Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks
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 s...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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World Scientific Publishing
2018-02-01
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| Series: | Journal of Advanced Dielectrics |
| Subjects: | |
| Online Access: | http://www.worldscientific.com/doi/pdf/10.1142/S2010135X18500030 |
| _version_ | 1818271983148728320 |
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| author | Sakshi Singh M. M. Mohsin Aejaz Masood |
| author_facet | Sakshi Singh M. M. Mohsin Aejaz Masood |
| author_sort | Sakshi Singh |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-12T21:34:50Z |
| format | Article |
| id | doaj.art-9a5be58074014623aeb2aed678478b39 |
| institution | Directory Open Access Journal |
| issn | 2010-135X 2010-1368 |
| language | English |
| last_indexed | 2024-12-12T21:34:50Z |
| publishDate | 2018-02-01 |
| publisher | World Scientific Publishing |
| record_format | Article |
| series | Journal of Advanced Dielectrics |
| spelling | doaj.art-9a5be58074014623aeb2aed678478b392022-12-22T00:11:13ZengWorld Scientific PublishingJournal of Advanced Dielectrics2010-135X2010-13682018-02-01811850003-11850003-410.1142/S2010135X1850003010.1142/S2010135X18500030Prediction of breakdown strength of cellulosic insulating materials using artificial neural networksSakshi Singh0M. M. Mohsin1Aejaz Masood2Department of Electrical Engineering, Z. H. College of Engineering & Technology, Aligarh Muslim University, Aligarh, UP 202002, IndiaDepartment of Electrical Engineering, Z. H. College of Engineering & Technology, Aligarh Muslim University, Aligarh, UP 202002, IndiaDepartment of Electrical Engineering, Z. H. College of Engineering & Technology, Aligarh Muslim University, Aligarh, UP 202002, IndiaIn 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.http://www.worldscientific.com/doi/pdf/10.1142/S2010135X18500030Cellulosic materialsrelative permittivityloss tangentbreakdown strengthANN |
| spellingShingle | Sakshi Singh M. M. Mohsin Aejaz Masood Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks Journal of Advanced Dielectrics Cellulosic materials relative permittivity loss tangent breakdown strength ANN |
| title | Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks |
| title_full | Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks |
| title_fullStr | Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks |
| title_full_unstemmed | Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks |
| title_short | Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks |
| title_sort | prediction of breakdown strength of cellulosic insulating materials using artificial neural networks |
| topic | Cellulosic materials relative permittivity loss tangent breakdown strength ANN |
| url | http://www.worldscientific.com/doi/pdf/10.1142/S2010135X18500030 |
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