLX index, the metacognition training method of six-degree-of-freedom observation control is validated. The method can monitor the cognition characteristics of the trainees during the training process and timely discover the problems existing in the cognition model and carry out training in a targeted manner. In

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Fig. 3 Part result of NASA_TLX between two groups

addition, metacognition is applied to the field of training tasks in which the observation control cognition ability and the operability are strong and the application scope of the metacognition theory is expanded.

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Acknowledgements This work is supported by the China Manned Space Flight Fund (2014SY54A001). Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of China Astronaut Research and Training Center.All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Zhou J (2011) Rendezvous and docking technology of manned space flight. Manned Spaceflight 02:1–8 2. Schunk DH (2008) Metacognition, self-regulation, and self-regulated learning: research recommendations. Educ Psychol Rev 20(4):463–467 3. Cheshire A, Ball LJ, Lewis CN (2005) Self-explanation, feedback and the development of analogical reasoning skills: microgenetic evidence for a metacognitive processing account. In: Bara BG, Barsalou L, Bucciarelli M (eds) Proceedings of the twenty-second annual conference of the cognitive science society, pp 435–441 4. Sternberg RJ (1985) Beyond IQ: a triarchic theory of human intelligence. CUP Archive 5. Trainin G, Swanson HL (2005) Cognition, metacognition, and achievement of college students with learning disabilities. Learn Disabil Q 28(4):261–272

Intermittent Failure Combing Analysis and Prevention of a Certain Type of Missile Weaponry Guanqian Deng, Guiyou Hao, Yingjie Lv and Ying Zhou

Abstract The intermittent fault can recover automatically without repair, and it can also evolve into a permanent fault. In addition to randomness, it is very difficult to diagnose. The diagnosis of an intermittent fault as a permanent fault will affect the readiness of the equipment and the success of the task and cause unnecessary replacement or maintenance. Ignore the intermittent faults and letting them work with disease, there is a great hidden danger of safety, which may lead to the destruction of the machine and the death of people. Therefore, taking a missile weapon equipment as an object, this paper combs the intermittent faults in the process of using the equipment, analyzes the causes of the faults, and on this basis, all kinds of intermittent fault prevention and treatment measures are described, respectively. The research results can be used for reference for preventing intermittent faults of equipment and taking correct measures to deal with them. Keywords Missile weapon equipment prevention

 Intermittent fault  Failure analysis and

1 Introduction The missile weapons equipment is composed of many components, and the functional structure is complex, the use environment is wicked, the working intensity is high [1]. The statistics show that there will be a variety of intermittent faults in the process of equipment use. Intermittent fault is defined as automatic recovery without repair, or disappearing after being replugged, but under certain conditions (over environmental stress or working stress), it reappears again and again. Compared with the permanent fault, the intermittent fault can recover automatically and repeatedly, and the frequency, duration, fault amplitude of the intermittent fault G. Deng (&)  G. Hao  Y. Lv  Y. Zhou Institute of Reliability Engineering, Beijing University of Aeronautics and Astronautics, Beijing, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_76

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all have a certain randomness, when it is excited, its performance is similar to those of the permanent fault [2]. When the intermittent fault is restored, the function of the product is normal, so the intermittent fault diagnosis is very difficult [3]. A lot of research work has been carried out at home and abroad for its diagnosis, but most of them remain in the stage of theoretical exploration [4–6]. At present, the field of fault diagnosis still divides the product into normal and (permanent) fault state [7]. When fault occurs, the usual practice of the troops is to interrupt the mission, conduct troubleshooting, and replace or repair the “faulty parts” or ignore the fault and let the equipment work with the disease [8]. If intermittent failure occurs, interrupting the task for replacement or maintenance will affect the combat readiness, and mission success rate of the troops, and waste maintenance support resources. Ignoring the fault to continue work may lead to the failure of the whole launch mission and even cause heavy economic losses and casualties such as bomb damage and death of people [9, 10]. Therefore, it is urgent to comb the intermittent fault of the equipment, analyze the causes of the fault, and provide technical support for preventing and taking the correct fault treatment measures.

2 Intermittent Fault Combing and Treatment of a Certain Type of Missile Weapon Equipment The intermittent fault combing of a certain type of missile weapon is as follows: (1) Poor contact with the plug-in. According to statistics, in the equipment (especially missile launchers), in use process by electric connector, modular connectors, PCB, and other poor contact, fixed bad, defective insulation caused by intermittent failures and bigger share. For example, some abnormal unlock electric connector plug at the time of separation, a separation of electric connector off plug due to shortening the poor contact, contact after an electric connector in the cable assembly is not stable to return to normal after the electric connector plug again. The temperature rise of an insulation cover is not normal. After replugging the launcher, the cable plug is returned to normal. A startup platform is not normal within 5 s, and it is back to normal after reinserting and drawing a certain module and printing plate. Erase the abnormal, replug a board, and return to normal. The voltage test of AICI is not qualified, and the replacement of a certain module is normal. A positive or negative pulse number is not up to standard, and it is normal to reinsert a certain module. After the power supply is connected, the display is not displayed, and the reattachment of the control host and the monitor is back to normal after connecting video cable. After connecting to the host, the monitor can not find the hard disk, open the host, reconnect the main board and the hard disk to connect the cable and return to normal and so on.

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(2) Intermittent faults caused by aging. The long or frequent use of equipment due to aging, wear, and fatigue is not uncommon, especially in equipment that has a long time, especially near to life. For example, an axial limit mechanism is not normal, and after replacing the limit mechanism, the retry is normal. The opening of the target window is abnormal, and the retry is normal after replacement. The left mouse button of a certain control console sometimes fails, and the number of failures increases over time and eventually becomes completely ineffective. Replace the left mouse button (or mouse button circuit board) and return to normal. The valve cannot be closed automatically, and the valve should be replaced. By emitting device display control combination is observed at the beginning of a heating is obviously not normal, display control combination preliminary judgment fault, under the charged state inspection 10 a1  3/1, 2 point no voltage, replace the launcher temperature control, display control combination observation heating back to normal again. (3) Software failure As more and more software is installed on the equipment, manufacturers and versions are not the same, and there are more and more intermittent failures caused by software errors. For example, if a control host crashes or starts abnormal, it can enter normally after the restart, and it will not start after long-term use. Reinstall the Windows NT operating system (also may need to replace the hard disk) and return to normal. The computer is dead without reason and normal after restart. A controller can’t go through zero, get messy code, restart the power after zero return to normal, and so on. (4) Other There are some other unexplained intermittent faults during the use of the equipment. For example, some distance gate pulse width is not qualified, retry normal. A Dc power supply assembly will intermittently appear protective tripping; close air switch can work normally. An equivalent unit state electric cabinet display voltage of 26 V (should be 27 V, start the motor moment there will be 2 V voltage), the equivalent device state adjust M0 voltage of 29 V (should be 28 V) voltage automatically after returning to normal and so on.

3 Analysis of Intermittent Fault Causes of a Missile Weapon The reasons for the above analysis are summarized as follows: (1) Environmental stress leads to poor contact of connectors. Equipment in use process will inevitably suffer from vibration, shock, temperature, collision, such as environmental stress, and connectors are usually made of

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plug (needle) and outlet (hole), under the effect of the outside world squash or stretch on the one hand can make the transition gradually into a clearance or interference fit or transition fit, so that the contact resistance changes, squeezed cause the contact resistance is reduced, the traction caused by increased contact resistance, thus appeared the poor contact phenomenon such as instantaneous short circuit or open circuit. In addition, the relative motion or peristalsis between the plug and the socket causes the surface of the inserted needle to be worn, peeling, and even plastic debris. High temperature will oxidize the coating and aggravate the above wear. Contact resistance changes caused by contact oxidation, insulation dust, plastic debris, etc. (2) Prolonged and frequent use causes fatigue and wear. Equipment components, especially rubber parts after a long period of use, can appear aging, wear, and fatigue, the cumulative damage, with the increase of cumulative damage equipment intensity will gradually decline, when suffering from stress is greater than the gear strength, would be a drop in performance, the function (in part) to become bad, or lost, resulting in intermittent failures, this column is installed in or around for a long time especially in the life of the equipment. (3) Software error causes software failure. In the course of the use of a certain type of missile weapon, there are intermittent failures related to software. When people are involved in various stages of the software life cycle, there will inevitably be errors, and software errors will inevitably result in one or more software defects. When a software defect is activated, a software failure occurs. The same software defect is activated under different conditions and may cause different software failures. When software failure occurs, it will inevitably result in software failure if it is not handled in time. (4) Materials and processes, etc. In the process of equipment design, the selection of material is not reasonable, and the hard and brittle material of the cutting material causes the fracture of the jack, and the material is too soft to cause the hole to loosen. In the process of production, poor quality of heat treatment process, wire stripping lines core fracture or mechanical damage and make the wire core fracture, pressure holes and the wire line diameter does not match, crimping pliers, caused by improper pressure. In the process of assembly, the quality of the adhesive and assembly process is poor, which causes the glue between the jack and the inserting pin, and the second locking device is not in place and will cause the contact site to produce a fracture or short circuit failure.

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4 Intermittent Failure Prevention and Disposal Measures for a Type of Missile Weapon Equipment Intermittent fault is an intermediate state between normal and permanent fault. It may only be subjected to transient over stress, and no physical damage occurs. In this case, there is usually no need to interrupt the tasks and replace or repair them. It may also be due to the long-term use of physical damage accumulated to a certain extent, as a precursor to permanent fault. In this case, it should be replaced or repaired timely. Through combing and reason analysis of intermittent fault of missile weapon equipment, it can provide technical support for the equipment intermittent fault prevention and the fault treatment measures. From the previous analysis, we can see that the connectors are sensitive to environmental stress, especially to vibration, high temperature and their comprehensive stresses. Therefore, attention should be paid to shock absorption and cooling measures in the process of use, and parallel forces should be applied in the connection of the connectors, and the insertion should be in place. Try to avoid frequent and repeated insertion. Once the connector is in poor contact and other bad phenomena, you can troubleshoot it by reinserting and check whether there is oxidation, peeling, wear, and so on. On the surface of the socket pin and socket surface coating. If the coating of the connector is oxidized, peeled or worn seriously, and the fault is repeated, then the replacement may be considered. For the fault caused by software, software fault injection and software evaluation can be used to find software errors and avoid software defects before the software is finalized. After installation, once the suspected software related to the crash, automatic restart and other faults can be solved by restarting and reinstalling the software or driver. For some components which are used for a long time or frequently, or the environment in which it is used is wicked and the working intensity is high, we should pay close attention to their service life, rated life, and status changes in the use of process and carry on the maintenance according to the situation. If the fault occurs or performance depredated, replace the new parts. For some other unexplained intermittent faults, fault detection is usually carried out by reinserting, restarting, or replacement according to product type and fault characteristics.

5 Conclusions The data show that plug-in, long-term, and frequent use, software and other easy to trigger intermittent fault. The contact malfunctions caused by the connectors are usually excluded by replugging. It can be solved by restarting, reinstalling software, or driving for the failure of software caused by dead machine and automatic restart. New components are often required for failures in a long or frequently used component. The prevention of intermittent fault and proper fault disposal measures

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can not only improve the availability and safety of equipment, but also avoid unnecessary waste and save maintenance and maintenance resources.

References 1. Deng G (2013) Key technology research on intermittent fault diagnosis in extreme temperature environment. National University of Defense Technology, Changsha 2. Steadman B, Berghout F, Olsen N (2008) Intermittent fault detection and isolation system. In: IEEE AUTOTESTCON conference, Salt Lake City, UT, USA, 37–40 3. de Johan K (2009) Diagnosing multiple persistent and intermittent faults. In: 21st international joint conference on artificial intelligence, Pasadena, CA, USA, 733–738 4. Deng G, Qiu J, Liu G, Lv K (2013) Environmental stress level evaluation approach based on physical model and interval grey association degree. Chin J Aeronaut 26(2):456–462. https:// doi.org/10.1016/j.cja.2013.02.024 5. Deng G, Qiu J, Liu G, Lv K (2013) A novel fault diagnosis approach based on environmental stress level evaluation. J Aerosp Eng 227(5):816–826. https://doi.org/10.1177/ 0954410012442857 6. Sorensen BA, Kelly G, Sajecki A et al (2001) An analyzer for detecting intermittent faults in electronic devices. In: IEEE systems readiness technology conference, 1–12 7. Guilhemsang J, Heron O, Ventroux N et al (2010) Emphasis on the existence of intermittent faults in embedded systems. In: IEEE workshop on defect and data driven testing, 1–6 8. Correcher A, Garcia E, Morant F, Blasco-Gımenez R, Quiles E (2008) Diagnosis of intermittent fault dynamics. In: IEEE international conference on emerging technologies and factory automation, Hamburg, Germany, 559–566 9. Constantinescu C (2007) Impact of intermittent faults on nanocomputing devices. In: Proceedings of IEEE/IFIP DSN (Supplemental Volume), Edinburgh, UK, 238–241 10. Abreu R, Zoeteweij P, van Gemund AJ (2009) A new Bayesian approach to multiple intermittent fault diagnosis. In: 21st international joint conference on artificial intelligence, Pasadena, California, USA, 653–658

High Altitude Oxygen Production and Implementation of Special Vehicle Haiyan Niu, Liang Tian, Yaofeng He and Jianquan Ding

Abstract There are unstable factors in plateau area of China. Altitude hypoxia directly affects the operation ability of occupants. Because the special vehicles are transformed from mechanization to information, the occupant task changes from physical load to body–brain load type. Low-altitude and high-cold environment in plateau area has great influence on occupant control ability, especially cognitive ability. In this paper, by analyzing the oxygen demand of the special vehicles at the plateau, the oxygen absorption strategy of the occupants, and the principle of addition, the realization and experimental verification method of the oxygen production on the plateau of special vehicles and the experimental verification method are put forward. Keywords Plateau

 Oxygen production  Hypoxia  Operational ability

The plateau accounts for more than 1/4 of the land area of our country, bordering on six countries, including large-area territorial dispute areas and unstable factors, in addition, the plateau’s special geographical environment and severe weather conditions will cause occupant hypoxia. The altitude stress caused by hypoxia is one of the main factors that affect the ability formation of occupant. The area with altitude over 3000 is recognized as the height with medical significance, and altitude hypoxia is a general term of low pressure and low partial oxygen partial pressure climate in plateau area. From sea level to 100,000 m sky, the average content of oxygen in air is 21%. However, the higher the altitude, the thinner the air, and the atmospheric pressure decreases accordingly, and the oxygen partial pressure in the air decreases proportionally. According to the measurement, the elevation of Lhasa city is 3649 m, oxygen content is 64% of the plain, the elevation of Shiquanhe is 4278 m, the oxygen content is 56% of the plain, the elevation of Naqu is 4507 m, and the oxygen content is 59% of the plain. Therefore, although the relative proportion of oxygen in the atmosphere is not changed, hypoxia occurs due to the fact H. Niu (&)  L. Tian  Y. He  J. Ding Beijing Special Vehicle Institute, Beijing 100072, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_77

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that the thin air causes the low absolute amount of oxygen. In addition, the plateau region also has climate characteristics such as cold, windy, dry, large temperature difference between daytime and night, and large solar radiation intensity.

