地铁车辆和供电系统是城市轨道交通的重要组成部分，包括车门系统、牵引系统、制动系统、轮对、高压断路器等关键系统和设备及车辆主要备品备件，这些系统和设备的健康状态不仅关系轨道交通系统的安全，还对提高城市轨道交通车辆运营的安全性和可靠性及乘客的舒适性体验有重要作用。本书介绍了地铁车辆与供电系统维修策略优化及预测技术方面的一些近期新研究成果，重点介绍了车门系统、牵引系统、制动系统、轮对、高压断路器的可靠性分析、可靠性建模和维修策略优化方法和技术，还对城市轨道车辆轴承部件剩余寿命预测及备品备件的需求预测技术进行了概述。

第1 章 绪论 ··········································································.001
1.1 轨道交通维修策略优化和预测现状 ···································.002
1.1.1 维修的发展现状 ···················································.002
1.1.2 预测性维修的优化目标 ··········································.009
1.1.3 车辆维修现状 ······················································.014
1.1.4 剩余寿命预测发展现状 ··········································.017
1.1.5 备品备件需求预测概述 ··········································.022
1.2 本书的主要内容 ····························································.028
参考文献 ···········································································.029
第2 章 车门系统可靠性分析与维修策略优化 ································.037
2.1 离散时间马尔可夫过程 ···················································.037
2.2 通用生成函数法 ····························································.040
2.2.1 通用生成函数法的基本原理 ····································.040
2.2.2 复杂系统的通用生成函数技术 ·································.041
2.3 可靠性模型及维修周期优化 ·············································.045
2.3.1 通用生成函数法可靠性指标 ····································.045
2.3.2 系统可靠性建模概述 ·············································.046
2.3.3 维修周期优化模型 ················································.047
2.4 车门系统可靠性建模与维修策略优化 ································.048
2.4.1 车门系统可靠性建模 ·············································.048
2.4.2 车门系统的可靠性指标计算 ····································.055
2.4.3 车门系统维修策略优化 ··········································.056
2.5 本章小节 ·····································································.058
参考文献 ···········································································.058
第3 章 基于Phase-type（PH）分布的系统可靠性分析 ··················.060
3.1 PH 分布的基本概念 ······················································.060
3.1.1 PH 分布的定义 ····················································.060
3.1.2 PH 分布的性质 ····················································.062
3.1.3 PH 分布的可靠性指标 ···········································.064
3.2 基于PH 分布的串并联系统可靠性分析 ······························.065
3.2.1 串联系统 ····························································.065
3.2.2 并联系统 ····························································.067
3.3 牵引系统案例分析 ························································.071
3.3.1 系统描述 ····························································.071
3.3.2 模型分析与建立 ···················································.072
3.3.3 系统可靠性指标的计算 ··········································.074
3.4 制动系统案例分析 ························································.075
3.4.1 系统描述 ····························································.075
3.4.2 模型分析与建立 ···················································.077
3.4.3 系统可靠性指标的计算 ··········································.080
3.4.4 可靠性与维修策略对比分析 ····································.081
3.5 车门系统案例分析 ························································.082
3.5.1 系统描述 ····························································.082
3.5.2 模型分析与建立 ···················································.083
3.5.3 系统可靠性指标的计算 ··········································.086
3.5.4 可靠性与维修策略对比分析 ····································.087
3.6 本章小结 ····································································.088
参考文献 ···········································································.088
第4 章 基于冲击理论的维修策略优化 ··········································.090
4.1 冲击理论概述 ······························································.090
4.1.1 故障机理分析 ······················································.090
4.1.2 基于Poisson 冲击流的累积损伤模型 ·························.093
4.2 基于冲击理论的组合维修概率模型 ···································.095
4.2.1 轮对磨耗及维修效果分析 ·······································.095
4.2.2 维修策略描述 ······················································.097
4.2.3 组合维修概率模型 ················································.099
4.3 故障风险及组合策略优化模型 ··········································.108
4.3.1 轮缘厚度超限故障风险 ··········································.108
4.3.2 组合维修策略优化模型 ··········································.110
4.4 案例分析 ·····································································.111
4.5 本章小结 ·····································································.118
参考文献 ···········································································.119
第5 章 基于混合故障率的断路器维修策略优化 ·····························.120
5.1 基于修正因子的混合故障率函数·······································.120
