Wavelet neural network method for fault diagnosis of push-pull circuits

Abstract

A wavelet neural network method for fault diagnosis of push-pull circuits is presented. Firstly, output voltage signals under faulty conditions are obtained with simulation. Then wavelet coefficients of output voltage signals are gained by Daubechies wavelet decomposition, and faulty feature vectors are extracted from coefficients. After training the networks by faulty feature vectors, the wavelet neural networks model of the circuit fault diagnosis system is built. The simulation result shows the fault diagnosis method of the push-pull circuits with wavelet neural network is effective.