Detection and classification of impulse faults in transformer using wavelet transform and artificial neural network

This paper aims at describing a method for the detection and classification of impulse faults in a transformer winding using wavelet transform and an artificial neural network. The method is explained by considering the lumped parameter model of a winding. The WT decomposes the signal and RMS value of the detailed signal is extracted to train the ANN. The simulation results are satisfactory in detection and classification of faults.