A Method of Gear Fault Diagnosis Based on CWT and ANN

Aimed at the engine rotor fault, a new diagnosis method based on Wavelet Transform and artificial neural network (ANN) is proposed. Firstly, according to the wavelet transform theories, the original signals are sampling repeatedly, and the continuous wavelet transform (CWT) is used for the signals sampled. Afterward, the obtained signals are decomposed to fixed layer so as to obtain the frequency band characteristics of the original signals. So the traditional spectrum features are extracted, and the feature vector is obtained. Second, we use ANN technique to diagnose the selected features intelligently. The results adequately prove that the methods of feature extraction and feature selection advanced in this paper are rational and effective.