1 Influence of High-Altitude Hypoxia on Human With the increase of altitude and decrease of oxygen partial pressure, the oxygen partial pressure in alveolus of lung and arterial oxygen saturation also decrease. This produces a complex overall reflection to the physical functions of human body, involving all systems and organs. When the altitude reaches about 3000 m, human body will appear acute altitude disease symptoms, such as dizziness, headache, dysphoria, shortness of breath, asthenia, which directly affect the working ability of tank occupants. In the plateau with altitude over 5000 m, the physical and mental ability is obviously decreased or even lost. In the physical aspects of personnel, it mainly has the following influences [1]: (1) Nervous system. In particular, the cerebral cortex is most sensitive to hypoxia, 1 g of brain tissue requires 0.09–0.10 ml of oxygen in 1 min, almost 20 times the oxygen demand of muscle tissue. About 25% of oxygen in human body is used by the brain which occupies approximately 5% of the body weight. (2) Respiratory system. The increase of altitude is accompanied by decrease of atmospheric density, but the trachea gas and the vapor partial pressure in alveoli in human body are kept constant at 47 mmHg. When the atmospheric density decreases, the ratio of oxygen partial pressure in the trachea air and the alveolar air exceeds the atmospheric density reduction ratio, as shown in Table 1. When the personnel rushed to the plateau, the lung ventilation increases with the elevation to increase the oxygen partial pressure and oxygen saturation of the alveoli, and increase the amount of oxygen uptake. In general, the pulmonary ventilation volume increases by 20% more than the plain after 4–7 days after reaching the plateau, the increase of pulmonary ventilation volume also results in the increase of carbon dioxide discharge, the sensitivity of respiratory centre to carbon dioxide is increased, severe acute hypoxia can directly inhibit respiratory center, respiratory attenuation, and even failure. (3) Cardiovascular system. When personnel enters the plateau from the plain, the heart rate will accelerate, and the increase of cardiac output will lead to

Table 1 Changes in oxygen partial pressure of tracheal gas and alveolar gas caused by height changes Above sea level (m)

Sea level

1500

3000

4000

Oxygen partial pressure in the atmosphere (mmHg) Oxygen partial pressure in the trachea (mmHg) Oxygen partial pressure in the alveoli (mmHg)

160 149 105

132 122 82

110 100 62

98 84 50

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pulmonary artery hypertension and pulmonary edema, thus increasing the load of the right ventricular. The study “The Influence of Plateau Hypoxia on Psychological Function and Its Protection” completed by Guoyu Yang, from the Third Military Medical University Mental Health Education Centre, shows that the nerve tissue is most sensitive to the environmental change, the brain function is damaged first with most serious symptom; the longer the exposure time is, the more the damage is, especially to the personnel feeling, memory, thinking, and attention. In the mental aspects of personnel, it mainly has the following influences [2]: (1) Influence on feeling. Influence on vision—vision is most sensitive to oxygen deficiency in the sensory of human, the night vision is obviously damaged over the 4300 m altitude, and the vision is not improved due to the compensatory reaction of the organism or the elevation of the altitude; influence on audition— audition is affected by the increase of altitude, the high frequency range hearing decreases at about 5000 m altitude, mid-frequency and low-frequency range hearing obviously decrease at about 5000–6000 m altitude, and the directional force of hearing is obviously affected; influence on touch sensation—the touch sensation of human gradually becomes slow in severe hypoxia. (2) Influence on memory. The memory is very sensitive to hypoxia and is affected at the altitude of 1800–2400 m; at about 5000 m altitude, memory is weak enough to remember two things at the same time. With the increase of altitude, the degree of hypoxia increases, and the memory damage of different degrees can also be represented. (3) Influence on thinking. In acute altitude hypoxia, thinking ability of human may be directly affected, and the thinking ability of human may be damaged when the altitude is 1500 m, and its expression is that the ability to complete new and complex operation; the thinking ability of human in all aspects at 3000 m altitude decline, especially judgment; the writing ability declines, and there is an obstacle to the expression ability at 4000 m altitude; at 7000 m or higher altitude, some people suddenly had a loss of consciousness without obvious symptoms. The danger of hypoxia on the thinking ability is that the subjective feeling and the objective damage are contradictory, and that is, human cannot realize the damage of own behavior ability and cannot observe the behavior mistake. (4) Influence on attention. Under acute altitude hypoxia, the attention of human will be reduced obviously, and the attention will be difficult to concentrate when the altitude is higher than 5000 m. With the increase of altitude, the concentration of attention will become more and more narrow. The special environmental characteristics of plateau have an obvious effect on the physiological and psychological activity of human, and the best way to combat the anoxia is to supply oxygen.

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2 Analysis on the Demands for Occupant Operation Capacity of Special Vehicles According to the classification of special vehicle occupant professional technical posts, the occupants mainly include three persons, shown in occupant 1, occupant 2, and occupant 3; the primary capability characterization of the occupants is gradually broken down according to typical tasks performed by the occupants [3]. The main tasks of occupant 1 are to observe road conditions, traffic conditions, monitor vehicle status, determine working condition, communication, and so on. The execution mode mainly corresponds to continuous observation during the maneuvering, vehicle is controlled by the steering wheel, brake, accelerator, and transmission, the state of the vehicle is monitored by the display instruments and the alarm devices of the vehicle, and working condition is selected according to the application condition of the vehicle, accept command from occupant 2 command, or communicate between occupants through the helmet and communication box. The main operational abilities of the occupant are visual ability, hearing ability, coordination ability, reaction ability, movement ability, and information perception ability. The main tasks of occupant 2 include operation environment monitoring, environmental information perception, communication, command, and communication. The execution mode mainly corresponds to job environment observing, target searching, environmental state perception and target judgment, communication with the superior commander and the vehicle occupants, the traveling route planning, target indication, and so on. The main operational capability of the occupant is visual ability, information perception ability, decision ability, response and movement ability, etc. The main tasks of occupant 3 include communication, target tracking, target attacking, and effect evaluation. The execution mode mainly corresponds to obeying the instruction from occupant 2, communication with occupants in the vehicle, operating the device to track the target, judging the target attribute to select type of ammunition, and attacking effect evaluation. The main working ability of the occupant is characterized by visual ability, operational stability, information sensing ability, reaction ability, motion capability, and so on. It can be seen from the breakdown of occupant’s operation tasks in the Table; the occupant’s task is body–brain composite, with the development of technology, it has higher and higher demand on accurate operation, and it is necessary for the occupants to maintain a high level of cognition during the whole process of operation.

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3 Demand and Strategy Analysis on Installation of Oxygen Production Equipment (1) The installation of oxygen production equipment to special vehicles in the plateau has the following three demands: (i) It is the effective measure to reduce the non-combat attrition of occupants in plain rushing to the high-altitude plateau by installing the oxygen-producing device According to the data, special vehicle occupants enter altitude of 3658 m from land, and the incidence of acute altitude maladaptation is 70–80%; the troops enter the region through emergency air transport suffering from acute plateau maladaptation, the occurrence peak of the disease is 3–4 days after reaching the plateau, the incidence rate is up to 95%, which is the most important factor for influencing the operation ability. It is shown from data, when a special vehicle performance test is carried out on the comprehensive plateau training field of Yangbajing in August 2012, the heart rate of a driver accelerated rapidly from 110 to 140 times/min within 5 min, and the oxygen concentration rapidly dropped to 80%. Within 5 min after oxygen inhalation, the heart rate decreased to 100 times/min, and the blood oxygen concentration increased to 98%. It is shown that short-time oxygen inhalation can relieve the sudden conditions caused by hypoxia. The special vehicle requires the occupants to accurately operate and effectively control, and the above symptoms caused by acute altitude maladaptation directly lead to the non-combat attrition of the occupants. When the frontier guards carry out related tasks, they usually rest to the plain after staying for 10–15 days in high-altitude areas; therefore, it can reduce the risk of hypoxia due to hypoxia in the high-altitude plateau by installing oxygen production equipment for the special vehicles. (ii) It is the basic way to guarantee the operation ability of occupants by installing oxygen production equipment In the plateau area, human body, in order to adapt to the plateau anoxic environment, will cause a series of physiological and pathological changes and decrease the human labor function, and the operation ability is obviously decreased. According to the survey, the work efficiency of human is reduced by about 20% in the altitude of 3000–4000 m. With the increase of altitude, the plateau area directly leads to the decrease of occupant operation ability, while oxygen inhalation is the most effective and most direct measure to relieve the altitude stress and plateau disease. (iii) It is an effective method to rescue sick and wounded in high altitude by installing the oxygen production equipment Due to the reduction of body resistance, the sick and wounded are extremely vulnerable to high-altitude hypoxia environment, which can lead to serious illness and even life-threatening condition; if the sick and wounded patients can inhale

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oxygen in time, on the one hand, it can stabilize the sick and wounded from emotion, and on the other hand, the patient can win the time for subsequent treatment. (2) Analysis on the strategy of installing oxygen production equipment for the special vehicle in plateau (i) Provide oxygen with concentration not less than 50% under high-altitude environment As the altitude of the plateau rises, the content of oxygen in the air keeps constant at 21%, but as the air becomes thinner and thinner, the absolute amount of oxygen becomes lower. At altitude of 3000 m, the absolute content of oxygen is only 67% of the plain area due to the rarefaction of air, resulting in shortness of breath. It can be seen that the plateau oxygen concentration of the onboard oxygen production equipment should be as high as possible from the aspect of demand, in combination with the industrial level of the vehicle-mounted oxygen production equipment in China, it is required to provide the human body with oxygen with a concentration of not less than 50% under the plateau environment. (ii) The oxygen flow rate of single carrier shall not be less than 1.5 L/min in the manner of intermittent oxygen inhalation by turn According to different oxygen-supply requirements, it can be divided into continuous oxygen supply and intermittent oxygen supply. Constant oxygen supply is generally an oxygen-supply mode in which oxygen is supplied for a long period under the condition that the oxygen source is relatively sufficient, and this oxygen-supply mode is mostly adopted for the medical oxygen supply. Intermittent oxygen supply is adopted when the oxygen source is insufficient, and the occupants in the vehicle inhale oxygen by turn to obviously improve the operation efficiency of the occupants. When altitude stress occurs, it cannot be taken in the lump due to the large difference between occupants, the symptoms can be effectively relieved in more than ten minutes after oxygen inhalation, it is not necessary to inhale oxygen if the symptoms has effectively disappeared within 12 h, and the short-time oxygen inhalation case in the Tibet Yangbajing Laboratory can also explain the effect of short-time oxygen inhalation. From the medical angle, the suitable range of inhalation oxygen concentration (human alveolar oxygen exchange) is 24–33%, oxygen concentration = 21 + 4  oxygen flow  oxygen concentration according to the oxygen inhalation mode of nasal suction tube, oxygen concentration not less than 50% is provided to human body under plateau environment (at altitude of 4000 m, the oxygen concentration of a certain type of special vehicle is 54.7% [4]), and when the oxygen flow rate of a single occupant is not less than 1.5 L per minute, the concentration of inhaled oxygen = 21 + 4  1.5  50% = 24%, and the lower limit of inhalation oxygen concentration can be reached.

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4 Installation and Verification of Vehicle-Mounted Oxygen Production Equipment The following principles [5] shall be followed in the installation of vehicle-mounted molecular sieve oxygen production equipment in special vehicles: Firstly, the space and power supply capability shall be utilized effectively without affecting the operation and use of the original equipment of special vehicles. Secondly, the model of the vehicle-mounted oxygen production device is as uniform as possible from the aspects of use, guarantee, maintenance, and exchange of the oxygen production equipment. Thirdly, select the determined or verified products, which can fully meet the requirements on electromagnetic compatibility and environmental adaptability. Due to the particularity of gas leakage, the oxygen production effect of the oxygen production equipment shall be verified after the special vehicle has been installed with the equipment, and the following items shall be verified: rated power, air tightness of pipe, oxygen flow rate, oxygen concentration, oxygen outlet pressure of the humidification bottle and oxygen terminal.

