Application of WAVELET-SVM in Fault Diagnosis for the UV Control System
2011 ◽
Vol 65
◽
pp. 199-203
Keyword(s):
Wavelet Analysis extracts the main feature from the fault signal through wavelet transformation, so it is advantageous to withdraw fault characteristic for fault diagnosis. Support Vector Machine (SVM) has shown its good classification performance in fault diagnosis. A new method of fault diagnosis for UV control system based on WAVELET-SVM is raised. The sensor output is sampled in frequency domain and it is preprocessed by wavelet to extract main vectors of the fault features. Fault patterns under various states are classified using multi-class SVM, and fault diagnosis is realized. The simulation results show that WAVELET-SVM is feasible to detect and locate faults quickly and exactly and has high robustness.
2013 ◽
Vol 22
(01)
◽
pp. 1250038
◽
2013 ◽
Vol 422
◽
pp. 83-88
2008 ◽
Vol 07
(01)
◽
pp. 151-155
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2019 ◽
Vol 14
(4)
◽
pp. 487-492
Keyword(s):
2005 ◽
Vol 127
(3)
◽
pp. 294-303
◽
2014 ◽
Vol 666
◽
pp. 203-207
2011 ◽
Vol 121-126
◽
pp. 268-272
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