《轨道交通装备健康管理》全面介绍了工程系统健康管理的相关概念、技术体系和设计流程，重点分析了典型的关键技术，以机械智能诊断与健康预测为核心，介绍了传感器与数据获取、信号处理与特征提取、故障诊断及失效预测、信息融合及智能决策等诸多方法。按照“概念-内容-技术-算法-实例”的逻辑主线，将各个关键方法由浅入深、通俗易懂地娓娓道来，为轨道交通装备健康管理的学习及工程系统相关科学研究提供了重要参考。
　　《轨道交通装备健康管理》既适合各高校及研究院所的相关人员学习使用，也适合作为从事轨道交通高端装备系统设计及工程实现的技术人员参阅，此外，《轨道交通装备健康管理》内容丰富，算法叙述由浅入深，适合作为相关课程的本科或研究生教材。

PREFACE
Chapter 1 Background of Systems Health Management
1．1 Introduction
1．2 Maintenance Strategy
1．3 From Maintenance to PHM
1．4 Definitions and Terms of Systems Health Management
1．5 Preface to Book Chapters
1．6 References

Chapter 2 Design Approach for Systems Health Management
2．1 Introduction
2．2 Systems Engineering
2．3 Systems Engineering， Dependability， and Health Management
2．4 SHM Lifecycle Stages
2．4．1 Research stage
2．4．2 Requirements development stage
2．4．3 System/functionalanalysis
2．4．4 Design， synthesis andintegration
2．4．5 System test and evaluation
2．4．6 HM system maturation
2．5 A Systems-based Methodology for CBM/PHM Design
2．6 References

Chapter 3 Technical Approaches for Systems Health Management
3．1 Introduction
3．2 Data-Driven Approaches
3．3 Model-Based Approaches
3．4 Hybrid Approaches
3．5 OSA-CBM Architecture
3．6 Problems during Implementation
3．7 Related Techniques
3．8 References

Chapter 4 Sensors and Data Acquisition
4．1 Introduction
4．2 Data Acquisition
4．2．1 Selecting a proper measure
4．2．2 Vibration transducers
4．2．3 Transducer selection
4．2．4 Transducermounting
4．2．5 Transducer location
4．2．6 Frequency spans
4．2．7 Data display
4．3 References

Chapter 5 Signal Processing and Feature Representation
5．1 Signal Processing
5．2 Feature Representation
5．2．1 Features in time domain
5．2．2 Features in frequency domain
5．2．3 Features in auto-regression domain
5．3 References

Chapter 6 Feature Extraction
6．1 Introduction
6．2 BasicConcepts
6．2．1 Pattern and feature vector
6．2．2 Class
6．3 Parameter Evaluation Technique
6．4 Principal Component Analysis (PCA)
6．5 Kernel PCA
6．6 Fisher Discriminant Analysis (FDA)
6．7 Linear Discriminant Analysis (LDA)
6．8 References

Chapter 7 Fault Diagnosis
7．1 Introduction
7．2 Data-Driven Diagnosis
7．2．1 Classifierconcepts
……
Chapter 8 Failure Prognosis
Chapter 9 Data Fusion
Chapter 10 Cases Study for Rail Vehicle Systems Health Management