Detection of partial discharges in power cables by neural network

Abstract

In this paper, the system of detecting corona discharges automatically with an artificial neural network is examined and a network which can distinguish between corona and noise patterns occurring in power cables is investigated. A feed-forward type of a neural network with three layers, i.e., input, hidden, and output layers is used. It is found that the network which learns only corona and no noise patterns does not show a good performance. This means that the network should learn both corona and noise patterns even for recognizing only corona discharges. The network which uses frequency spectra of the waveforms obtained by fast fourier transform (FFT) method as input patterns is also investigated. The network with FFT pretreatment is found to show a better performance than the one without FFT pretreatment.