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 International Journal of Engineering and Technology Research (IJEATR)

ISSN:  2327-0349  (Online)



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Vol. 4, No. 1, June 2016

Table of Contents

Articles


Modeling Of Breakdown Voltage of Solid Insulating Materials by Artificial Neural Network

Authors: Lav Singh Mathur, Mr. Amit Agrawal, Dr. Dharmendra Kumar Singh

Abstract

This paper presents a model to find out the breakdown voltage of solid insulating materials under AC excitation condition by employing the artificial neural network method. The paper gives a brief introduction to multilayer perceptrons and resilient back-propagation. A relation between input variables and output variables i. e. breakdown voltage is demonstrated. The inputs to the neural networks are the thickness of material, diameter of void, depth of void and permittivity of materials. Neural network methodology is the one of the most popular and widely used method for the analysis of voids. ANN is built to train the multilayer perceptrons in the context of regression analysis. Back-propagation algorithm is used for learning and to train the ANN and it is provides a custom choice of activation and error function. MATLAB software is used for designed, trained and tested in the ANN.

Keywords: Permittivity, Breakdown Voltage, ANN, Insulation Sample, Multilayer Feed-forward Neural Network, Voids, Thickness.