DocumentCode :
2083720
Title :
Fault diagnosis for power unit based on wavelet packet PCA-SVM
Author :
Liao Wei ; Wang Huan
Author_Institution :
Hebei Univ. of Eng., Handan, China
fYear :
2010
fDate :
29-31 July 2010
Firstpage :
3851
Lastpage :
3855
Abstract :
In this paper, a new method of fault diagnosis for power unit based on wavelet packet PCA-SVM is proposed. Firstly, using wavelet packet transformation to extract each band of energy as the initial samples; Secondly, taking principal component analysis to excavate the features of the initial samples, eliminating the correlation between data while ensure the integrity of data as far as possible, then the smallest diagnostic features were got. The fault diagnosis model based on SVM and the smallest features can effectively reduce the computational complexity and the difficulty of obtaining fault characteristics. Simulation results show that the proposed method can effectively shorten the time of diagnosis, improve the diagnostic efficiency, this method is an effective way to diagnosis the fault for power unit.
Keywords :
fault diagnosis; power apparatus; power engineering computing; principal component analysis; support vector machines; wavelet transforms; PCA-SVM; computational complexity; fault diagnosis model; power unit; principal component analysis; wavelet packet transformation; Fault diagnosis; Feature extraction; Principal component analysis; Support vector machines; Wavelet analysis; Wavelet packets; Fault Diagnosis; PCA; Power Unit; SVM; Wavelet Packet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
Type :
conf
Filename :
5572518
Link To Document :
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