正版 水下防喷器系统可靠性建模与评估 刘永红 等 科学出版社 978

Contents
Foreword
Preface
Chapter 1 Development of Automatic Subsea Blowout Preventer Stack Control System Using PLC Based SCADA 1
1.1 Introduction 1
1.2 Hardware architecture 3
1.2.1 Overall system architecture 3
1.2.2 Triple redundant controllers 5
1.2.3 Dual redundant Ethernet 6
1.2.4 Redundant subsea electronic modules 7
1.3 Voting algorithm 8
1.3.1 Discrete output voting 8
1.3.2 Discrete input voting 9
1.3.3 Analog input voting 9
1.4 Software methodology 10
1.4.1 Control logic 10
1.4.2 HMI program 13
1.4.3 Redundant databases 13
1.4.4 Remote access 15
1.5 Results and discussions 15
1.6 Conclusions 20
References 21
Chapter 2 Reliability Analysis of Subsea Blowout Preventer Control Systems Subjected to Multiple Error Shocks 23
2.1 Introduction 23
2.2 System description 25
2.2.1 Architecture of subsea BOP control system 25
2.2.2 Configuration of subsea BOP control system 27
2.3 System modelling and reliability analysis 29
2.3.1 Assumptions 29
2.3.2 System modelling and reliability analysis for TMR system 30
2.3.3 System modelling and reliability analysis for DDMR system 36
2.4 Results and discussions 37
2.5 Conclusions 44
References 45
Chapter 3 Performance Evaluation of Subsea Blowout Preventer Systems with Common Cause Failures 47
3.1 Introduction 47
3.2 System description 49
3.3 Reliability modelling and analysis 52
3.3.1 Assumptions 52
3.3.2 Failure rate and repair rate calculations 53
3.3.3 Reliability modelling 55
3.3.4 Performance evaluation 58
3.4 Results and discussions 59
3.5 Conclusions 64
References 64
Chapter 4 Using Bayesian Networks in Reliability Evaluation for Subsea Blowout Preventer Control System 66
4.1 Introduction 66
4.2 System description 69
4.2.1 Subsea BOP system 69
4.2.2 Configuration of subsea BOP control system 70
4.3 Bayesian networks modelling for reliability analysis 75
4.3.1 Overview of Bayesian networks 75
4.3.2 Bayesian networks modelling for redundant systems 75
4.3.3 Bayesian networks modelling for subsea BOP control systems 78
4.4 Results and discussions 82
4.4.1 Reliability of subsea BOP control systems 82
4.4.2 Difference between posterior and prior probabilities 82
4.4.3 Effects of coverage factors on the reliability 84
4.4.4 Effects of failure rate on the reliability 85
4.5 Conclusions 86
References 87
Chapter 5 Dynamic Bayesian Networks Based Performance Evaluation of
Subsea Blowout Preventers in Presence of Imperfect Repair 90
5.1 Introduction 90
5.2 Dynamic Bayesian networks with imperfect repair 92
5.2.1 Overview of BN and DBN 92
5.2.2 DBN modeling of series and parallel systems 93
5.2.3 Imperfect repair modeling 95
5.2.4 Conditional probability table 97
5.2.5 Reliability and availability 99
5.3 Case study 100
5.3.1 Fault tree 100
5.3.2 Corresponding DBN 103
5.3.3 Evaluation and validation 107
5.3.4 Results and discussions 107
5.4 Conclusions 113
References 114
Chapter 6 Performance Evaluation of Subsea BOP Control Systems Using Dynamic Bayesian Networks with Imperfect Repair and Preventive Maintenance 116
6.1 Introduction 116
6.2 DBN modeling of series， parallel and voting systems 119
6.2.1 DBN modeling with common-cause failure 119
6.2.2 Imperfect repair and preventive maintenance modeling 122
6.2.3 Conditional probability table 125
6.2.4 Reliability and availability 127
6.3 Case study 129
6.3.1 Configuration of subsea BOP control system 129
6.3.2 DBN modeling of subsea BOP control system 130
6.3.3 Evaluation and validation 133
6.3.4 Results and discussions 134
6.4 Conclusions 141
References 142
Chapter 7 Application of Bayesian Networks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations 144
7.1 Introduction 144
7.2 Proposed methodology 147
7.3 Case study 148
7.3.1 Subsea BOP operations 148
7.3.2 Modeling and analysis 151
7.3.3 Results and discussions 164
7.4 Conclusions 168
References 169
Chapter 8 Research on the Dynamic Bayesian Networks Based Real-Time Reliability Evaluation Methodology 172
8.1 Introduction 172
8.2 Proposed methodology 174
8.3 Case study 175
8.3.1 Subsea pipe ram BOP system 175
8.3.2 Modelling 177
8.3.3 Results and discussions 183
8.4 Conclusions 187
References 188
Chapter 9 A Dynamic Bayesian Networks Modelling of Human Factors on Offshore Blowouts 190
9.1 Introduction 190
9.2 Pseudo-fault tree 192
9.2.1 Human factors in offshore drilling 192
9.2.2 Pseudo-fault tree of safety barriers 193
9.3 Dynamic Bayesian networks 198
9.3.1 Introduction of dynamic Bayesian networks 198
9.3.2 Translating pseudo-fault tree into dynamic Bayesian networks 199
9.3.3 Evaluation and validation of dynamic Bayesian networks 203
9.4 Results and discussions 204
9.4.1 Quantitative analysis results 204
9.4.2 Effect of repair on the HFBF 204
9.4.3 Mutual information investigation 206
9.4.4 Validation of the model 208
9.5 Conclusions 208
References 209
Chapter 10 Application of Bayesian Networks to Reliability Evaluation of Software System for Subsea Blowout Preventers 211
10.1 Introduction 211
10.2 Software development 212
10.2.1 Subsea BOP c

评论

本书重点论述了深水防喷器系统的可靠性建模与评估理论与方法，采用markov、bayesiannetworks等工具研究了深水防喷器系统的可靠性和可用性，给出了考虑共因失效、不接近覆盖、不接近维修、预防性维护等的可靠性建模方法，并研究得到了系统参数对可靠性的影响规律关系，给出了提高深水防喷器系统可靠性的措施。

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