References 1. Lv Y, Huo Z (2003) Extreme environmental physiology [M]. Military Medical Science Press, Beijing, pp 3–12 2. Feng Y (2014) Design of tank and armored vehicle—general design volume [M]. Chemical Industry Press, Beijing, pp 141–149 3. Yang G, Feng Z, Wang T (2003) The science of behavioral medicine in China [J]. The effect of plateau hypoxia on psychological function and its protection 12(4):471–473 4. Li H (2005) Oxygen making technology [M]. Metallurgical Industry Press, Beijing, pp 242–246 5. Feng Y (2014) Design of tank and armored vehicle—general design volume [M]. Chemical Industry Press, Beijing, pp 187–195

Study on Test Specification for Vibration Control of Heavy Vehicles Heping Wang, Mei Zhang and Xiaoyu Zhong

Abstract In this paper, the vibration status of a heavy vehicle is analyzed. On this basis, the road roughness tester is developed with the principle of triangular summation and the typical pavement. The road surface power spectrum and grade are analyzed, and the basis for vibration testing and evaluation is provided. At present, the testing standard of heavy vehicle vibration control is made early, and the test method and data processing method have lagged behind the development of modern signal processing and testing technology. The paper analyzes the above deficiencies and establishes a standard system for vibration control test of heavy vehicles. Keywords Heavy vehicle

 Vibration control  Test specification

1 Analysis of the Status of Heavy-Duty Vehicles Vibration The factors that cause the vibration of heavy-duty vehicles are mainly caused by the roughness of the pavement and the self-induced vibration caused by the power transmission system. For the tracked vehicles, the beat between the track and the ground is also one of the main reasons for the vibration of the vehicle, except for the roughness of the road. The frequency and intensity of this vibration are inversely proportional to the pitch of the main track and proportional to the vehicle speed [1]. The vibration frequency range of different vibration sources is shown in Table 1. At present, the vibration intensity of heavy vehicle is relatively high, especially to the thin-shell heavy-duty vehicle, the strong vibration often causes the instrument to be damaged in the vehicle, cracks to the heavy components, and even causes numbness of hands and feet of the personnel in the vehicle. The following tables show the vibration intensity of the main heavy-duty vehicles at the vertical direction on the sand road (Table 2). H. Wang (&)  M. Zhang  X. Zhong Beijing Special Vehicle Institute, Beijing 100072, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_78

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Table 1 Vibration frequency range of different vibration sources Vibration source

Road roughness

Power system

Track string function

Motor, etc.

Frequency (Hz)

0.5–20

80–250

30–70

>300

Table 2 Vibration intensity at main position of one vehicle Speed (km/h)

Transmission body Peak Mean square

Instrument support Peak value Mean square

Left deck limit block Peak value Mean square

30 40

6.07 11.60

2.60 3.75

12.91 7.97

0.99 0.92

0.31 0.36

1.60 1.20

As can be seen from the above table, the vibration intensity of heavy vehicle is relatively high when traveling on the off-road surface, and the root-mean-square value of vibration at different parts is over 0.5 g; the peak value is over 2 g and even over 10 g. Viewing from the power spectrum, the vibration caused by the track beating the ground accounts for the main proportion in the vibration component of the tracked vehicle, and the road roughness is the main factor for the vibrator of the wheeled vehicles.

2 Study on Test Technology of Pavement Characteristics of Heavy-Duty Vehicles The pavement roughness is the main cause of heavy-duty vehicle vibration. The main roads for the heavy-duty vehicle included paved road, undulating soil road, sandstone road, broken stone road [2]. The pavement spectrum reflects the undulating degree and the unevenness of the pavement, and when the data relating to the vibration and noise of the heavy-duty vehicle is tested, the pavement characteristics need to be measured and analyzed; namely, the undulating degree and the grade of the road shall be determined, thus providing data for vibration modeling and simulation. In this paper, with the triangle summation method, a pavement spectrum measuring device based on two principles of angle datum and inertial datum is developed, and the test system is mainly composed of two-track pavement measuring arm, gyro datum, sampling sensor, instrument, and data processing computer. The undulating degree of pavement is analyzed using the displacement power spectral density for pavement spectrum. In the spectrum, A, B … G, H are the grades of pavement according to international pavement standard, altogether 8 grades. Grade A is the best pavement; Grade H is the worst pavement; the attenuation index of each grade of pavement is 2, and the energy of adjacent grades of payment is 1 times different. After testing and analyzing, the high-frequency part of the pavement grade of the undulating soil road is Grade D, and the low-frequency part is Grade D–E;

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Fig. 1 Change of vibration on different pavements at the same speed

the high-frequency part of the sand and stone pavement is Grade D+, and the low-frequency part is Grade D–E. From the results of pavement grade and pavement power spectrum analysis, the worst of the road surface is Grade D+, the second grade of undulating soil road is class D, and the paving road is Grade B; the worse the road condition, the greater the vibration intensity of the vehicle, the more obvious the phenomenon of wheel type heavy-duty vehicle. Figure 1 shows the vibration intensity of the seats of driver and passenger of one-wheeled vehicle on different roads at the same speed. It can be seen from Fig. 1 when the driving speed is the same, the undulating degree and the hardness of the pavement increase, and the root-mean-square value of the vibration acceleration of the heavy-duty vehicle is greatly increased.

3 Analysis on Test Specification for Vibration Control of Heavy-Duty Vehicle At present, in the field of heavy-duty vehicle vibration control test and evaluation, there are mainly “Measurement of Human Body Vibration Environment,” “Limit and Evaluation Criteria for Comfort Reduction of Human Body Vibration Exposure,” and so on. The above criteria have preliminarily established the pavement, condition, test instrument, and personnel vibration comfort evaluation method for the vibration test of heavy-duty vehicles in the field test. But they were formulated a long time before and have lagged behind the development of modern signal processing and testing technology in terms of testing methods and data processing methods. In addition, these criteria in heavy-duty vehicle vibration test and evaluation are not related to the local body evaluation of human such as hands and feet, test and evaluation of vibration reduction index of vibration control system. Therefore, it is necessary to deeply study the vibration control and test system of heavy-duty vehicles, perfect the test and evaluation methods, and form a complete set of test and evaluation criterion [3]. The incomplete and unstandardized heavy-duty vehicle vibration control test and evaluation methods have influenced the design, test, data processing, and evaluation

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of the heavy-duty vehicle vibration control system and hindered the development process of the heavy-duty vehicle vibration control system. The main problems include: There are not the vibration control component performance index test evaluation criterion, impact vibration test, and evaluation criterion; the ergonomics evaluation standard and criterion are incomplete; version is out of date.

3.1

Impact Test and Evaluation Criterion of Heavy-Duty Vehicles

The impact vibration of heavy-duty vehicle is mainly caused by the instantaneous high-strength vibration caused by heavy-duty vehicle when driving at high speed and crossing the entrenchment, which are short in duration, but the impact strength is high, and the acceleration can reach several hundred and even thousands of Gs. Such high-strength acceleration not only affects the health and safety of personnel, but also damages the instrument and reduces the reliability and precision of the instrument, thus resulting in a decrease in the operational capability of heavy-duty vehicle. At present, there are few standards and criteria for impact vibration test, data processing, and evaluation methods of heavy-duty vehicles, which are conducted mainly referring the test methods or standards of ships, aircraft or rockets. The impact type and equivalent of these equipment are different from those of heavy-duty vehicles, and the test and evaluation methods of impact vibration of heavy-duty vehicles need to be established since they should not be conducted completely in accordance with these test and evaluation methods [4]. The impact vibration test and evaluation system of heavy-duty vehicles are shown in Fig. 2. The impact vibration acceleration to personnel cannot be evaluated simply by the response curve, and the cumulative effect of impact vibration must be taken into account. The impact vibration takes acts in different aspects to the human body, and the evaluation and calculation methods are also different. The main evaluation methods are as follows: (1) the acceleration tolerance limit in the direction of spine, mainly the function of acceleration pulse and duration, and the acceleration here refers to uniform acceleration and (2) the acceleration tolerance limit toward the sternum and head direction, which is a function of the pulse amplitude and duration.

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Study on the Test and Evaluation Criterion for Cabin Environment Vibration of Heavy-Duty Vehicles

At present, the man–machine environment evaluation of heavy-duty vehicles mainly refers to the “Measurement of Human Body Vibration Environment,” in which the 1/3 phase-weighted acceleration root-mean-square value is applied and “Fatigue-Reduction of Ergonomic Limits” allowed exposure time are adopted to

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evaluate the ergonomics of the seats. The above standards refer to ISO2631/1-1985 Standard. This standard evaluates the effect of body vibration on human body by the relationship between four basic vibration parameters including the effective value of vibration acceleration, vibration direction, vibration frequency, and vibration duration. According to the feeling of the recipient, the root-mean-square value of acceleration is adopted to give three different artificial boundaries in the frequency range of 1–80 Hz of the center frequency: comfort reduction limit, fatigue work efficiency limit, and exposure limit. The main problem is that the human body is subject to the quantitative value of the boundary and limit of the whole-body vibration, and there is a dispute; the individual difference, motion sickness, etc., of the person’s response to the vibration are not sufficiently taken into account in the standard, and the evaluation standard is not perfect in the aspects of vibration perception, comfort, and so on. The new standard has been modified as the followings compared to the old standard [5]: (1) Delete the concept of “Fatigue-Reduction Ergonomic Limits.” (2) Establish the evaluation standard of human body on bearing whole-body vibration in the aspects of vibration to human health, comfort, vibration perception, motion sickness, and so on. (3) The quantitative index of the boundary and limit of the whole-body vibration. (4) Different evaluation methods are adopted for different conditions for vibration evaluation, and the applicable conditions are specified.

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The vibration evaluation at prone position is mainly used for evaluating the armored ambulance, mainly involving in measurement methods, measurement instruments, and evaluation method. The sensor pad is closely combined with the human body and is mainly used for measuring the vibration of the head and the hip. The evaluation method mainly includes main frequency-weighed acceleration to evaluate the six-level comfort to vibration. The local vibration of hand and foot is mainly used to test the vibration control of lever and pedal of heavy-duty vehicle. It mainly includes the installation method and testing direction of sensors. The evaluation method is mainly the daily vibration quantity, three axial directions shall be measured, and the highest axial acceleration shall be used as the evaluation reference. Motor sickness metering value is mainly used to evaluate the incidence of motion sickness.

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Method for Evaluating Vibration Damping Performance of the Vibration Control Part of Heavy-Duty Vehicles

The vibration isolation index of the general vibration control parts is represented with vibration isolation efficiency: T ¼ ð1  TA Þ  100%

ð1Þ

TA is the absolute bit transfer coefficient, the ratio of the amplitude value of the transmission force (acceleration) transmitted to the base through elastic support and the disturbing force of the object itself, the ratio of the vibration amplitude value of the elastic support and the amplitude value of the base itself, or the ratio of the vibration velocity and the acceleration.

TA ¼

M0 V0 a0 ¼ ¼ M V a

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No matter how large the frequency ratio n is, only when the frequency ratio is pffiffiffi [ 2, TA will be less than 1. Therefore, the selection of the natural frequency of pffiffiffi the elastic support system must satisfy xxn [ 2 condition for the purpose of vibration isolation. Because of the presence of damping, the TA value varies with pffiffiffi frequency, and all TA curves intersect at xxn ¼ 2 point.

x xn

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi h  i2 u u 1 þ 2n xxn u TA ¼ u u  2 2 h  i2 t 1  xxn þ 2n xxn

ð3Þ

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At present, there is nearly no criterion for testing and evaluation of vibration control system components of heavy-duty vehicles such as vehicle body suspension, shock absorber, metal rubber, etc., and the performance evaluation of these vibration control systems cannot be met comprehensively by the index of vibration isolation efficiency alone.

4 Conclusions (1) The undulating characteristic of pavement reflects the vibration intensity of heavy-duty vehicles; in this paper, the trigonometric summation is adopted to study the pavement spectrum test and has tested and analyzed the typical pavement spectrum of heavy-duty vehicles, which has provided the data and reference for the vibration analysis and simulation of heavy-duty vehicles. (2) According to the situation of incomplete test criterion for the vibration control test of heavy-duty vehicles, this paper has analyzed and built the heavy-duty vehicles’ impact vibration control test criterion frame, heavy-duty vehicle man– machine ring cabin vibration test criterion frame, vibration control components performance test, and evaluation criterion frame, which have provided the idea and reference for the formulation of the vibration control test criterion of heavy-duty vehicles.

References 1. Sun Y, Wang X (2008) Explosion shock wave on human body injury and protection research or explosives. J 31(1):50–55 2. Zhang Y, Zheng X (2008) Energy feedback type electric suspension principle and experimental research. Automot Eng 30(1):48–54 3. Liu H, Li R (2008) Research and development of engine vibration isolation control technology. Veh Engine 175(3):1–9 4. Lang to enter, Zhou Y (2011) Cheng country. A new formula system transmission in the vehicle gearbox performance evaluation, lubrication and seal 36(2):114–117 5. Harris CM (2008) Harris, shock and vibration handbook

The Multiple Classification Method of Signal Recognition for Spacecraft Based on SAE Network Wei Lan, Yixin Liu, Zhang Qi, Shimin Song, Chun He, Lijing Wang and Ke Li

Abstract Based on deep learning, a multi-classification algorithm network is designed for the large amount of data generated in spacecraft test. In the algorithm, the initial offsets and weights of a multi-layer neural network are initialized using an auto-encoder method. The initialized parameters are monitored by the gradient descent method to make the dimension data more separable. Many shortcomings of traditional algorithms can be effectively overcome using this algorithm. For example, the storage space can be reduced and the calculation time can be saved when the data is large or complex. Expert knowledge of the spacecraft health management platform can be provided through the study of measured data. Experimental data shows that the depth learning algorithm which is based on SAE has higher accuracy in spacecraft multi-class signal testing.

