Application of the neural network to detecting corona discharge occurring in power cables

A 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 feedforward 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 waveforms obtained by a fast Fourier transform (FFT) method as input patterns is also investigated. The network with FFT pretreatment is found to show better performance than the one without FFT pretreatment.