Insulator contour optimization by a neural network

Contour optimization of axi-symmetric insulators in multi-dielectric arrangements by a neural network (NN) has been carried out to obtain not only a uniform but also a complex electric stress distribution along the insulator surface. Three case studies have been reported In detail. Multilayer feed-forward networks with error backpropagation and also with resilient propagation learning algorithms have been employed. The training and test data have been prepared by means of electric field calculations. The results show that optimized insulator contours have been obtained with an acceptable degree of accuracy with the help of a trained NN.