 



Keywords PHM Deep learning Auto-encoder Data compression Deep belief network

 Pattern recognition

1 Introduction In spacecraft launch and operation, forecasting and health management play an important part, improving the safety and reliability of spacecraft as well [1, 2, 3]. The decision support layer and the spacecraft health assessment layer both need to combine the pattern recognition algorithm with expert system data and current data W. Lan University of Aeronautics and Astronautics Beijing, Beijing 100191, China Y. Liu  Z. Qi  L. Wang  K. Li (&) Fundamental Science on Ergonomics and Environment Control Laboratory, School of Aeronautics Science and Engineering, Beihang University, Beijing 100191, China e-mail: [email protected] S. Song  C. He China Academy of Space Technology, Beijing 100094, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_79

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to forecast fault signal and reliable instruction [2, 4]. In expert system, the information is mostly extracted from the raw data based on the machine learning system, so knowledge acquisition becomes a restriction [5]. Deep learning uses a multi-layer neural network with good learning ability [6, 7]. Its application has been very successful in many fields such as computer vision and speech recognition. Deep learning solves the gradient divergence problem when the gradient descent method is used to train the multi-layer neural network with the layered initialization method [8–11]. While preserving the characteristics of self-organization, selflearning, and massively parallel computing in shallow networks, deep learning gets more core content from large data. This paper introduces data analysis of deep learning technology in the aerospace field, extracts the main characteristics of the original spacecraft data for the first time and classifies and proposes using traditional algorithms [12–14]. A depth-based multi-class classification algorithm is used to study spacecraft signal prediction and health management [15, 16].

2 System and Algorithm Multi-channel data acquisition and fast acquisition of each channel are both necessary in the fault diagnosis system for satellites. Fifty channels of data are detected by a satellite from China, and each channel’s acquisition rate is greater than 30 MB/s. But we may only care about a few of them. Other data was stored in the Oracle database for later use. Combined with the characteristics of the neural networks, the following learning system is proposed, as shown in Fig. 1. This chart consists of three steps: data acquisition, electronic graphic coding, and network training. The raw data is obtained from the offline data stored in the ground station database, which comes from different channels and from various events. Throughout the process, we can perform real-time network training as well as call the prepared network for troubleshooting. The main characteristics of the raw data are extracted from the trained network and classified by other traditional classification algorithms. The basic network structure, network parameter initialization, and optimization training are discussed below.

2.1

The Basic Structure of Network

Deep learning is a subtler level, in the shallow form of neural networks. The deep learning network is able to study more features of the data and fit complex nonlinear problems accurately at the same time. A deep learning network is introduced in this paper as shown in Fig. 2. The network consists of three parts: an input layer, a hidden layer, and an output layer. In order to initialize the network parameters using the tag samples, the last hidden layer and the output layer are connected to the logistic regression. The

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number of neurons in the input and output layers is decided by the sample dimensions and the number of sample tags. Implicit layer nodes are obtained from empirical formulas. The network hidden layer of this paper is 4, and the network structure is 103–80–60–40–20–6. The hidden layer activation function selects sigmoid as (1). f ðxÞ ¼

1 1 þ ex

ð1Þ

More hidden layers bring more detailed description of the characteristics of the data, so that more information can be got. But more hidden layers will increase training time, and the memory usage of the computer will be more. While not increasing the training time and memory usage, this paper designed the experiment of the accuracy of different network structures with the number of cycles. The network structure is 103–50–6, 103–80–60–40–20–6, 103–90–80–70–60–40–20 in sequence. After the network training is stable, the classification accuracy is about 97% when the network depth is 103–50–6 and about 98% for the other two kinds of network depth. Therefore, the depth of the network is about deep; that is, the more the hidden layers, the higher the classification accuracy. When the network depth increases, the training time and memory usage will increase at the same time. In order to save computing time and computer hardware resources while ensuring classification accuracy, the deep learning network structure selected in this paper is 103–80–60–40–20–6. In addition, for different datasets, the optimal network structure is often different. And by adjusting the initial parameters, different

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network structures can also have the same level of classification accuracy; there is still no theoretical support in the face of optimal network structure selection, which can only be obtained through experiments.

2.2

Network Parameter Initialization

The entire network is trained with an iterative algorithm to overcome the gradient diffusion problem. The method of weight initialization and offset deep learning is to train layer by layer, so the output of the upper layer is used as input for the next layer. The parameters of each hidden layer between the networks need to be initialized by an automatic encoder or a deep belief network. Using sample labels and gradient descent methods, weights of the network can be fine-tuned. After s network is trained, the output of each hidden layer is a mapping of raw data, so it can be directly classified by other algorithms [17–21]. The automatic encoder method [8, 22] can initialize the network weights with the original data. Then, the network weights can map the key features of the original data better. The basic flow of automatic coding is as follows: First, the encoder compiles original signal into code. Then, the code is converted to a reconstructed signal by a decoder. At last, the encoder and decoder parameters [8, 9, 22–26] are modified inversely by the error between the reconstructed signal and the original signal. Finally, several automatic encoder methods are used to implement the stack auto-encoder. The equations of encoding and decoding method are as follows: Om ¼ Wmn  Xn þ B

ð2Þ

Yn ¼ W1nm  Om þ B1

ð3Þ

where m is the neurons number of hidden layer, and n is the dimension of training samples. Select the error of the training sample and the reconstructed data as a penalty function: error ¼

n X

jXi  Yi j

ð4Þ

i¼1

The basic process of the algorithm: (a) Step 1: Take the training sample as input. (b) Step 2: Cut down the dimension of the training sample using the encoder, wherein the number of hidden layer neurons is equal to the dimension of the new data.

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(c) Step 3: Convert the new data into reconstructed data through the decoder. (d) Step 4: Compute the error between the reconstructed data and the training sample. (e) Step 5: Minimize the reconstruction error by modifying the parameters of the encoder and decoder. (f) Step 6: Take the initial weights of the ANN input layer and the hidden layer as final weights.

3 Simulation 3.1

Acquisition of Data

Selected 19 different kinds of signals and manually adding sample label from the 13th mode of a spacecraft flying data, we obtain 22,400 samples with 1000 features contained in each of them; the physical meaning of the part of the data is shown in Fig. 3. Using 16,000 samples of original signal for training and 6400 for testing, before input the network, the original data was normalized.

3.2

Classification Accuracy Change with Sample Size

The number of classes and cycles influent classification accuracy. As shown in Fig. 4. The deep learning network can effectively compress the original data after initialization, extracting the main features, but it cannot be directly used for classification [27–30]. Therefore, fine-tuning the initialized parameters using the marked samples is necessary. It can guarantee the convergence of the network, but it will increase the training time and reduce the efficiency of the algorithm, because the number of fine-tuned samples or cycles is too much. In order to find the optimal fine-tuning samples of the dataset we used, we designed an experiment in which the classification accuracy changes with the size of samples. Classification results obtained are as shown in Fig. 5. When the number of classes is small, various algorithms can achieve high classification accuracy. For example, if the class is less than 8, the classification accuracy of the two deep learning networks can approach 100%. The classification accuracy of different algorithms will decrease when the number of classes rises. The results show that the classification accuracy of K-nearest neighbor, support vector machine, and naive Bayes is significantly reduced. At the same time, the depth learning algorithm reduces the classification accuracy significantly lower than other algorithms. And by increasing the number of loops to offset the impact of the reduction, deep learning increases the classification accuracy.

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The classification count will decrease if the feature dimension of the sample is too big, causing a dimensional disaster. The reduced size of the sample not only increases the speed of operation, reduces memory usage, but also improves classification accuracy. Kernel-based principal component analysis and nonlinear dimensionality reduction methods have been widely used in engineering; the former is not suitable for dimensionality reduction of nonlinear separable samples; on the contrary, the latter is solved by projecting into high-dimensional space to solve nonlinearity. Divide the problem, thereby increasing the computational complexity of the computer. The deep learning initialization process is unsupervised, that is, greedy to learn data features from bottom to top, without supervision, so the extracted features can well fit the original signal, improve the segmentation of data,

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Table 1 Classification accuracy variation chart for dimension reduction data Method

Raw data (%)

Compressed data DBN (%)

SEA (%)

KNN NBM SVM LR

79.67 80.26 82.97 –

97.42 81.27 90.12 90.09

97.46 85.55 90.98 91.77

Table 2 Memory usage and training time variation chart for dimension reduction data Method

Memory usage (MB) Raw data Compressed data

Total running time (SEC) Raw data Compressed data

KNN NBM SVM

787 952 875

21.42 98.18 33.58

523 633 595

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and effectively avoid the dimensional disaster. And in this paper, as an input to other algorithms, features are extracted from the last hidden layer of depth tilt. Table 1 provides the classification accuracy of different classification algorithms. Table 2 provides running time and the memory usage. From Table 1, it can be seen that the classification accuracy of the original data is significantly lower than the dimensionality reduction data. K-nearest neighbor classification accuracy is significantly improved because K-nearest neighbors are based on linear separable theory. Compared with DBN and raw data, the data compressed by SAE method have higher classification accuracy. Table 2 gives that the deep learning algorithm extracts 50 features from 1000 features, which save both the memory footprint and total time of the program. Through simulation, the classification accuracy and separability of the data are improved, and the calculation time taken to extract the main features of the raw data by using deep learning is saved.

4 Conclusion This paper introduces the general procedure of satellite fault diagnosis based on SAE deep learning network; the main feature of raw data extraction is the use of two different deep learning strategies. Experimental data shows that through reasonable training, deep learning techniques can still achieve higher classification accuracy when there are large samples and multiple tags. This algorithm can be directly used in satellite fault diagnosis by training the original data of the spacecraft. The accuracy, convergence speed, and stability of the algorithm are improved. At last, the deep neural network algorithm has a simple structure. It shows great

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flexibility and adaptability to data with specific rules and ambiguities. In-depth study of deep neural networks combined with other algorithms can improve the accuracy and real time of satellite fault diagnosis. The deep belief network and stack auto-encoder designed in this paper are very simple. There is still room for improvement in this method. Acknowledgements The authors are supported by the Aeronautical Science Foundation of China (No. 2017ZD51043), the Chinese National Natural Science Foundation (No. 61773039), Fundamental Research Funds for the Central Universities (No. YWF-14-HKXY-017, YWF-13-HKXY-033), and ‘Fanzhou’ Youth Scientific Funds (No. 20100504).

References 1. Luo R (2013) Analysis of PHM technology for spacecraft. Spacecr Eng 2. Bing L, Sun Z, Jiang X (2003) A study of integrated vehicle and ground health management technology for spacecrafts. Aerosp Control 21(2):56–61 3. Batzel TD, Swanson DC (2009) Prognostic health management of aircraft power generators. IEEE Trans Aerosp Electron Syst 45(2):473–482 4. Gang-De LV, Yang ZC (2011) Study on prognostics and health management system modeling technology. Measur Control Technol 5. Xin MA (2008) Knowledge acquisition methods for expert systems based on machine learning. J Beijing Univ Chem Technol 35(5):89–93 6. Lin Z, Jia Y (2016) Neural network-based distributed adaptive attitude synchronization control of spacecraft formation under modified fast terminal sliding mode. Neurocomputing, 171(C):230–241 7. Hinton GE (2006) Reducing the dimensionality of data with neural networks. Science 313 (5786):504–507 8. Hinton GE, Osindero S, Teh YW (2006) A fast learning algorithm for deep belief nets. Neural Comput 18(7):1527–1554 9. Bengio Y (2009) Learning deep architectures for AI. Found Trends® Mach Learn 2(1):1–127 10. Rodrigues LR, Gomes JPP, Ferri FAS, Medeiros IP, Galvão RKH, Júnior CLN (2015) Use of phm information and system architecture for optimized aircraft maintenance planning. IEEE Syst J 9(4):1197–1207 11. Xu J, Wang Y, Xu L (2014) PHM-oriented integrated fusion prognostics for aircraft engines based on sensor data. IEEE Sens J 14(4):1124–1132 12. Anand IM (2014) Reverse multiple-choice based clustering for machine learning and knowledge acquisition. In: International conference on computational science and computational intelligence, vol 1, pp 431–436. IEEE 13. Liu Y, Li K, Huang Y, Wang J, Song S, Sun Y (2014). Spacecraft electrical characteristics identification study based on offline FCM clustering and online SVM classifier. In: International conference on multisensor fusion and information integration for intelligent systems, pp 1–4. IEEE 14. Li K, Liu Y, Wang Q, Wu Y, Song S, Sun Y et al (2015) A spacecraft electrical characteristics multi-label classification method based on off-line fcm clustering and on-line wpsvm. PLoS ONE 10(11):e0140395 15. Liu Y, Li K, Song S, Sun Y, Huang Y, Wang J (2015). The research of spacecraft electrical characteristics identification and diagnosis using PCA feature extraction. In: International conference on signal processing, vol 53, pp 1413–1417. IEEE

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16. Li K, Liu W, Wang J et al (2014) Multi-parameter decoupling and slope tracking control strategy of a large-scale high altitude environment simulation test cabin. Chin J Aeronaut 27(6): 1390–1400 17. Wersing H, Körner E (2014) Learning optimized features for hierarchical models of invariant object recognition. Neural Comput 15(7):1559–1588 18. Zabalza J, Clemente C, Caterina GD, Ren J, Soraghan JJ, Marshall S (2014) Robust PCA micro-doppler classification using SVM on embedded systems. IEEE Trans Aerosp Electron Syst 50(3):2304–2310 19. Keerthi SS, Shevade SK, Bhattacharyya C, Murthy KRK (2014) Improvements to Platt’s SMO algorithm for SVM classifier design. Neural Comput 13(3):637–649 20. Chen H, Chang KC, Chen H, Chang KC (2008) K-nearest neighbor particle filters for dynamic hybrid bayesian networks. IEEE Trans Aerosp Electron Syst 44(3):1091–1101 21. Yu C, Ooi BC, Tan KL, Jagadish HV (2001) Indexing the distance: an efficient method to knn processing. In: Vldb 22. Carmona PL, Sánchez JS, Fred ALN (2014) Editorial: advances in pattern recognition applications and methods. Neurocomputing 123:1–2 23. Li K, Liu W, Wang J, Huang Y (2013) An intelligent control method for a large multi-parameter environmental simulation cabin. Chin J Aeronaut 26(6):1360–1369 24. Martínez AM, Kak AC (2001) PCA versus LDA. IEEE Trans Pattern Anal Mach Intell 23(2):228–233 25. Thomas S, Seltzer, ML, Church K, Hermansky H (2013) Deep neural network features and semi-supervised training for low resource speech recognition. In: IEEE international conference on acoustics, speech and signal processing, pp 6704–6708. IEEE 26. Luus FPS, Salmon BP, Bergh FVD, Maharaj BTJ (2015) Multiview deep learning for land-use classification. IEEE Geosci Remote Sens Lett 12(12):2448–2452 27. Zhou XY, Tian XW, Lim JS (2015) Fuzzy naive bayesian for constructing regulated network with weights. Biomed Mater Eng 1(s1):1757–1762 28. Zhang X, Hao S, Xu C, Qian X, Wang M, Jiang J (2015) Image classification based on low-rank matrix recovery and naive Bayes collaborative representation. Neurocomputing 169:110–118 29. Friedman J, Hastie T, Tibshirani R (2000) Special invited paper. Additive logistic regression: a statistical view of boosting. Ann Stat 28(2):337–374 30. Pregibon D (1981) Logistic regression diagnostics. Ann Stat 9(4):705–724

Part VIII

Theory and Application Research

Evaluation on the Design of Man-Machine-Environment System of Interactive Experience Space in Library Kunzhu Zhang, Liyan Tan and Yang Liu

Abstract In order to evaluate the design of man-machine-environment system of interactive experience space of Tsinghua University Library, this paper establishes an evaluation system based on user survey method and 13 classical principles of human factors. All the factors are divided into two categories: interface and non-interface. The Space arrangement, size layout, display design, and features of human–machine interaction are examined to evaluate the comfort, convenience, accessibility, and visibility, and to find possible improvements. The established evaluation methods and analysis results may provide certain reference for the humanized enhancement of the interactive experience space of library.



