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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...

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Autores principales: Zhang, Jun, Bian, Haifeng, Zhao, Huanhuan, Wang, Xuexue, Zhang, Linlin, Bai, Yiping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
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.
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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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