Principle and Application of Fault Diagnosis for Non-stationary Signals in Mechanical Equipment

Author: He Zhengjia
Publisher:
Publish Date: 2001-11-19
Features: This book discusses the generation and characteristics of non-stationary signals in mechanical equipment, the physical significance and engineering background of signal orthogonal decomposition. It introduces non-stationary signal processing methods for extracting fault information, such as the Wigner-Ville time-frequency distribution, short-time Fourier transform, wavelet transform, wavelet packet analysis, harmonic wavelet, Laplace wavelet, Hermitian wavelet, and matching pursuits (matching pursuits), including their basic principles and applications. It clarifies the reprocessing techniques after wavelet transformation of signals, such as wavelet packet autoregressive spectral analysis, wavelet packet band energy monitoring, wavelet fractal analysis, harmonic wavelet axis trajectory method, genetic wavelet analysis, wavelet packet fuzzy clustering neural network, as well as the online monitoring and diagnosis network system for mechanical equipment that implements these methods and techniques. It provides examples of the application of these methods in industrial and mining enterprises for monitoring and diagnosing mechanical equipment. The book is based on advanced materials and is highly practical, making it suitable for use and reference by a broad range of technical personnel engaged in mechanical equipment condition monitoring and fault diagnosis, as well as equipment management and maintenance. It is also suitable as a textbook or reference book for senior undergraduate and graduate students in mechanical, energy, and power engineering at universities.