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Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines
With the increasing demand for electricity transmission and distribution, single-phase grounding accidents, which cause great economic losses and casualties, have occurred frequently. In this study, a Bayesian network (BN)-based risk assessment model for representing single-phase grounding accidents...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7142559/ https://www.ncbi.nlm.nih.gov/pubmed/32178361 http://dx.doi.org/10.3390/ijerph17061841 |
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author | Zhang, Jun Bian, Haifeng Zhao, Huanhuan Wang, Xuexue Zhang, Linlin Bai, Yiping |
author_facet | Zhang, Jun Bian, Haifeng Zhao, Huanhuan Wang, Xuexue Zhang, Linlin Bai, Yiping |
author_sort | Zhang, Jun |
collection | PubMed |
description | With the increasing demand for electricity transmission and distribution, single-phase grounding accidents, which cause great economic losses and casualties, have occurred frequently. In this study, a Bayesian network (BN)-based risk assessment model for representing single-phase grounding accidents is proposed to examine accident evolution from causes to potential consequences. The Bayesian network of single-phase grounding accidents includes 21 nodes that take into account the influential factors of environment, management, equipment and human error. The Bow-tie method was employed to build the accident evolution path and then converted to a BN. The BN conditional probability tables are determined with reference to historical accident data and expert opinion obtained by the Delphi method. The probability of a single-phase grounding accident and its potential consequences in normal conditions and three typical accident scenarios are analyzed. We found that “Storm” is the most critical hazard of single-phase grounding, followed by “Aging” and “Icing”. This study could quantitatively evaluate the single-phase grounding accident in multi-hazard coupling scenarios and provide technical support for occupational health and safety management of power transmission lines. |
format | Online Article Text |
id | pubmed-7142559 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-71425592020-04-15 Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines Zhang, Jun Bian, Haifeng Zhao, Huanhuan Wang, Xuexue Zhang, Linlin Bai, Yiping Int J Environ Res Public Health Article With the increasing demand for electricity transmission and distribution, single-phase grounding accidents, which cause great economic losses and casualties, have occurred frequently. In this study, a Bayesian network (BN)-based risk assessment model for representing single-phase grounding accidents is proposed to examine accident evolution from causes to potential consequences. The Bayesian network of single-phase grounding accidents includes 21 nodes that take into account the influential factors of environment, management, equipment and human error. The Bow-tie method was employed to build the accident evolution path and then converted to a BN. The BN conditional probability tables are determined with reference to historical accident data and expert opinion obtained by the Delphi method. The probability of a single-phase grounding accident and its potential consequences in normal conditions and three typical accident scenarios are analyzed. We found that “Storm” is the most critical hazard of single-phase grounding, followed by “Aging” and “Icing”. This study could quantitatively evaluate the single-phase grounding accident in multi-hazard coupling scenarios and provide technical support for occupational health and safety management of power transmission lines. MDPI 2020-03-12 2020-03 /pmc/articles/PMC7142559/ /pubmed/32178361 http://dx.doi.org/10.3390/ijerph17061841 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Jun Bian, Haifeng Zhao, Huanhuan Wang, Xuexue Zhang, Linlin Bai, Yiping Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines |
title | Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines |
title_full | Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines |
title_fullStr | Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines |
title_full_unstemmed | Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines |
title_short | Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines |
title_sort | bayesian network-based risk assessment of single-phase grounding accidents of power transmission lines |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7142559/ https://www.ncbi.nlm.nih.gov/pubmed/32178361 http://dx.doi.org/10.3390/ijerph17061841 |
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