5.1.1 故障率函数的“役龄回退因子” ······························.121
5.1.2 故障率函数的“故障率递增因子” ···························.123
5.1.3 修正因子对故障率函数的综合影响 ···························.124
5.2 可靠性模型 ··································································.125
5.2.1 各维修周期内设备的可靠性模型 ······························.126
5.2.2 设备全生命周期的可靠性模型 ·································.127
5.3 基于混合故障率的定期维修策略优化 ································.128
5.3.1 维修活动及维修条件假设 ·······································.128
5.3.2 维修概率模型 ······················································.129
5.3.3 维修策略优化模型 ················································.130
5.3.4 案例分析 ····························································.132
5.4 本章小结 ·····································································.135
参考文献 ···········································································.136
第6 章 基于维纳过程考虑测量误差的两阶段剩余寿命预测 ··············.137
6.1 考虑测量误差的两阶段退化建模和剩余寿命预测 ···················.137
6.1.1 基于维纳过程的两阶段退化建模 ······························.139
6.1.2 变化时刻确定和模型参数固定情况下的
两阶段剩余寿命预测 ·············································.141
6.1.3 变化时刻确定和模型参数随机情况下的
两阶段剩余寿命预测 ·············································.147
6.2 模型参数估计 ······························································.151
6.3 案例分析 ····································································.155
6.3.1 数值仿真分析 ······················································.155
6.3.2 实例研究 ····························································.158
6.4 本章小结 ····································································.166
参考文献 ···········································································.166
第7 章 基于维纳过程的考虑参数依赖的剩余寿命预测 ·····················.168
7.1 考虑参数依赖的线性退化建模和剩余寿命预测 ····················.168
7.1.1 基于维纳过程的线性退化建模 ·································.169
7.1.2 考虑运行条件的剩余寿命预测 ·································.170
7.2 模型参数估计 ······························································.173
7.2.1 先验参数的估计 ···················································.173
7.2.2 随机参数的贝叶斯更新 ··········································.174
7.2.3 基于期望优选化算法的模型参数估计························.177
7.3 案例分析 ····································································.179
7.3.1 数值仿真分析 ······················································.179
7.3.2 案例研究 ····························································.185
7.4 本章小结 ····································································.195
参考文献 ···········································································.195
第8 章 基于机器学习的剩余寿命预测 ··········································.197
8.1 基于机器学习的剩余寿命预测方法 ···································.197
8.1.1 半监督协同训练算法 ·············································.198
8.1.2 LSTM 网络模型 ···················································.201
8.2 基于故障诊断的剩余寿命预测方法 ···································.203
8.2.1 剩余寿命预测框架 ················································.203
8.2.2 BP 神经网络结构与参数设置 ··································.207
8.2.3 案例分析 ····························································.210
8.3 基于LSTM 网络的剩余寿命预测方法 ································.216
8.3.1 基于LSTM 网络的剩余寿命预测框架 ························.216
8.3.2 LSTM 网络参数设定 ·············································.219
8.3.3 案例分析 ····························································.222
8.4 本章小节 ·····································································.232
参考文献 ···········································································.233
第9 章 基于分布拟合的备品备件需求预测 ···································.235
9.1 基于分布拟合的需求预测模型 ··········································.235
9.2 案例分析 ·····································································.237
9.2.1 数据分析 ····························································.237
9.2.2 预测模型 ····························································.244
9.3 本章小结 ·····································································.251
参考文献 ···········································································.251
第10 章 基于缺乏失效位置信息的数据的备品备件需求预测 ············.253
10.1 窗口删失更新过程 ·······················································.253
10.2 基于窗口删失更新过程的备品备件需求预测模型 ················.256
10.2.1 需求预测流程 ·····················································.256
10.2.2 似然函数求解流程 ···············································.257
10.2.3 需求预测 ···························································.258
10.3 案例分析与模型评估 ····················································.262
10.4 本章小结 ···································································.271
参考文献 ···········································································.271