MODELING OF BREAKDOWN VOLTAGE OF SOLID INSULATING MATERIALS BY ARTIFICIAL NEURAL NETWORK

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 usedmethod 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.

Authors and Affiliations

Lav Singh Mathur

Keywords

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  • EP ID EP112423
  • DOI 10.5281/zenodo.56011
  • Views 82
  • Downloads 0

How To Cite

Lav Singh Mathur (30). MODELING OF BREAKDOWN VOLTAGE OF SOLID INSULATING MATERIALS BY ARTIFICIAL NEURAL NETWORK. International Journal of Engineering Sciences & Research Technology, 5(6), 788-797. https://europub.co.uk/articles/-A-112423