Chapter 1  Introduction1
1.1 The significance of aircraft diagnosis and prognosis technology
1.2 Development of fault diagnosis and prognosis for aircraft system
1.3 Development of aircraft maintenance theory
1.3.1 Aircraft breakdown maintenance system
1.3.2 Aircraft hard time maintenance system
1.3.3 Aircraft reliability centered maintenance system
1.3.4 Aircraft on condition maintenance system
1.4 Condition monitoring and fault diagnosis techniques for aeroengie
1.4.1 Research objects
1.4.2 The basic theory
1.4.3 Condition monitoring and fault diagnosis system aero engine
1.5 Inspection and repair techniques for aircraft structure
1.5.1 Structure inspection and maintenance goals
1.5.2 Aircraft design service goal and economic service life
1.5.3 Aircraft structure integrity and aging aircraft structure maintenance
1.5.4 The aircraft nondestructive detection techniques
1.5.5 Aircraft leakage detection technology
1.6 Review questions
Chapter 2  Testability Designing Analysis for SystemDiagnosis and Progosis
2.1 Introduction
2.2 Diagnostic and prognostic system requirements
2.3 Designing in fault diagnostic and prognostic systems
2.4 Diagnostic and prognostic functional layers
2.5 Testability modeling for complex system fault diagnosis
2.5.1 Types of failures
2.5.2 Designing completely testable systems using TEAMS
2.5.3 Testability design analysis based on MHFDG model for aircraft system aultdiagnosis
2.6 Test strategy optimization method for aircraft system fault diagnosis
2.7 Review questions
Chapter 3  Sensors and Sensing Strategies
3.1 Basic concepts of sensors, transducers and sensing strategies
3.2 Sensors application and quality requirements
3.2.1 Application
3.2.2 Quality requirements
3.3 The types of transducers
3.4 Type of sensors
3.4.1 Gases or liquids pressure sensors
3.4.2 Mechanical/structural sensor systems
3.4.3 Performance/operational sensors
3.4.4 Other new sensors
3.5 Sensor placement
3.6 Wireless sensor networks
3.7 Digital signal processing system
3.8 Review questions
Chapter 4  Fault Signal Analysis and Processing
4.1 The concept and classification of signal
4.1.1 The concept of signal
4.1.2 The classification of signal
4.2 Time domain analysis
4.2.1 Amplitude domain
4.2.2 Time difference domain
4.2.3 Stationary stochastic process
4.2.4 Ergodic stochastic process
4.3 Frequency domain analysis
4.3.1 Impulse function and convolution
4.3.2 Fourier series
4.3.3 Fourier transform
4.4 Review questions
Chapter 5  Theories for Fault Recognition and Diagnosis
5.1 Introduction
5.2 Fault diagnosis framework
5.2.1 Relevant definitions
5.2.2 Fault monitoring and diagnosis framework
5.3 Bayesian classification
5.3.1 Condition probability
5.3.2 Total probability formula
5.3.3 The Bayes decision based on minimum error ratio
5.3.4 Bayes decision based on the minimum average risk
5.4 Classification based on distance functions
5.4.1 Space distance (geometric distance) functions
5.4.2 Discriminant method with information distance
5.5 Fuzzy diagnosis
5.5.1 Membership function
5.5.2 Fuzzy vector
5.5.3 Fuzzy relationship
5.6 Grey diagnosis
5.6.1 Grey system modeling
5.6.2 The grey relation grade analysis
5.7 Neural network diagnosis
5.7.1 The topology structure and learning rules for artifi neuralnetwrk
5.7.2 Multlayer feed forward neural networks model and BP algorithm
5.8 Support vector machines diagnosis
5.8.1 Fundamental problems and methods of the machine learning
5.8.2 The core contents of statistical learning theory
5.8.3 Support vector machine
5.9 Expert system diagnosis
