Title :
Isolated singularity points recognition of hydroelectric generators fault signals based on CWT
Author :
Yang, Wang ; Tao, Sun ; Tianshu, Huang ; Dong, Sun
Author_Institution :
Inst. of Electron. Inf., Wuhan Univ., China
fDate :
31 Aug.-4 Sept. 2004
Abstract :
In order to extract fault feature information from low frequency vibrating transient signal of the main shaft of hydro-generator, an elective method is put forward. With bi-orthogonal spline wavelet, the method is designed to locate the isolated singularity points and estimate their singularity degree by applying WTMM (wavelet transformation maximal module) and MRA (multi-resolving analysis) of continuous wavelet transform (CWT) and least square algorithm and taking account of the length, intensity and Lipschitz exponent of WTMM lines. Result shows that the method has perfect effect.
Keywords :
fault diagnosis; feature extraction; hydroelectric generators; least squares approximations; signal processing; splines (mathematics); wavelet transforms; Lipschitz exponent; bi-orthogonal spline wavelet; continuous wavelet transform; fault feature information extraction; frequency vibrating transient signal; hydroelectric generators fault signal; isolated singularity points recognition; least square algorithm; multiresolving analysis; wavelet transformation maximal module; Algorithm design and analysis; Continuous wavelet transforms; Data mining; Feature extraction; Frequency; Hydroelectric power generation; Multiresolution analysis; Shafts; Signal generators; Wavelet analysis;
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
DOI :
10.1109/ICOSP.2004.1442296
