@article{ref1,
title="Bayesian network-based risk assessment of single-phase grounding accidents of power transmission lines",
journal="International journal of environmental research and public health",
year="2020",
author="Zhang, Jun and Bian, Haifeng and Zhao, Huanhuan and Wang, Xuexue and Zhang, Linlin and Bai, Yiping",
volume="17",
number="6",
pages="e1841-e1841",
abstract="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 &quot;Storm&quot; is the most critical hazard of single-phase grounding, followed by &quot;Aging&quot; and &quot;Icing&quot;. 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.<p /> <p>Language: en</p>",
language="en",
issn="1661-7827",
doi="10.3390/ijerph17061841",
url="http://dx.doi.org/10.3390/ijerph17061841"
}