Fault diagnosis of push-pull circuits using least squares wavelet support vector machines

An approach for fault diagnosis of push-pull circuits based on least squares wavelet support vector machines (LS-WSVM) is presented. Output voltage signals of push-pull circuits under faulty conditions are obtained with simulation. Then wavelet coefficients of output voltage signals are gained by wavelet decomposition, and faulty feature vectors are extracted from coefficients. After training multi-class LS-WSVM by faulty feature vectors, the LS-WSVM classifiers of the circuit fault diagnosis system are built. The simulation result shows the fault diagnosis method of the push-pull circuits with multi-class LS-WSVM is effective.