《基于混沌和小波的故障信息诊断》不拟追求故障信息诊断理论方法的全面性,而是**论述以混沌理论和多分辨分析理论为基础的强干扰背景的故障信息诊断新理论、新方法、新经验。近年来混沌工程学成为工程领域广泛关注的课题,但混沌理论在故障诊断中的应用研究还只是刚刚起步。此外,近年来出现的小波理论,以其特有的优势成了故障诊断领域的另一个热门话题,但是由于其概念体系的数学抽象性,限制了它的工程应用。《基于混沌和小波的故障信息诊断》在系统深入的理论依据基础上,提出了利用混沌振子的间歇混沌现象进行强噪声背景微弱信号检测的方法,并将其应用到强干扰背景下的故障信息诊断中。

Chapter 1 Introduction
1.1 Fault diagnosis significance of hydraulic system
1.2 Current research situations of fault detection and diagnosis technology 0f hydraulic system
1.3 Main research contents of this book

Chapter 2 Chaotic motion characters and their applications in engineering
2.1 Research branches of engineering chaos
2.2 Definitions of chaos
2.3 Characteristics of chaotic motion
2.4 Ways leading to chaos

Chapter 3 Methods for identifying chaos
3.1 Direct observing method of phase traiectory
and time course of state variables
3.2 Stroboscopic sampling method
3.3 Method of Poincare surface of section
3.4 Pseudo phase space method
3.5 Method of selGpower density spectrum analysis
3.6 Lyapunov exponent analysis method
3.7 Fractal dimension analysis method

Chapter 4 Periodic orbits of Duffing oscillator
4.1 Dufring equations and Melnikov methods
4.2 Elliptic functions and elliptic integrals
4.3 Conditions of chaos producing in Duffing oscillator
4.4 Existence conditions of periodic orbits in Duffing oscillator

Chapter 5 Chaotic and intermittent chaotic motion of Duffing oscillator
5.1 Numerical experiment research of chaotic motion of Duffing oscillator
5.2 Intermittent chaotic motion mechanism of Duffing oscillator
5.3 Influences of noise to chaotic motion of Duffing oscillator
5.4 Comparison of intermittent chaos-based weak signal detection method with stochastic resonance phenomenon
5.5 Scheme of applying Duffirig oscillator to fault diagnosis
5.6 Virtual instrument—based weak ultrasonic signal detecting system

Chapter 6 Wavelet transform and time.frequency analysis
6.1 Review on applications of wavelet analysis in signal processing
6.2 Wavelets and wavelet transform
6.3 Comparison of Fourier analysis and wavelet analysis
6.4 Windowed Fourier transform and time—frequency analysis
6.5 Wavelet transform and time-frequency analysis

Chapter 7 Orthogonal multiresolution analysis and orthogonal wavelet packet analysis for signals
7.1 Orthogonal multiresolution analysis and construction of orthogonal wavelets
7.2 Orthogonal wavelet packet analysis
7.3 Signal decomposition and reconstruction
7.4 Characters of chaotic motion signal under orthogonal wavelet packet analysis
7.5 Signal singularity detection
7.6 Noise elimination in signal based on wavelet transform

Chapter 8 Chaos and wavelet based fault diagnosis examples
8.1 Fault diagnosis for hydraulic pump
8.2 Fault diagnosis for sensor
8.3 Advantages of theoretical methods advanced in this book

Chapter 9 Fault diagnosis system used in mechanical equipments
9.1 Structure and Fault analysis of the rolling mill
9.2 Hardware design of the diagnosis system
9.3 Software design of the diagnosis system
9.4 The experiment of the system and the results analysis
References
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