Keywords Library Man-machine-environment system Man–machine interaction Evaluation



 Man–machine interface

1 Introduction Library is a public space for cultural education and also a typical and complete human-machine-environment system. Humanization will be the new highlights of library human–computer interaction. It is a very practical research to see how to display the library’s cultural features and resource advantages in a smarter, more innovative, and more attractive way. In April 2016, the interactive experience space of “Tsinghua Mark” (“the Space” for short) was officially launched at the Tsinghua University Library. This space is the first of its kind in domestic university libraries, similar to but different from the maker space. This space is an important exploration of using new technologies to create more humanized and intelligent library functions. K. Zhang (&) Tsinghua University Library, Beijing 100084, China e-mail: [email protected] L. Tan  Y. Liu Department of Industrial Engineering, Tsinghua University, Beijing 100084, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_80

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In recent years, the construction of the library maker space has become a hotspot [1–6]. To take American library maker space for example, researchers believe that the American library maker space has expanded the service area of the library, showing the significance of the existence of the library and enhancing the overall innovation capability of the society. This paper takes module design of the Space as the research object. By field surveys, user surveys, man–machine experiences, and other methods, this paper deeply studies the mode and content of the human–computer interaction of the Space module, and analyzes humanized functions and interface. This paper puts forward the idea and exploration of humanization and intelligent improvement, in order to promote the humanization of the human-machine-environment system of the library, providing references to the practical research and development of the intelligent function of the library.

2 Methods 2.1

Investigated Objects

The Space of “Tsinghua Mark” includes six modules as following (Fig. 1); 1. History of the library. Seven push–pull planks visually reflect the history of Tsinghua library. Each plank shows a significant event over a hundred years. 2. E-book borrowing screen. Six e-book borrowing screens are loaded with most popular books and presented by digitization. With quantities information like waterfall, users can acquire the whole text in PDF by scanning the QR Code.

Fig. 1 “Tsinghua Mark” interactive experience space

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3. Digital Humanities. Four representative collection replicas printed through 3D printing technology are displayed in library permanently. Users can find introduction and check spinning 3D model of the collections through scanning QR Codes. Users can get it through scanning. 4. Historical corridor. Eight digital screens compose the historical corridor of Tsinghua by presenting the Tsinghua weekly digital journals from 1916 to 2016. Journals roll transversely with the time axis. Users can click one to read online or on mobile devices through the QR code. 5. Digital scholarship. The main part is a screen employing document digital sources and visual tech to present the document published accomplishment of Tsinghua and documents by the famous colleges and the countries joined documents through a thermodynamic chart. Documents in the core journals by people in Tsinghua in the Republic of China era are also showed in this area. 6. Moments in Tsinghua. Signature and photograph imprinting interaction are settled in this area, using image matting and combining tech to put the user’s photograph shot on the spot into the Tsinghua building and the celebrities in history, and shadow the written word mementoes as leaves on the memory tree.

2.2

User’s Experience Investigation

Aiming at the six parts, we design a task list including seven tasks letting the users who visit the Space for the first time join the experiencing task and fill the chart. Table 1 shows the tasks and related result. Table 1 Note the content and result of the users experience investigation Module

Task content

Users’ response

1

Find the big event of the Tsinghua library in 1996 Find a book with regard to the technology or economic subject and read the first three pages

Uneasy to find the hiding function and need to add the prompt information The books drop randomly without classification badges and searching function. It is so slow for the phone to get the book A good decoration

2

3 4

5

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Observe the work of the 3D printing, calligraphy, and painting Find any Tsinghua weekly in 1918 and read the first three pages Find the amount of jointed document published by Tsinghua and the USA in 2011 Take a photograph with Tsinghua and preserve it on the phone

The identifiability of the page-turning button and the sensibility of LCD Touch Screen should be improved Lack of sensibility of the touch reaction and some unobvious buttons The unobvious place and restricted background source and the failure of the scan

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Evaluation Method

Usability is an important quality indicator for interactive IT products/systems. ISO 9241 defines availability as “the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction in a specified context of use.” Quesenbery’s 2001 also have 5Es, which are “Effective, Efficient, Engaging, Error tolerant, Easy to learn,” which link availability and user experience in five dimensions [7]. In the Space, it seems that “Effective, Engaging, Easy to learn” are the most important to mobilize users’ interests to find out what they want. Combining with the reality of the interactive experience space, we divide the factors affecting human–computer interaction into two categories: interface and non-interface. This study mainly focuses on the evaluation and improvement of interface design. While in the design of non-interfaces, human factors give some principles, including size, spatial layout, lighting. We evaluate the existing non-interface design according to light, sound, size, and layout, based on the classical theory related to human factors. In the evaluation of the interface design, we focused on the existing deficiencies and improvements in the existing interface design, but also pointed out the advantages of the existing interface design in the usability and user experience. We combined the results of user testing, expert evaluation, and commonly employed principles in the Heuristic Evaluation to reach the conclusion. We have selected 13 principles (Simplicity/Mapping/Consistency/Feedback and responsiveness/ Predictability/Clear Exits and closed dialogs/Minimize memory load/Flexibility and Efficiency/Error prevention/Error recovery/Diverse needs/Help and support/ Aesthetics) [8] to evaluate the interactive interface of the interaction space to find out whether the existing interface is rational design and make suggestions for further improvement.

3 Results 3.1

Interface Analysis

The usability of interface has significant influence on satisfactory of user experience. According to the results of usability test, the Space has some advantages, while the disadvantages especially for digital humanities are worth attention. Totally, the Space has some advantages: (Interface structure) reasonable navigation interfaces help users enter different parts; (Interactive tools) touch screens enhance interactive experience; (Function expansion) two-dimensional codes expand functions which are not restricted by the touch screens; (Content features) the characteristics of Tsinghua are very prominent.

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As an important breakthrough which to found the improvement points, the disadvantages of interface can be described in detail.

3.1.1

Tsinghua Memories

(1) Flexibility and Efficiency. After users clicking on the confirmation icon to take pictures, the interface will prompt “Please turn right in front of the camera.” One picture will be taken in 3 s, but the time to prepare for taking pictures is too short to allow users to get ready. However, two much preparing time will cause waste of time. So, we advise giving users 6 s or allowing users to choose ready time themselves. (2) Aesthetic. The signature function allows the user to write his or her own name on the screen, and then he or she can share the signature. But the lack of background makes the signature too monotonous to highlight the elements of Tsinghua. It is suggested that it can allow users to choose typical landscape of Tsinghua University, such as school gate and auditorium freely as the alternative background so that more Tsinghua elements can be incorporated, and the value and beauty of signatures can be improved.

3.1.2

E-Book Lending Screen

(1) Consistency. The speed and the size of the books’ covers keep changing which causes inconvenience for users’ reading and easily causes users’ visual discomfort and fatigue. It is recommended to fix the size and speed of the pictures, but it allows different cover to have different sizes. (2) Help and support. Click on the book cover, users can see the book introduction, but there is little about the contents. Users cannot get enough information. It is suggested to add content profiles and catalogs. The digital humanities part lacks a description of the functions, and some users may not know how to operate. It is suggested to add guidance and instructions. (3) Flexibility and Efficiency. Under current design, it is almost impossible if users want to find a specific book. Users can only choose books that appear in the screen, which is inefficient and not flexible enough. It is suggested that a search function should be added.

3.1.3

Tsinghua Weekly

(1) Mapping and Error prevention and Predictability. In the weekly reading screen, if the user wants to turn to the next page, he or she should click the triangle icon to the left, which violates most users’ operating habits. There is a similar

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problem of reading in the mobile phone. Users need to slide to the left of the screen to enter the next page. This kind of unconventional design causes trouble for users to turn to the next page. It is recommended that the switch to the next page should be designed to click on the right triangle or slide the phone screen to the right. (2) Predictability. In the weekly reading interface, clicking on the lower left corner of the book can turn to next page, but there is no hint of this function. It is difficult for the reader to find it. (3) Simplicity and Predictability. At the weekly access interface, there are two icons “^”, “_”. In general design, this kind of icons links the previous or the latter interface. Most users think clicking icon “^”, “_” can enter the interface of the weekly of the last year and the next year. Actually, there is no response. It is suggested to delete the two icons to avoid unnecessary operation.

3.1.4

Digital Humanities

(1) Consistency. In the “The International Co-authorship of Tsinghua University” interface, the different colors of dots in different capitals represent different amounts of co-authors on the map, but the dot area is too small to identify the cell color, it is difficult to provide accurate and sufficient information, which is insufficient for the readers. It is suggested to color the countries on map instead of just coloring the capital of countries so that users could easily tell different amounts of co-authors on the map. (2) Clear exits and closed dialogs. In the “The International Co-authorship of Tsinghua University” interface, users need to exit from the full screen first to return to the home page. Withdrawal from full screen mode should be based on the long press on the map icon. The operation is difficult to be known and too complex which causes great difficulties for users to return to the home page. It is recommended to add a return icon linking to the home page. (3) Simplicity and Predictability. The three circular icons in “Tsinghua top papers” interface, including birthplace division, age division, and educational background division, do not link to different classification interfaces, which mislead users to click. It is recommended to cancel these three icons. (4) Predictability. In the “Tsinghua top papers” interface, the hyperlinked text lacks characteristics different from general text such as the “Nature,” “Science,” and “SCI” in the lower right corner and the category of subjects in the pie chart (such as “biology,” “chemistry,” “physics”). Most users cannot realize that these text link to corresponding articles. It is recommended to adopt a specific format for hyperlinked text. In the interface of displaying information such as the title of the article, clicking the article information can show the author’s profile. But this function is difficult to find by the users. It is suggested to add prompting text. In this module, some similar problems about predictability can be found.

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Non-interface Analysis Light Factors

(1) Lighting of exhibition space. Considering energy conservation and the fact that people are accustomed to uniform pipelines, the exhibition area adopts integrated lighting. It uses artificial light sources in combination with natural light sources, composed by comprehensive lighting and local lighting [9]. Three sets of vertical LED lights are set on the ceiling to illuminate the interactive space as a supplemental light source at night or on cloudy days, thereby improving the economics of the design. In the digital humanities area, spotlights were set up to cast light on the history of each exhibit, which increased the brightness of the pavilion’s field of vision, allowing the users to have a clear vision and level perception during the visit, and to obtain a satisfying satisfaction. (2) Lighting of the video display terminal. The difference between the video display terminal and the traditional visual information source is that it emits light in addition to the light absorption display. Since the video display terminal is mostly a mirror-like glass material, it is particularly susceptible to external light illumination and causes reflection [10]. Therefore, in the vicinity of the digital display terminal, the illumination level and the brightness ratio between the screen and the surrounding area need to be reduced to avoid the glare effect. Also, in order to avoid reflection on the screen, it is necessary to change the relationship between the reflection source and the screen as much as possible, such as shielding the window, moving the screen direction, or tilting the screen. In the e-book borrowing screen area, in order to enable the six cascade flow screens to display with high contrast and avoid reflection, the screen posts are placed at an angle of 35° to the windows, and the windows are also treated with a dark color filter film to treat sunlight, weakening to ensure high-definition display screen. (3) Illumination of the imaging area. Glare is caused by the fact that the brightness in the visual range far exceeds the brightness to which the eye adapts, and it causes visual impairment [10]. If you use a normal flash camera, readers use the Tsinghua imprint to synthesize photographs. The photo flash at the time of shooting is strong, and it easily causes glare to the reader. In order to avoid glare, the Tsinghua Sealed Area uses a white LED lamp on the top of the head to ensure adequate light and no shadows in the imaging area.

3.2.2

Acoustic Factors

As an interactive experience area, this space needs to reduce noise. In the area of the historic promenade, a 3-cm-thick chemical fiber plush carpet is laid on the floor, which absorbs footsteps and other noises effectively, enhancing the intimacy of

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users. The spliced seats scattered throughout the Space are also materials that absorb external noise and improve the comfort of the Space.

