论文信息 - Detection and classification of impulse faults in transformer using wavelet transform and artificial neural network

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.

N. Vanamadevi | S. Santhi | M. Arivamudhan

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