Application of artificial neural network for modelling of discharge inception voltage

The present work attempts to apply artificial neural networks (ANNs) with supervised learning for modelling of discharge inception voltage and stress based on different void parameters. The void depth and gas pressure are the prime considerations of this model. The requisite training data are obtained from experimental studies, published in the literature. Detailed studies are carried out to determine the ANN parameters which give the best results. The results obtained from the ANN are found to be correct within a few % indicating its effectiveness as an efficient tool in estimation.