Application of time-frequency distribution and neural networks for fault classification in power electronics

A new method of fault analysis and detection by signal classification in frequency converters is presented. The Wigner Ville time frequency distribution is used to produce the representation of the signal and the probabilistic neural network as a classifier. The accuracy and robustness of the proposed method is investigated on signals obtained during the different fault mode operations of the industrial frequency converter.