Application of WAVELET-SVM in Fault Diagnosis for the UV Control System
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.
Zhenyu Du and Bin Liu
S. W. Wang et al., "Application of WAVELET-SVM in Fault Diagnosis for the UV Control System", Applied Mechanics and Materials, Vol. 65, pp. 199-203, 2011