3.2.3

Size Factors

(1) The visual height of the vertical screen. A person’s vertical field of view has an angular range. If we set the standard horizontal line of sight to be 0°, the maximum viewing area is 50° above and 70° below the standard eye level. In the interactive space, people are mostly standing. At this time, the natural line of sight of a person is lower than the horizontal line by 10°. When it is extremely relaxed, it deviates from the standard line of sight by 30° [9]. According to the National Body Size Standards Document (taking 95th percentile into account), the eye height of males 18–60 years old was 1664 mm, and the height of eyes of 18–55-year-old females was 1541 mm [11]. The comfortable distance from the vertical screen was about 450 mm. By calculation, the human sight range is 366–2138, and the natural line of sight is 1526. The heights and disappearance heights of the e-book reading were 260 and 17, both of which exceeded the range, thus giving people rich books and a strong visual impact. (2) Operational height of the vertical screen. Based on ergonomic design, the screens are set between the heights of an average standing person’s elbows and shoulders, and between his/her viewing angle of 15 degrees in elevation and 30 degrees in depression. The heights of QR codes on the e-book lending screen and historical promenade are 1650mm and 1560mm, respectively, and the e-books have an exit button height of 1750 mm, which exceeds the comfortable operation area. (3) Operating range of the horizontal screen. The operating area of the horizontal work surface should be within the reach of the convenient arm [10]. The digital academic platform is tilted at 19.5°, while its large screen of 187 cm long and 120 cm wide, and the dispersed buttons are beyond the scope of the largest work area. Thus, users have to move to touch the button. At the same time, the diameter of the circular button in the screen is 1.3 cm, which almost coincides with the diameter of a finger of adult. It is inconvenient to operate. Therefore, the button should be adjusted in size and distribution.

3.2.4

Layout Factors

(1) Routing. The route arrangement adopts a counterclockwise direction of travel and does not intersect or repeat. Users enjoy an abundant journey of viewing every part of this space with a short and smooth route.

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(2) Spatial hierarchy. The six screens of the e-book borrowing screen are arranged at an angle of 15° to the wall surface so that each screen can be seen at a glance. The depth of space and the sense of depth are improved.

4 Conclusion Combining users’ task feedback with theoretical analysis, this paper draws the following conclusions. (1) Strengthen the design of prompt signs, and make it clear for users to clarify the use of each function in each area. (2) Consider the actual demands of users and develop search functions when information is complicated. (3) Fit the actual human body standards and cater to users’ fixed habits, and always remember to create a comfortable operating experience. This study provides methods and examples for the evaluation of related humanmachine-environment systems and also provides reference for the construction of type digital experience spaces in a library. Acknowledgements This paper was supported by Students Research Training Project of Tsinghua University (1812T0156). Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Tsinghua University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Hatch M (2014) The maker movement manifesto: rules for innovation in the new world of crafters, hackers, and tinkerers. McGraw-Hill Education, New York 2. Burke JJ (2014) Maker spaces: a practical guide for librarians. Rowman & Littlefield, Lanham 3. Hamilton M, Schmidt DH (2015) Make it here: inciting creativity and innovation in your library. Libraries Unlimited, Santa Barbara, California 4. Wang F (2016) The practice and evaluation of the building of a maker space in the American library. Inner Mongolia Sci Technol Econ 2:127–128 5. Gao P (2016) Research on the evaluation of the maker space project in the University library. Inner Mongolia Sci Technol Econ (14):147–148 6. Chai Y, Du W, Liu X (2016) The construction and application of the evaluation index of the service quality of the maker space in University library—taking the library of Xi’an Aviation College as an example. Libr Res 46(2):46–50

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7. Quesenbery W (2001) What does usability mean: looking beyond ‘Ease of Use’. In: Proceedings of the 48th annual conference, Society for Technical Communication 8. Stone D, Jarrett C, et al (2005) User interface design and evaluation. Morgan Kaufman 9. Wu Q (2009) Man-machine-environment system. National Defence Industry Press, Beijing 10. Sanders MS, McCormick EJ (1993) Human factors in engineering and design. Ind Robot Int J 11. GB 10000–88 (1989) Human dimensions of Chinese adults. Standards Press of China, Beijing

The Dilemma Generated by Automated Driving Considered from Ethical Aspect Tianrui Qin, Quan Yuan and Wenjie Lu

Abstract Automated driving technology breaks the “human–vehicle–road” model in the past few years and also breaks down the original ethical guidelines. Along with the development of automated driving technology, a series of ethical issues have shown up. This paper analyzes the typical scenarios related to ethical issues of automated vehicles in the mixed road traffic. In these extreme scenarios, e.g., when facing at least two different vulnerable road users, automated vehicles have to impact “who” and meanwhile avoid “who.” In the next step, some feasible solutions are discussed through theoretical analysis. Once these ethical and moral dilemmas can be figured out, the automated vehicles will be just around the corner. Keywords Automated vehicles road users

 Ethical issues  Accident  Vulnerable

1 Introduction Automated driving technology is an important manifestation of informatization and intellectualization. Its development and widespread use reflect the progress of science and technology. However, while improving human’s life, it is also inducing a series of dilemmas related to ethical issues. According to the IEEE, it is estimated that by 2040, 75% of vehicles will implement automated driving [1]. The automated driving technology can bring a lot of benefits, such as eliminating traffic jams, reducing traffic accidents, and reducing environmental burdens. However, T. Qin  Q. Yuan (&) State Key Laboratory of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China e-mail: [email protected] W. Lu Traffic Management Research Institution of the Ministry of Public Security (TMRI), Wuxi 214151, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_81

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automated vehicles now face multiple ethical issues. One of the thorniest questions is: How to establish a set of ethical guidelines that automated vehicles should follow? This issue is not only a subject for manufacturers, ethical experts, and government regulators, but also a consumer concern. At present, Chinese companies are also speeding up the development and tests of automated vehicles. But facing to this urgent issue, there is still little relevant discussion in academic circles. Therefore, this paper aims to discuss the ethical dilemmas of automated vehicles from the scientific and technological ethic perspective and reflect on the issues associated with civilian automated driving technologies, on the basis of combining domestic and international research. This may dialectically examine the impact of scientific and technological progress on moral concepts.

2 Ethical Issues Faced by Automated Vehicles The automated vehicles have fundamentally changed the traditional “human–vehicle–road” closed-loop control method and brought uncontrollable drivers out of the closed-loop system, thereby greatly improving the efficiency and safety of the traffic system. The modern automated vehicle is based on the automotive industry and relies on high technologies. Its horizontal development is inseparable from the practical needs of various uses. The vitality of its vertical development lies in continuous technological innovation [2, 3]. Although automated vehicles have not yet been truly market-oriented, the application of automated driving technology has become an irreversible trend. When a car is in automated driving mode, every driving decision needs to be early made by program. When the vehicle faces some difficult scenes, there may be ethical dilemmas. In the case of man-made driving, it is generally believed that the instantaneity of the accident makes it impossible to adopt rational and judicious judgments after balancing the interests of all aspects. Instead, it deals with accidents based on instinct. In the contrast, in an automated driving situation, once the vehicle makes use of the advantages of supercomputers and big data and determines the next driving plan by quantifying and calculating the impact factors, the instinctive response that the driver makes instantaneously will be superseded. Programming lengthens the time to respond to an accident and won a time for handling the accident [4]. By this, how automated vehicles make decisions in accidents can also be a moral problem. And how to set up a program that embodies goodness ultimately depends on the person’s own value orientation, and this cannot be expected to the improvement of technology [5]. In the ethical issues of science and technology, these ethical dilemmas are often summed up in two most typical ideological experiments called trolley problem and tunnel problem (see Fig. 1). However, in the real roadway, there are some more risky scenarios related to vulnerable road users (pedestrians, bicyclists, animals, etc.) that automated vehicles have to avoid collisions.

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Fig. 1 Some scenarios related to ethical issues of automated vehicles

2.1

Trolley Problem

The trolley problem was originally proposed by Philippa Ford, and the most usual initial version is: “Suppose you are driving a tram out of control on the main road. Unfortunately, there are five workers working on the track, if you let the tram continue to run, these five workers will be killed, the only way to save the five people is to turn the steering, so that the tram will go to a next track, but there is also a worker on the track, so what would you choose?” And this problem is applied to automated vehicles and may be in a similar situation, for example, while an automated heavy truck is driving at high speed on the road, and suddenly an out-of-control car ran to the opposite lane. Five people on the car may all die if it hit. The automated truck can also choose to turn to the right sidewalk to avoid the car, but it will hit a pedestrian walking and cause his death. At this point, the driver or computer has to make a choice [6].

2.2

Tunnel Problem

The tunnel problem can be understood as a variant of the trolley problem, but there are also some differences. The trolley problem describes the selection dilemma of automated cars for collision targets, while the tunnel problem is for the conflict between the vehicle’s personnel and passers-by, pointing the ethical choice to the driver’s self-sacrifice.

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The tunnel problem is described as this: On a single mountain road, the automated car is preparing to enter the tunnel. At this time, a child runs to the middle of the road and is just blocked at the entrance to the tunnel. At this moment, the automated car has only two choices: Hit the child or hit the wall at the tunnel entrance. The first choice may cause the child’s death, and the second will endanger the driver’s life. There is a survey showed that 64% of people said they would choose to crash into children. Perhaps the human’s self-protection instinct can provide an explanation for this result. However, if the accident does not result in serious injury to the person inside vehicle, or if there is only a certain probability of surrender of the person inside vehicle, or it will also lead the death of multiple pedestrians, the problem will be even more complicated [1].

2.3

Pedestrians’ Fault

If accidents are due to pedestrians’ faults (such as non-compliant crossings), the choice of automated vehicles is also very important. Due to technical limitations, the automated vehicle may not be able to detect or analyze the surroundings safety in time. At this time, is it to choose to hit the pedestrian directly or take more risks (disturbing the traffic and causing greater harm) to protect this pedestrian? [7] This is in fact an extreme case of “trolley problems.” Choosing one side will only make one pedestrian and pay the price of life just for crossing the road. Choosing the other side may have all the peace, but it may also cause chaos in road traffic and cause more loss. There is no choice which seems to make people feel “safe,” but more “safe” is the original intention of automated technology [8]. Recently, a real accident involving automated vehicle happened and also caused people to reconsider the safety of automated vehicles.

2.4

Animals in Traffic

Another interesting, but very real problem, is whether the automated vehicle needs to avoid the animals entered the roadway while driving. When a person is driving, it is so often that an animal suddenly occurs on the road, whether it is a pet or a wildlife. This usually does not cause major problems in China, but in other countries, drivers who kill animals on highways are often condemned by animal protection organizations, regardless of whether the driver intends to do so. In the state of automatic driving, avoiding animals may cause traffic jams and even danger; but if you choose not to avoid animals in the program, it is very likely that will be denounced by animal protection organizations. The biggest difference between animals and pedestrians is their ability to understand. Even if pedestrians can understand the situation in the scene, their unregulated traffic behavior may lead

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to danger for themselves when the road vehicles are unmanned, not to the animals which have no ability to understand human society [9].

2.5

Passenger’s Priority

In a crash involving an automated vehicle, the car’s pre-programmed procedures will allow the position of the passenger to be the safest. When there is only one passenger, this will undoubtedly protect his safety. However, when there are multiple passengers in one vehicle, the program needs to determine which passenger to protect at first. Is it the child in back row to protect at first or the leader in front row? This issue may be even more problematic today than before. For example, in the past, we had the principle of “Ladies First.” However, simply using gender as the basis for determining the priority of passengers will inevitably cause feminist’s opposition, let alone the sexual minorities such as transgender people at all.

3 Existing Methods and Analysis of Automated Driving Ethics When accidents endanger life or basic rights, computer programs must address ethical dilemmas and make decisions. Facing the moral dilemma of automated vehicles, people with different values will make different choices. The current countermeasures mainly include two kinds of attempts: First, establish ethical rules from top to bottom, including the rules of deontology and consequentialism, and second, establish ethical rules through machine learning from the bottom up [2]. These countermeasures propose solutions from different aspects and try to establish an effective rule to guide the ethical choice of automated vehicles.

3.1

Deontology

In the view of the deontologists such as Kant, people are the purpose of existence. The deontological theory believes that the justification of behavior comes from whether the behavior is ethical or not. And the automated vehicles must also abide by certain basic principles, and Asimov’s three laws of robot are typical representatives. Influenced by Asimov’s three laws [9], Gerdes and Thornton proposed three laws of automated vehicles: The automated vehicles must not hit pedestrians and bicycles; the automated vehicles should not collide with other vehicles unless it conflicts with the first theorem; the automated vehicles cannot collide with other objects unless it conflicts with the first and second theorems [10].

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Consequentialism

Consequences are represented by Bentham’s utilitarianism. Utilitarian believe that according to the principle of “the greatest happiness of the most people,” designers should consider which option can bring the most benefit or generate less harm [1]. According to this principle, in the absence of a clear identity of the potential hitter, the car should drive toward the lesser side.

3.3

Machine Learning

In the road traffic, automated vehicles may make some human unpredictable behaviors, which will pose a great threat to traffic safety [11]. Machine self-learning is a bottom-up process, and its decision-making basis is the practical behavior in human driving. Many of these behaviors do not conform to ethical norms. That is to say, the ethical rules learned by machines are based on actual descriptions, rather than normative ethical guidelines. In practice, violations of driving and changing lanes will affect the contents of machine learning. This requires that humans provide continuous feedback and corrections for the content of machine learning, but this is back to the normative ethics problem: What exactly is right, this issue is still pending. However, in addition to solving these problems, when civilian automated driving technology is gradually accepted and promoted, it must not only seek reasonable consensus on value in related moral decisions, but also pay attention and deal with the same difficult problems that arise as a result of the program. The ethical concept of transformation may not only make people’s value judgments and life ideas tend to be homogenous, but also may have a disruptive influence on the current mainstream moral outlook.

4 Discussion Before the automated driving technology was introduced to the market, how to solve the ethical issues became a very important issue. The reason is in the essential difference between morality and science. In science, it is very easy to distinguish right or wrong of a problem; however, when it comes to moral issues, each person’s values and moral concepts are different. Even in the same issues, its attitude and solution are also different. For example, in the “trolley problem,” there is no right or wrong between the two options. The specific choice is only the expression of personal values. In this research, the ethics of automated driving need to start from the following aspects.

