Condition based monitoring of gapless surge arrester using electrical and thermal parameters
A new method to assess the condition of metal-oxide surge arresters is presented. The thermal image and third harmonic leakage current are used as an indicator. The correlation between the leakage current and temperature of the arrester is processed using a neural network. The temperature profile of...
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my.utm.906482021-04-29T23:28:19Z http://eprints.utm.my/id/eprint/90648/ Condition based monitoring of gapless surge arrester using electrical and thermal parameters Novizon, Novizon Malek, Z. A. Syafii, Syafii Ahmad, M. H. Aulia, Aulia Ulfiah, S. A. TK Electrical engineering. Electronics Nuclear engineering A new method to assess the condition of metal-oxide surge arresters is presented. The thermal image and third harmonic leakage current are used as an indicator. The correlation between the leakage current and temperature of the arrester is processed using a neural network. The temperature profile of arrester, ambient temperature and humidity were as input to the neural network and the peak value of the third harmonic resistive current as a target. Results are presented with the training of neural network close to the target and testing result is 98% successfully. 2019 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/90648/1/ZulkurnainAbdulMalek2019_ConditionBasedMonitoringofGapless.pdf Novizon, Novizon and Malek, Z. A. and Syafii, Syafii and Ahmad, M. H. and Aulia, Aulia and Ulfiah, S. A. (2019) Condition based monitoring of gapless surge arrester using electrical and thermal parameters. In: 1st Conference on Innovation in Technology and Engineering Science, CITES 2018, 8-9 Nov 2018, Padang, West Sumatera, Indonesia. http://dx.doi.org/10.1088/1757-899X/602/1/012007 |
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TK Electrical engineering. Electronics Nuclear engineering Novizon, Novizon Malek, Z. A. Syafii, Syafii Ahmad, M. H. Aulia, Aulia Ulfiah, S. A. Condition based monitoring of gapless surge arrester using electrical and thermal parameters |
description |
A new method to assess the condition of metal-oxide surge arresters is presented. The thermal image and third harmonic leakage current are used as an indicator. The correlation between the leakage current and temperature of the arrester is processed using a neural network. The temperature profile of arrester, ambient temperature and humidity were as input to the neural network and the peak value of the third harmonic resistive current as a target. Results are presented with the training of neural network close to the target and testing result is 98% successfully. |
format |
Conference or Workshop Item |
author |
Novizon, Novizon Malek, Z. A. Syafii, Syafii Ahmad, M. H. Aulia, Aulia Ulfiah, S. A. |
author_facet |
Novizon, Novizon Malek, Z. A. Syafii, Syafii Ahmad, M. H. Aulia, Aulia Ulfiah, S. A. |
author_sort |
Novizon, Novizon |
title |
Condition based monitoring of gapless surge arrester using electrical and thermal parameters |
title_short |
Condition based monitoring of gapless surge arrester using electrical and thermal parameters |
title_full |
Condition based monitoring of gapless surge arrester using electrical and thermal parameters |
title_fullStr |
Condition based monitoring of gapless surge arrester using electrical and thermal parameters |
title_full_unstemmed |
Condition based monitoring of gapless surge arrester using electrical and thermal parameters |
title_sort |
condition based monitoring of gapless surge arrester using electrical and thermal parameters |
publishDate |
2019 |
url |
http://eprints.utm.my/id/eprint/90648/1/ZulkurnainAbdulMalek2019_ConditionBasedMonitoringofGapless.pdf http://eprints.utm.my/id/eprint/90648/ http://dx.doi.org/10.1088/1757-899X/602/1/012007 |
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13.18916 |