描述
开 本: 16开纸 张: 胶版纸包 装: 平装-胶订是否套装: 否国际标准书号ISBN: 9787512428102
本书可作为飞机维修专业的教材，并可作为飞机维修及相关专业的研究生和技术人员的参考书。
In this book, the complete theory systems and frameworks of aircraft
testability and fault prognosis techniques are established.The common
testability design analysis, fault diagnosis and prognosis methods of aircraft
are introduced comprehensively. The objects of the book are to stand out the
characteristics of aviation, to pursue comprehensive and detailed content, and
to emphasize the combination of theory and application.
In the aspect of theory, the advanced theories and techniques including
signal analysis, multisignal modeling, test strategy optimization, sensor placement and
sensing strategies,fault diagnosis methods, fault prognosis techniques and so
on, which are involved in aircraft testability and fault prognosis, are all
introduced in detail. In this book, aircraft testability and fault prognosis
techniques include: testability modeling and analysis for aircraft system fault
diagnosis and prognosis, vibration monitoring and fault diagnosis for aeroengine, trend analysis of aeroengine, and
nondestructive testing of aircraft structure. In this book, many diagnosis
cases are arranged in order to make theory to combine practice.
The book can be acted as the teaching material for senior aircraft
maintenance majors, and reference book for postgraduate and technician of this
major and related majors.
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 aeroengie
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 System
Diagnosis 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 ault
diagnosis
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 artificial neural
netwrk
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 and
Compnent
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 Diagnosis
Techniques 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 for
Aircraft 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 nondestructive
testing 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 on
plane 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
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