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Monitoring Porcelain Insulator Condition Based on Leakage Current Characteristics
Insulator monitoring using leakage current characteristics is essential for predicting an insulator’s health. To evaluate the risk of flashover on the porcelain insulator using leakage current, experimental investigation of leakage current indices was carried out. In the first stage of the experimen...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504817/ https://www.ncbi.nlm.nih.gov/pubmed/36143682 http://dx.doi.org/10.3390/ma15186370 |
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author | Salem, Ali Ahmed Lau, Kwan Yiew Ishak, Mohd Taufiq Abdul-Malek, Zulkurnain Al-Gailani, Samir A. Al-Ameri, Salem Mgammal Mohammed, Ammar Alashbi, Abdulaziz Ali Saleh Ghoneim, Sherif S. M. |
author_facet | Salem, Ali Ahmed Lau, Kwan Yiew Ishak, Mohd Taufiq Abdul-Malek, Zulkurnain Al-Gailani, Samir A. Al-Ameri, Salem Mgammal Mohammed, Ammar Alashbi, Abdulaziz Ali Saleh Ghoneim, Sherif S. M. |
author_sort | Salem, Ali Ahmed |
collection | PubMed |
description | Insulator monitoring using leakage current characteristics is essential for predicting an insulator’s health. To evaluate the risk of flashover on the porcelain insulator using leakage current, experimental investigation of leakage current indices was carried out. In the first stage of the experiment, the effect of contamination, insoluble deposit density, wetting rate, and uneven distribution pollution were determined on the porcelain insulator under test. Then, based on the laboratory test results, leakage current information in time and frequency characteristics was extracted and employed as assessment indicators for the insulator’s health. Six indicators, namely, peak current indicator, phase shift indicator, slope indicator, crest factor indicator, total harmonic distortion indicator, and odd harmonics indicator, are introduced in this work. The obtained results indicated that the proposed indicators had a significant role in evaluating the insulator’s health. To evaluate the insulator’s health levels based on the extracted indicator values, this work presents the naïve Bayes technique for the classification and prediction of the insulator’s health. Finally, the confusion matrix for the experimental and prediction results for each indicator was established to determine the appropriateness of each indicator in determining the insulator’s health status. |
format | Online Article Text |
id | pubmed-9504817 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95048172022-09-24 Monitoring Porcelain Insulator Condition Based on Leakage Current Characteristics Salem, Ali Ahmed Lau, Kwan Yiew Ishak, Mohd Taufiq Abdul-Malek, Zulkurnain Al-Gailani, Samir A. Al-Ameri, Salem Mgammal Mohammed, Ammar Alashbi, Abdulaziz Ali Saleh Ghoneim, Sherif S. M. Materials (Basel) Article Insulator monitoring using leakage current characteristics is essential for predicting an insulator’s health. To evaluate the risk of flashover on the porcelain insulator using leakage current, experimental investigation of leakage current indices was carried out. In the first stage of the experiment, the effect of contamination, insoluble deposit density, wetting rate, and uneven distribution pollution were determined on the porcelain insulator under test. Then, based on the laboratory test results, leakage current information in time and frequency characteristics was extracted and employed as assessment indicators for the insulator’s health. Six indicators, namely, peak current indicator, phase shift indicator, slope indicator, crest factor indicator, total harmonic distortion indicator, and odd harmonics indicator, are introduced in this work. The obtained results indicated that the proposed indicators had a significant role in evaluating the insulator’s health. To evaluate the insulator’s health levels based on the extracted indicator values, this work presents the naïve Bayes technique for the classification and prediction of the insulator’s health. Finally, the confusion matrix for the experimental and prediction results for each indicator was established to determine the appropriateness of each indicator in determining the insulator’s health status. MDPI 2022-09-14 /pmc/articles/PMC9504817/ /pubmed/36143682 http://dx.doi.org/10.3390/ma15186370 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Salem, Ali Ahmed Lau, Kwan Yiew Ishak, Mohd Taufiq Abdul-Malek, Zulkurnain Al-Gailani, Samir A. Al-Ameri, Salem Mgammal Mohammed, Ammar Alashbi, Abdulaziz Ali Saleh Ghoneim, Sherif S. M. Monitoring Porcelain Insulator Condition Based on Leakage Current Characteristics |
title | Monitoring Porcelain Insulator Condition Based on Leakage Current Characteristics |
title_full | Monitoring Porcelain Insulator Condition Based on Leakage Current Characteristics |
title_fullStr | Monitoring Porcelain Insulator Condition Based on Leakage Current Characteristics |
title_full_unstemmed | Monitoring Porcelain Insulator Condition Based on Leakage Current Characteristics |
title_short | Monitoring Porcelain Insulator Condition Based on Leakage Current Characteristics |
title_sort | monitoring porcelain insulator condition based on leakage current characteristics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504817/ https://www.ncbi.nlm.nih.gov/pubmed/36143682 http://dx.doi.org/10.3390/ma15186370 |
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