Active Safety Methodologies of Rail Transportation (eBook)

Yong Qin is the Dr., Professor, vice dean of State Key laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University. He also is the vice director of Beijing Research Center of Urban Traffic Information Intelligent Sensing and Service Technologies, the vice dean and secretary general of Rail Transportation Electro-technical Committee of China Electro-technical Society, the vice dean and secretary general of Rail Intelligent Transportation Systems Committee of China Intelligent Transportation Systems Society, and the member of IEEE ITS and RS, senior member of IET. He also has “the China Outstanding Scientific and Technological Workers Award” and “IBM Faculty Award”.His research interests are in the area of intelligent transportation systems, railway operation safety and reliability, rail network management and traffic model. He has authored or coauthored more than 100 publication papers(SCI/EI), 1 ESI highly cited paper and 5 books, has 23 patents granted, also won 11 science and technology progress award of ministry, 2 Golden awards of international exhibition of inventions and so on.

Preface 6
Contents 8
Chapter 1: Fundamental of Rail Transportation Active Safety 11
1.1 Research Paradigm of Rail Transportation Active Safety 11
1.1.1 Concepts and Methodologies 11
1.1.2 Research Architecture 12
1.2 Literature Review 14
1.2.1 Safety Region Estimation Theory and Methods 14
1.2.2 State Identification and Predication of Train Equipment 17
1.2.2.1 Safety State Analysis of Equipment 18
1.2.2.2 State Monitoring and Evaluation of Wheel Rolling Bearings 21
1.2.3 Train Safety and Reliability Evaluation 24
1.3 Research Work of Authors´ Group 26
References 29
Chapter 2: Safety Region Based Active Safety Methods 34
2.1 Safety Region Analysis Model 34
2.1.1 Basic Concepts 34
2.1.2 Processing Procedures 40
2.1.3 Computation Methods 41
2.2 Safety Region Based Accident-Causing Model 46
2.2.1 Concepts and Procedures 47
2.2.1.1 Definition of Safety Region 47
2.2.1.2 Analysis of Accident-Causing Model 49
2.2.2 Case Study 52
2.2.2.1 The Wenzhou Train Collision Accident Analysis 53
2.2.2.2 Specified Application of the Safety Control Measures 57
2.2.2.3 Corresponding Prevention Measures 60
References 61
Chapter 3: Train Equipment Fault Diagnosis and Prognosis 63
3.1 Fault Diagnosis of Rolling Bearings Based on Safety Region 63
3.1.1 The Configuration and Faults of Rolling Bearings 63
3.1.2 Rolling Bearings Vibration Mechanism 63
3.1.3 Procedure of the Safety Region Identification of Rolling Bearings 64
3.1.4 LMD of the Vibration Signal of Rolling Bearings 65
3.1.5 Safety Region Feature Extraction of Rolling Bearings 71
3.1.6 The Safety Region Identification of Rolling Bearings Based on SVM 75
3.2 Degradation Assessment of Rolling Bearings Based on SVDD 105
3.2.1 Support Vector Data Description 105
3.2.2 Particle Swarm Algorithm Based on Dynamic Weight Adjustment 108
3.2.3 Research on the Self-Adaptation Warning 111
3.2.4 Case Study 111
3.3 Fault Diagnosis of Door System Based on the Extended Petri Net 116
3.3.1 Subway Train Door: Open Process Analysis 116
3.3.2 Subway Train Door System Fault Diagnosis Theory and Method 116
3.3.3 Case Study 120
References 124
Chapter 4: Train Reliability and Safety Analysis 126
4.1 Introduction 126
4.1.1 Reliability and Safety Standards of European Railway System 126
4.1.2 System of Train Operational Reliability and Safety Analysis 127
4.1.2.1 Data 127
4.1.2.2 System Reliability Assessment 128
4.1.2.3 System Safety Assessment 128
4.1.3 Procedure of Train Operational Reliability and Safety Assessment 128
4.2 Reliability Analysis and Prediction of Bogie Frame 130
4.2.1 Reliability Analysis of Bogie Frame Based on Survival Analysis 130
4.2.1.1 Survival Analysis Theory 130
4.2.1.2 Maximum Likelihood Estimation 131
4.2.1.3 Goodness of Fit Test 132
4.2.2 Failure Rate Prediction of Bogie Frame Based on BP and PSO-BP Methods 132
4.2.2.1 BP Neural Network 132
4.2.2.2 Basic Principles of PSO 133
4.2.2.3 PSO-BP Prediction Model 133
4.2.3 Case Study 134
4.2.3.1 Analysis of Bogie Frame 134
4.2.3.2 Prediction of Failure Rate 137
4.3 Residual Life Prediction of Rolling Bearings Based on GA-BP 139
4.3.1 Residual Life Prediction Model of Rolling Bearings Based on GA-BP 139
4.3.2 Case Study 141
4.4 Operational Risk Assessment of High Speed Train 146
4.4.1 Basic Challenges of High Speed Train Operational Risk Assessment 150
4.4.1.1 Construction of High Speed Train Operational Risk Assessment Index System 151
4.4.1.2 Applications of TFNIFS in the Risk Assessment Index System 154
4.4.1.3 Correlation Risk Index 156
4.4.2 Dynamic VIKOR Method for High Speed Train Operational Risk Assessment 159
4.4.3 Case Study 163
References 171
Chapter 5: Operational Risk Analysis of Rail Transportation Network 173
5.1 Operational Risk Assessment Model 173
5.1.1 Operational Safety Assessment Index System of Metro Station 174
5.1.2 Operational Safety Assessment Index System of Traffic Line 177
5.1.3 Operational Safety Assessment Index System of Traffic Network 178
5.2 Operational Risk Prediction Model 179
5.2.1 Safety State Prediction Based on ARMA Model 182
5.2.2 Safety State Prediction Based on GA-SVR Model 184
5.3 Case Study 190
5.3.1 Case Study on ARMA Model 190
5.3.2 Case Study on GA-SVR Model 191
References 197
Chapter 6: Safety Prognostic Analysis in Traffic System 199
6.1 Traffic Operation Risk Analysis Model Based on Safety Region 199
6.1.1 Sequential Forward Selection and Principal Components Analysis 199
6.1.2 Computation Procedure 200
6.1.3 Case Study 201
6.1.3.1 Data Description 201
6.1.3.2 State Variable Extraction 202
6.1.3.3 Traffic Safety State Identification 203
6.2 Traffic Crash Risk Evaluation Model Based on Reliability Theory 206
6.2.1 Structural Reliability Analysis Theory 206
6.2.2 Analysis Procedure 208
6.2.3 Case Study 209
6.2.3.1 State Variable Selection 209
6.2.3.2 State Variable of Traffic System 210
6.2.3.3 Limited State Function Estimation 211
6.2.3.4 Test Results Analysis 213
References 216