5.9.1 Introduction
5.9.2 Traditional rule based expert system principle
5.9.3 Diagnosis principle of neural network expert system
5.10 Model based fault diagnosis
5.10.1 Common fault modeling
5.10.2 Dynamic systems modeling
5.11 Data based fault diagnosis
5.11.1 Alarm bounds method
5.11.2 Statistical clustering methods
5.11.3 Neural network classification and clustering
5.12 Review questions
Chapter 6  Prognosis Approaches for Aircrafts System andCompnent
6.1 Introduction
6.1.1 Revolutionary concepts made possible by prognostics
6.1.2 Prognostic applications related to aircraft
6.2 Prognostics approaches used in the aeronautical science164
6.2.1 Reliability based approach
6.2.2 Physics/model based approach
6.2.3 Data driven approach
6.2.4 Hybrid/fusion approach
6.3 Physics/model based fault prognosis
6.3.1 The state estimation
6.3.2 The RUL prediction
6.3.3 A case：pneumatic valves leakage prediction in refuelling systm
6.4 Data driven performance prognosis
6.4.1Data driven approach based on feed forward NN
6.4.2 Data driven prognostics based on Dynamic Wavelet Neural Netwrks
(DWNNs)
6.4.3 A case: gas turbine performance prognosis
6.5 Time series prediction methods
6.5.1 Linear time series prediction methods
6.5.2 Nonlinear time series prediction methods
6.5.3 Time series prediction based on neural networks
6.5.4 The prediction method using support vector machine
6.6 Review questions
Chapter 7  Condition Monitoring and Fault DiagnosisTechniques for Aeroegine1
7.1 Aeroengine state diagnosis
7.1.1 Basic principle of engine state diagnosis
7.1.2 Basic concepts for fault diagnosis
7.1.3 Fault equation
7.1.4 Conclusion
7.2 The vibration monitoring and diagnosis system for aero engine
7.2.1 The main exciting sources of aero engine
7.2.2 The common faults mechanism analysis of rotor system
7.3 Common faults and their diagnosis of gear
7.3.1 Common fault forms and fault causes of gear
7.3.2 Vibration mechanism of gear
7.3.3 The common signal analysis and processing methods for gear
ault diagnosis
7.3.4 The signal characteristics and precision diagnosis of common
aults of gear
7.4 Review questions
Chapter 8  Nondestructive Testing Techniques forAircraft Structural Inspction
8.1 The significance and function of NDT in aviation maintenance
8.1.1 Nondestructive testing for old aircraft
8.1.2 Nondestructive testing of new materials on new aircraft
8.1.3 The role of nondestructive testing in aircraft calendar life study
8.1.4  The role of nondestructivetesting in the aircraft fatigue crack
growth monitoring
8.1.5 Aircraft nondestructive testing techniques
8.2 Ultrasonic testing
8.2.1 Summary
8.2.2 Ultrasonic propagation velocity and acoustic impedance
8.2.3 The reflection and transmission of ultrasonic wave vertically
irradiating on plane interface
8.2.4The reflection and refraction of ultrasonic slantwise incidence onplane interface
8.2.5 Ultrasonic testing method
8.2.6 Application of ultrasonic testing in aviation maintenance
8.3 Eddy current testing method
8.3.1 Summary
8.3.2 Eddy current testing principle
8.3.3 Eddy current testing features
8.3.4 Application for eddy current testing in aviation maintenance
8.4 Magnetic particle testing method
8.4.1 Summary
8.4.2Basic principle of magnetic particle testing
8.4.3 Characteristics of magnetic particle testing
8.4.4 The application of magnetic particle testing in aviation maintenance
8.5 Review questions
References

本书详细介绍了涉及飞机测试和预测技术方面的先进理论和技术，建立了飞机可测试性和故障预测技术的完整理论体系和框架，全面介绍了飞机常见的可测试性和预测方法，包括故障诊断和预测系统设计、可测性建模方法、传感器和传感策略等。