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Improve the Ethical Principles of Automated Technology

Although there are three laws of automated vehicles, it is clear that these three laws have not yet convinced most people. In principle, automated vehicles should protect the safety of people in the car and more people as possible. However, this does not mean that innocent people who follow the rules can be sacrificed when it’s necessary. Compared to the five individuals on the uncontrolled car, roadside pedestrians, as weak, should be protected and should never pay for the independent cars.

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Perfect Automated Driving Laws and Definite Responsibilities

At present, there are no corresponding laws and regulations for automated vehicles, which must be published before automated vehicles are officially listed [12]. In the relevant laws, there should be a clear statement of the treatment of various accidents and the determination of accident liability. For example, in the previous “trolley problem,” if an automated vehicle is hit by an out-of-control car, the responsibility lies with the out-of-control car’s driver or the product company. Once the automated vehicle chooses to crash into a pedestrian, the responsibility for the accident should be the programmer or the owner of the automated vehicle. After clarifying the responsibility for accidents, the auto companies and users will also produce and choose the appropriate automated vehicles according to the laws.

4.3

Further Improvement of Automated Technology

Although advances in technology cannot fundamentally solve the ethical and moral issues involved in automated technology, the reduction in the failure rate of automobiles and the improvement in the safety protection capability of occupants can greatly reduce the accident rate and the difficulty of handling. When the accident rate drops to a very low level, some problems that are difficult to condemn and can hardly deal with directly can be addressed with ambiguously, making the automated driving ethical issues no longer a prominent problem.

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5 Conclusion As technology develops, automated vehicles are bound to enter our lives. Although so far there has not been a complete system to deal with the various ethical issues that may be encountered by automated driving, many people have already proposed some solutions in terms of ethics, law, and technology. They wish to establish a set of moral principles determined through top-down ethical approach as well as bottom-up machine learning, and then make people accepted through legislation. This is the most feasible way to solve the ethical dilemma issue of automated driving. Acknowledgements This paper was supported by National Key R&D Program of China (2017YFC0803802) and the Open Project of Key Laboratory of Ministry of Public Security for Road Traffic Safety, China (No: 2017ZDSYSKFKT11).

References 1. He H (2017) Dilemma, causes and countermeasures of automated vehicles ethics. Stud Dialect Nat 33(11):58–62 2. Urmson C, Anhalt J, Bagnell D et al (2008) Automated driving in urban environments: boss and the urban challenge. J Field Robot 25(8):425–466 3. Qiao W, Xu X (2007) Development status and direction of automated vehicle. Shanghai Auto 7:40–43 4. Gogoll J, Müller JF (2017) Automated cars. In favor of a mandatory ethics setting. Sci Eng Ethics 23(3):681–700 5. Du Y (2017) Research on moral responsibility in robot ethics. Stud Sci Sci 11:1608–1613 6. Thomson JJ (1976) Killing, letting die, and the trolley problem. Monist 59(2):204–217 7. Bonnefon JF, Shariff A, Rahwan I (2016) The social dilemma of automated vehicles. Science 352(6293):1573–1576 8. Winkle T (2016) Development and approval of automated vehicles: considerations of technical, legal, and economic risks. Auton Driv 9. Goodall NJ (2014) Machine ethics and automated vehicles. Road vehicle automation. Springer International Publishing, pp 93–102 10. Hauser M, Cushman F, Young L et al (2007) A dissociation between moral judgments and justifications. Mind Lang 22(1):1–21 11. Gerdes JC, Thornton SM (2015) Implementable ethics for automated vehicles. Autonomes Fahren. Springer, Berlin, pp 87–102 12. Dennis L, Fisher M, Slavkovik M et al (2016) Formal verification of ethical choices in automated systems. Robot Autom Syst 77(C):1–14

Application of Man-Machine-Environment System Engineering in Shipboard Equipment Baiqiao Huang and Pengyi Zhang

Abstract Shipboard equipment is a typical man-machine-environment system. In order to improve the operating efficiency of operators and the “human adaptability” level, full consideration needs to be taken to factors of human, machine, and environment. The characteristics of man, machine, and environment which are related to shipboard equipment have been analyzed by man-machine-environment system engineering (MMESE) theory, and the factors of man, machine, and environment that should be considered during shipboard equipment development are introduced in three aspects including man–machine interaction design, man–environment interaction design, machine–environment and interaction design in order to provide theoretical basis for improving the work efficiency and “human adaptability” level of shipboard equipment.



Keywords Man-machine-environment system engineering Man–machine interaction design Man–environment interaction design Workload





1 Introduction Shipboard equipment is a typical man-machine-environment system. “Man” consists of equipment operators and operational commanders, and “machine” refers to shipboard equipment, divided into three level based on the hierarchical relationship, that is equipment level, system level, and hierarchy level. “Environment” includes the marine climate environment of the shipboard equipment, the rocking vibration environment of ship platform and the closed environment of cabin. Currently, the shipboard equipment has gradually developed from focus on function realization to B. Huang (&)  P. Zhang China Ocean Security System of System Innovation Center, Beijing 100094, China e-mail: [email protected] B. Huang  P. Zhang System Engineering Research Institute of China State Shipbuilding Corporation, Beijing 100094, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_82

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focus on “human adaptability” development. In order to improve the operating efficiency of operators and the “human adaptability” level of shipboard equipment, full consideration needs to be taken to factors, such as human characteristics, human–equipment interaction and micro-climate environment where people works, and this is exactly the content of man-machine-environment system engineering (MMESE). MMESE is a science applying system science theory and system engineering method to correctly deal with the relationship among three factors, including human, machine, and environment and deeply study the optimal combination of man-machine-environment system [1]. This theory had been proposed by Professor Shengzhao Long and developed under the guidance of Xuesen Qian. Research emphasis of MMESE includes human characteristics, machine characteristics, environment characteristics, human–machine relationship, human–environment relationship, machine–environment relationship, and overall performance. Currently, the man-machine-environment design of United States shipboard equipment is world leading, in which general “human–machine ergonomics design criteria for military system” has been established based on data collected for many years (MIL.STD.1472F), and “design criteria for ship habitability” has also been established specifically for the ship design (T9640.AB.DDT.010/HAB); large ship development in the USA must follow said standards. The man-machineenvironment design of ship in China has a rather late start and Harbin Engineering University has developed many researches on the application of MMESE in ship design; the top level framework for implementation in large ship and application of MMESE is proposed in [2], and the factors required to be considered from three aspects, including life correlation, operation correlation, and safety correlation, are separately introduced. Man-machine-environment assessment method of ship habitat is centralized in [3]. Man-machine-environment design and application of ship control console arrangement are studied in [4].

2 Analysis of Man-Machine-Environment Characteristics 2.1 2.1.1

Man Characteristic Analysis Physical Characteristics of Human

Physical characteristics of human refer to the dimension characteristic when human body is taken as the movement system, and such characteristic determines the range of activity when human body operates equipment and is a necessary reference basis in equipment design. The dimensions of different parts of human body are measured to determine the dimension difference between individual and group. For product design, the measurement of functional dimension of human body is critical, as it determines the operation space of human body. The measurement of physical

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characteristics of human of the group and selection of high-percentile human body dimension parameters are taken as the restraints of product design to make designed products suitable for most people.

2.1.2

Physiological Characteristics of Human

Physiological characteristic of human refers to the physiological phenomenon characteristics shown by human body during the period of maintaining their own vital functions and the interaction among human, equipment, and environment. From the system perspective, human body is a complicated and open macro-system. In operating equipment, human beings should firstly ensure their own vital functions; the physiological characteristic of human also includes the sense organ characteristics and locomotive organ characteristics of human. Sense organs of human (mainly including eyes and ears) are receivers of external information, responsible for receiving, and transmitting external information to the central nervous system of information processing; the locomotive organs of human (mainly including hands and mouth) are the actuators upon information decision making, responsible for putting the decision results into practice, including operating equipment or sending voice command. There are another important characteristics —the physical workload and physiological fatigue of human; due to the fatigue characteristics, human beings are unable to output in a continuous and stable way, which should be an important factor in task planning.

2.1.3

Psychological Characteristics of Human

Psychological characteristics of human refer to characteristics of information processing and decision-making process during the interaction between human and equipment and environment. Rasmussen [5] divides the information processing and decision-making process of human into three types, including skill-based, rule-based and knowledge-based (Fig. 1). Three decision-making processes determine different decision complexity and reaction time and form different mental workload. The division of decision-making type is beneficial to classification and delicacy management of each task during operation.

2.1.4

Group Characteristics of Human

Group characteristics of human refer to the characteristics shown by human under the influence of other group members, mainly including social facilitation effect, social standardization tendency, social concern tendency, and social conformity tendency. The group characteristic of human is a special psychological characteristic. Human beings are in group environment in operating the equipment and will be certainly under the influence of others; therefore, it is necessary to be considered

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Fig. 1 Decision-making process model of human

in the task process, and operators will show different performances under two circumstances of supervision and supervision absence, which is the influence of social facilitation effect.

2.2

Characteristic Analysis of Shipboard Equipment (Machine)

Spatial dimensions where shipboard equipment is located can be divided into four types, underwater, surface, midair, and space. In terms of different shipboard equipment, there are different design requirements for human–machine–environment. For example, submarine, located at an environment without sunlight, places high requirements for illumination. Surface deck open to air, located at an environment with intense sunlight, places high requirements for luminance of screen display.

2.3 2.3.1

Environmental Characteristics Analysis Natural Environment

High requirements are placed for environmental suitability of equipment due to high temperature, low temperature, high humidity, and salt spray conditions of the

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ocean. In terms of workbench open to air on ship deck, high requirements are placed for luminance of electronic display screen of equipment due to sunlight intensity on deck. High requirements are also placed for protection level of equipment open to air on deck due to wind, thunder, rain, snow, and other weather conditions of ocean.

2.3.2

Working Environment

Characteristics of working environment of marine equipment mainly consist of two types. The one is the environment where ship is pitching and rolling. People are not operating equipment at a stable land. Thus, simplified way of interaction shall be considered in design. The other one is that space in cabin is generally sealed and narrow and ill-ventilated, which is apt to present a sense of oppression. Thus, people-oriented design for micro-climatic environment in cabin is particularly important.

2.3.3

Social Environment

Each ship is a small community. Crews are superiors and subordinates in terms of position, which indicates a relation between leading and being led. Also, there is a relation of cooperation and competition between crews of the same level. Both social concern tendency and social facilitation effect among social characteristics of man mentioned above will impact personal work performance. In most cases, ship sails for more than 30 days. As a result, crews live in a small sparsely-populated environment for a long time. How to keep a healthy mental state is another important factor required to be considered.

3 Man-Machine-Environment Factors of Shipboard Equipment Design 3.1

Human–Machine Interaction Design

Human–machine interaction is the basic element for equipment to fulfill its functions and missions. Physical characteristics, physiological characteristics, psychological characteristics, and social characteristics shall be given into full consideration in design process of human–machine interaction for shipboard equipment so that designed product is able to suit to use by man and improve efficiency and reliability of people’s operation.

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Design of Hardware Console, Operation Space and Maintenance Space with Human Body Measurement Data Considered

Body dimensions data of crews are obtained by human body measurement. And database is established and used to guide height of shipboard equipment control console, angle of inclination of screen, and layout design of upper function key or button on console so that designed equipment is suitable for most people. Besides, adequate operation space is provided for operators in terms of placement design of equipment. Particularly, maintenance space shall be considered in advance and maintenance space outside equipment shall be considered in equipment placement, shipboard equipment is mostly placed in a narrow cabin. Thus, priority shall be given to consider the constraint relation between space of cabin and physical dimensions of personnel.

3.1.2

Interface colour design considering light condition

The basic premise of human–machine interaction is that the information can be displayed clearly, completely, and unambiguously to the operator. Therefore, as for shipboard equipment, it is necessary to consider color design of the software interface under different lighting conditions. For example, daytime sunlight of different intensity exists in over water cabins of shipboard ships in the daytime and evening, both of difference between sunlight and electronic lighting and different sunlight intensity (i.e., difference of daytime and night) should also be considered for color blending of software interface design, so as to have the software interface clearly convey information.

3.1.3

Interface Layout Design Considering Visual Search Rules

The first step for human–machine interaction process is that the operator receives information on the software interface through eyes. Usually, the software interface will provide a variety of information, while the operator needs to search and position the information required for this operation decision quickly from various information on the interface; therefore, it is about visual search, which is an important part of human–machine interaction field research in MMESE. Visual search can be divided into structured and non-structured areas according to search area, and it can be divided into random search and systematic search according to search strategy. For structured areas, systematic search strategy which is generally adopted will have a faster speed. The research also shows that complex background can reduce the speed of target search, that distinction degree of targets and background can improve speed of search. Besides, the visual search strategy is also related to the law of eye movement. Therefore, during design of the software interface layout, eye movement of operators should also be referred to, so actions like important data related to decisions placed at the focus area, information

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organized in a structured form, background simplified and increasing distinction degree of information and background can facilitate operators to search and position the information required quickly.

3.1.4

Functional Logic Design Considering Decision-Making Types

It can be learnt from the decision-making classification of Rasmussen that decision-making is divided into three types: skill-based, rule-based, and knowledge-based. Most of functions belong to rule-based decision-making process for software operation, while the complexity of the rule-based decision-making depends on number of decision-making participation parameters and logical complexity of decision-making. As for software function design, the perspective of user decision-making should be considered by minimizing the number of parameters involving in decision-making and complexity of decision-making logic as far as possible so as to improve reliability of decision-making process.

3.2

Human–Environment Interaction Design

Three aspects are mainly considered in human–environment interaction design: influence of environment on human’s physical health, influence of environment on human–machine design, and influence of special social environment of shipboard ships on human’s mental health.

