A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree

The insulation state of high-voltage cables in coal mines directly influences the reliability of power supply in coal mines and the level of safe production. In this paper, the degradation mechanism of cable insulation is analyzed, and an online monitoring technology of cable insulation in coal mine...

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Detalles Bibliográficos
Autores principales: Fu, Wenjun, Xu, Ying, Gao, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9152389/
https://www.ncbi.nlm.nih.gov/pubmed/35655513
http://dx.doi.org/10.1155/2022/2247017
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author Fu, Wenjun
Xu, Ying
Gao, Yan
author_facet Fu, Wenjun
Xu, Ying
Gao, Yan
author_sort Fu, Wenjun
collection PubMed
description The insulation state of high-voltage cables in coal mines directly influences the reliability of power supply in coal mines and the level of safe production. In this paper, the degradation mechanism of cable insulation is analyzed, and an online monitoring technology of cable insulation in coal mines based on decision tree is proposed, the technical principle of the judgment method of cable degradation based on decision tree is studied, the feasibility of this technology is verified through simulation, the existing online monitoring solutions for cable insulation are analyzed, and a wide-area synchronous measurement and monitoring system for cable insulation is designed. This technology has been applied in Chinese coal mine enterprises in China and achieved a good effect.
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spelling pubmed-91523892022-06-01 A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree Fu, Wenjun Xu, Ying Gao, Yan Comput Intell Neurosci Research Article The insulation state of high-voltage cables in coal mines directly influences the reliability of power supply in coal mines and the level of safe production. In this paper, the degradation mechanism of cable insulation is analyzed, and an online monitoring technology of cable insulation in coal mines based on decision tree is proposed, the technical principle of the judgment method of cable degradation based on decision tree is studied, the feasibility of this technology is verified through simulation, the existing online monitoring solutions for cable insulation are analyzed, and a wide-area synchronous measurement and monitoring system for cable insulation is designed. This technology has been applied in Chinese coal mine enterprises in China and achieved a good effect. Hindawi 2022-05-23 /pmc/articles/PMC9152389/ /pubmed/35655513 http://dx.doi.org/10.1155/2022/2247017 Text en Copyright © 2022 Wenjun Fu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Fu, Wenjun
Xu, Ying
Gao, Yan
A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree
title A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree
title_full A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree
title_fullStr A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree
title_full_unstemmed A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree
title_short A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree
title_sort study on insulation monitoring technology of high-voltage cables in underground coal mines based on decision tree
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9152389/
https://www.ncbi.nlm.nih.gov/pubmed/35655513
http://dx.doi.org/10.1155/2022/2247017
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