Study on the fault diagnosis based on wavelet packet and support vector machine

The method of intelligent fault diagnosis based on wavelet packet transform and support vector machine is presented. The key to fault diagnosis is feature extracting and fault classifying. According to the method, the energy of frequency bands after wavelet packet decomposition of the vibration signals is taken as the extracted features and input to support vector machine(SVM). Then, fault pattern is recognized using SVM multiple fault classifier. Finally, the proposed method is applied to the fault diagnosis of rolling bearings, and the results of the experiment demonstrate that the proposed method is efficient in intelligent fault diagnosis.