3.2.1

Impact of Environment on Human Physical Health

For the impact of environment on human physical health, various factors that affect human physical health in the environment are mainly considered and security measures are added. The working environment of the ships mainly includes the deck surface and inner of cabin. Strong sunlight and high temperature on the surface of deck, airtight and narrow space in the cabin, poor air circulation and concentration of oxygen and toxic gases in the air need to be taken into account in the design of personnel working conditions.

3.2.2

Impact of Environment on the Human–Machine Interaction Design

The impact of environment on human–machine interaction design mainly includes the influence of sunshine conditions on the open workbench of deck, illumination conditions on the workbench in the cabin and wobbling vibration environment on ships during the human–machine interaction operation. High-brightness display

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should be used for the open workbench on the deck. High contrast color under sunlight should be considered for the color matching of software interface. Interface design under different sunshine intensity in the daytime, evening, and at night can also be considered for the software interface. Design of work environment in the cabin mainly includes the design of lighting conditions, and the adaptability design of the software interface under lighting conditions. The process of human–machine interaction also needs to overcome the environmental conditions of wobble and vibration of ships and considers the simplicity of operation and the stability of input devices, such as using trackball instead of ordinary mouse.

3.2.3

Impact of Social Environment

The impact of special social environment on ships on people’s psychology is mainly reflected in people’s psychological stress due to lonely and monotonous work and living environment in the long-term sailing missions, especially for submarines which stay in deep sea without sunshine. We should consider regularly diverting people’s psychology and provide facilities for seafarers to relax and keep a watchful eye on the mental health of the crew.

3.3

Machine–Environment Interaction Design

Machine–environment interaction design mainly refers to the protection design of equipment in the marine environment. The marine environment is harsher. Under the environment of high temperature, high humidity and high salt fog, the equipment is easy to be corroded. The outdoor equipment on the deck is easily damaged under sunshine, rain, hurricanes, and other volatile weather conditions. In the wagging vibration environment, the interface of equipment is prone to fracture. Therefore, shipboard equipment should meet high requirements of machine–ring interaction design. Corrosion-resistant materials should be used, and corrosion-resistant coatings should be applied on the surface; outdoor equipment on the deck should be provided with higher grade of protection; solid and anti-vibration navigation interface instead of conventional interface should be used for electronic equipment.

4 Conclusions Characteristics of shipboard equipment in man, machine, and environment are analyzed in the thesis, and these characteristics include physiological characteristics of human, mental characteristics, and group characteristics of human, characteristics of shipboard equipment, characteristics of natural environment in shipboard equipment, characteristics of working environment as well as characteristics of

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social environment. Based on results of analysis on these characteristics, it is proposed to use the theory of MMESE in human–machine interaction design, human–environment interaction design, and machine–environment interaction design of shipboard equipment so as to provide theoretical basis for comprehensive promotion of the theory of man–machine–environment system engineering in shipboard equipment development.

References 1. Long Z (1993) Man-machine-environment system engineering theory and its significance in productivity development. In: Progress in man-machine-environment system engineering research, vol 01. Beijing Science and Technology Press, Beijing, pp 2–13 2. Shang Z (2008) The application of the system of man-machine-environment on the large-scale marine. Harbin Engineering University 3. Yan H (2008) The man-machine-environment evaluation system of ship living cabin. Harbin Engineering University 4. Wang S (2012) Ergonomic design and application of ship wheelhouse layout. Harbin Engineering University 5. Rasmussen J (1983) Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. J IEEE Trans Sys Man Cybern 13(3):257–266

Spacial design of Display Console on Ship-Based Man-Machine-Environment System Engineering Jingyu Song and Baiqiao Huang

Abstract Spacial design of warship display console includes operation space design and human psychological space design. In this paper, the man-machine-environment system engineering (MMESE) theory is used to analyze the main factors influencing the spatial design of the display console, including the physical measurement characteristics of the human body affecting the human operating range and the human psychological spatial characteristics affecting human operation safety and comfort. And according to the human adaptability standards, the design of operation space of the display console based on the human body measurement of the crew and the layout design of the display console based on the individual psychological space were, respectively, carried out. And provide theoretical guidance for standardizing the spatial design method of the display console and improving the “human adaptability” of the display console.



Keywords Man-machine-environment system engineering Display console Space design Anthropometry Psychological space Human adaptability







1 Introduction Display console on ship is the naval basic equipment with a wide application, is mainly used for commanding the control information system, and is one of the devices with most interaction with operators. The operation of the display console is a typical process of man-machine-environment system engineering, where “man” refers to the operator, “machine” is the display console itself, and “environment” comprises the cabin environment in which the display console is located at the rocking vibration J. Song  B. Huang (&) System Engineering Research Institute of China State Shipbuilding Corporation, Beijing 100094, China e-mail: [email protected] B. Huang China Ocean Security System of System Innovation Center, Beijing 100094, China © Springer Nature Singapore Pte Ltd. 2019 S. Long and B. S. Dhillon (eds.), Man-Machine-Environment System Engineering, Lecture Notes in Electrical Engineering 527, https://doi.org/10.1007/978-981-13-2481-9_83

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environment of the ship body. At present, naval military equipment is gradually developing from function concern to “people orientation.” The operation space and the psychological space design of human are the important means to achieve “people orientation” for the design of the ship’s display console. Therefore, in order to improve the “people orientation” and operation efficiency of the ship’s display console, we need to take full consideration of the influencing factors in man-machine-environment system engineering for guiding the design of display console. Man-machine-environment system engineering is the science [1] that uses systematic science theory and system engineering method to correctly handle the relationship between human, machine, and environment and deeply study the optimal combination of man-machine-environment system. The research focuses of man-machine-environment system engineering include the characteristics of human, the characteristics of the machine, the characteristics of the environment, man–machine relationship, man–environment relationship, machine–environment relationship, and the overall performance of man-machine-environment system. At present, the man-machine-environment design of US Navy has a leading position in the world and has established general Guidelines for Ergonomics Design of Military Systems (MIL.STD.1472F) based on man–machine engineering design data collected for many years. The man-machine-environment design starts later in China, Harbin Engineering University has carried out more researchers on the application of man-machine-environment engineering to the ship design, and the man-machine-environment design and application in the ship’s cabin layout are studied in [2]. The man–machine interaction design of radar display console guided through the human body measurement data is studied in [3]. The outlines of ship display console and software in man–machine interaction design are studied in [4]. On the basis of reference to human body measurement standard, this paper studies the space design of display console and pays attention to the operation space and the psychological space design of operator of display console, so that the designed display console can meet the requirements on function with convenient operation and “people orientation” with comfortable and safe performance.

2 Characteristics Analysis on the MMESE in the Display Console spacial design Characteristics of human include physical characteristics, physiological characteristics, and metal characteristics of human. Physical characteristics refer to the size characteristics of human body as the moving system, which determines the range of activity when operating the equipment, and is the reference to the design of the operation space of display console. The physiological characteristics of human refer to the physiological phenomenon properties of human during the process of maintaining its own life function during the interaction between human and equipment and environment, which is mainly influenced by the system load and the mental load during the process of operating the display console and does not

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influence the space design of display console. The mental characteristics of human refer to the information processing and decision-making process of human during interaction with equipment and environment, and mental factors such as value viewpoint, character, motivation, and emotion, including the psychological spatial feeling of operators, which shall be taken into key consideration. The factors of “machine” refer to the functional design of the control console itself, which is not discussed in this paper. The display console is generally arranged in the cabin with suitable environmental conditions, the corrosion effect of the high-humidity and high-salinity air on the console shall be considered, and the strengthening performance of the console position and under the rocking vibration condition of the ship as well as operation convenience shall also be taken into consideration, which are not discussed in this paper. Therefore, this paper focuses on the influence of the physical characteristics of human on the operation space design of the display console and the influence of mental spatial characteristics on the layout of display console.

3 Operational Space Design Based on Human Body Measurement 3.1

Human Body Measurement Data of Naval Vessel Crew

The human body size as references to the operation space design of display console adopts the measurement data of naval vessel crew of Chinese Navy (GJB/ Z131-2002 Appendix C) [5] and meets the range of men of P5–P95 of the human body size of dressed adult. The major measurement data of male crew is shown in Table 1.

Table 1 Human size data of male crew (mm)

a b c d e f g h i

% Raw data P5

P95

Corrected data P5 P95

1630.7 1513.2 868.6 761.2 520.7 483.3 382.0 130.3 419.7

1794.3 1674.8 958.4 857.6 602.7 548.5 438.0 169.5 499.3

1660.7 1543.2 – – 533.7 513.3 412.0 143.3 –

1824.3 1704.8 – – 615.7 578.5 468.0 182.5 –

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Display Console Control Range Design

Based on the human body size, the hand-operated area, the moving space of crew, the channel size and the personal psychological space, the human factors engineering simulation analysis are carried out and constantly iterated and optimized, and the human factors engineering layout plan of the display console is formed. Relevant design principles on control panel regulated in Article 5.7.5.2 of GJB/Z 131-2002 “Man-Machine Engineering Design Manual for Military Equipment and Facilities” are adopted as the basis for analysis of the hand reachable area of crew, and the specific operation space design conclusions are as follows: 1. The display position of the main controller shall be placed between the shoulder height and the waist height. 2. The position of controller shall ensure that the operator can simultaneously manipulate two controllers with both hands without hands crossing or exchanging. 3. The frequently used controller shall be installed at the left or right front of the operator. 4. The frequently used controller shall be installed in the range of not over 400 mm from the normal working position. 5. The controller not used frequently shall be installed in the range of not over 700 mm from the normal working position. 6. All controllers shall be placed within the reachable range of operator.

4 The Spatial Layout Design of Display Console Based on Personal Psychological Space 4.1

Personal Psychological Space Introduction

Personal psychological space is an invisible area around the operator, which is the desired space for human psychology and is not the physical space required for normal operation. Human’s demand on psychological space is always larger than the operating space. When the psychological space is invaded, it produces unpleasant feeling, anxiety, discomfort, and tension, and it is difficult to maintain a good mental state, which may divert attention under light situation and even influence the operation under serious situation. The personal psychological space of crew can be roughly divided into four areas outward: tight area, near area, social area, and public area, as shown in Fig. 1. (1) Tight Area It is the area closest to human body, which covers an area within about 45 cm from the human body. This area generally does not allow outsider invading. If

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Fig. 1 Psychological space of crew

there is stranger in this area, it will affect the operation and even make the operator overwhelmed by sensory stimuli, which is the area of intimate contact. The area of about 0–15 cm from the human body is characterized by direct contact with the body or close to the body and not allowing for the intrusion of ordinary person. The area of about 15–45 cm from the human body is characterized in that the possibility of physical contact is reduced (hand can be grasped or touched), but there is still a visual perception of the presence of another person. (2) Near Area Near area refers to an area of about 45–120 cm from the human body. This is the area of friendly contact and is the space area of friendly conversation with people, as well as the distance between friends and colleagues. The area of about 45–76 cm from the human body: This is the distance between acquaintances. The stranger’s intrusion will cause the feeling of being embarrassed or evasive, and even be regarded as a kind of threat. The area of about 76–120 cm from the human body: This is the distance from which the fingertips can come into contact when the two are opposed to each other. It is the area that comes into contact with ordinary person. (3) Social Area Social area refers to the area of about 1.2–3.5 m from the human body. This is the psychological space range of general social activities and does not have work relation on personal contact. In this area, conversation between persons will not be influenced since the distance is too far away, and also will not make a sense of alienation.

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The area of about 1.2–2.1 m from the human body: This is the distance between people who work together or when talk with superior or subordinate. The area of about 2.1–3.5 m from the human body: This is the area of general work contact, with formal social properties such as formal meetings, etiquette. It can keep a certain distance between the persons. In this area, when someone is present, it will not be considered impolite even during normal work. (4) Public Area Public area is outside the social area and refers to the distance kept in public, which has exceeded the spatial range of direct contact with the individual. The area of about 3.5–7.5 m from the human body: This is the distance that needs to speak with raised voice and sees the activity of each other clearly. The area of about 7.5 m away from the human body: In this case, it is not clear to identify the expression of the other person and the subtle part of the voice, it is the space for talking with exaggerated gesture and loud voice, and conversation requires the means of communication.

4.2

Spatial Layout Design of Display Console

1. Longitudinal Movement Spacing of Crew At least, 1220-mm free activity area shall be provided in front of the console under possible conditions; the distance for the backward activity of the crew who is seated or standing shall not be less than 1000 mm in front of the console; the distance between the trailing edge of the equipment rack and the nearest elevation or obstruction shall not be less than 1070 mm; the spacing shall not be less than 1270 mm when the staff is working, and other person (single person) is allowed to pass through. The minimum spacing of the longitudinal activities of crew is shown in Fig. 2:

Fig. 2 Minimum portrait action spacing of crew

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2. Transverse Movement Spacing of Crew The transverse spacing between two adjacent crews shall generally not be less than 1000 mm.

5 Conclusion In this paper, the space design of display console mainly includes the operation space design and the psychological space design, and based on the man-machine-environment system engineering method, the main factors influencing the space design of the display console are analyzed, including physical characteristics and the psychological spatial characteristics of human body. The spatial layout design of display console based on human body measurement and personal psychological space is carried out. This paper provides the theoretical and methodological guidance to satisfy the operation functionality and the “people orientation” of the display console.

References 1. Long Z (1993) Human-machine-environment system engineering theory and its significance in productivity development. In: Progress in human-machine-environment system engineering research, vol 01. Beijing Science and Technology Press, Beijing, pp 2–13 2. Wang S (2012) Ergonomic design and application of ship wheelhouse layout. Harbin Engineering University 3. Chen Chunfei (2006) Humanized design of display control panel of radar. Electro-Mech Eng 22(3):39–41 4. Qiao Y (2013) The research and application of human-computer interaction techniques in ship integrated navigation display and control console. Harbin Engineering University, pp 6–13 5. General Equipment Department of PLA. GJB Z131-2002 (2002) Human engineering design handbook for military equipment and facilities

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