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6CCVD Research

Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks

At a Glance

Section titled ā€œAt a Glanceā€
MetadataDetails
Publication Date2018-02-01
JournalJournal of Advanced Dielectrics
AuthorsSakshi Singh, M.M. Mohsin, A. Masood
InstitutionsAligarh Muslim University
Citations1

Abstract

Section titled ā€œAbstractā€

In this research work, a few sets of experiments have been performed in high voltage laboratory on various cellulosic insulating materials like diamond-dotted paper, paper phenolic sheets, cotton phenolic sheets, leatheroid, and presspaper, to measure different electrical parameters like breakdown strength, relative permittivity, loss tangent, etc. Considering the dependency of breakdown strength on other physical parameters, different Artificial Neural Network (ANN) models are proposed for the prediction of breakdown strength. The ANN model results are compared with those obtained experimentally and also with the values already predicted from an empirical relation suggested by Swanson and Dall. The reported results indicated that the breakdown strength predicted from the ANN model is in good agreement with the experimental values.

Tech Support

Section titled ā€œTech Supportā€

Original Source

Section titled ā€œOriginal Sourceā€

References

Section titled ā€œReferencesā€
  1. 1954 - Dielectric Materials and Applications
  2. 1927 - International Critical Tables of Numerical Data, Physics, Chemistry and Technology
  3. 2005 - Neural Networks: A Comprehensive Foundation
  4. 2002 - Neural Network Toolbox Userā€™s Guide

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