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Title
Scenario deduction of gas explosion accidents in coal minefire areas based on Bayesian network
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作者
兰泽全李玉麟旷永华张丽娜张明
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Author
LAN Zequan;LI Yulin;KUANG Yonghua;ZHANG Lina;ZHANG Ming
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单位
华北科技学院矿山安全学院
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Organization
School of Mine Safety,North China Institute of Science and Technology
Guizhou Panjiang Cleaned Coal Co.,Ltd.
Inner Mongolia Beilian Energy Development Co.,Ltd.
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摘要
为防止煤矿火区瓦斯爆炸事故造成严重的人员伤亡和财产损失,利用知识元、情景构建及推演理论,研究煤矿火区瓦斯爆炸事故的演变过程。以2014年7月某矿瓦斯爆炸事故为例,从情景状态、应急目标、处置措施、孕灾环境四个维度出发,构建基于动态贝叶斯网络预测模型的煤矿火区瓦斯爆炸事故情景网络,计算事故情景发生概率,分析其演变规律。结果表明,煤矿火区瓦斯爆炸事故推演结果与实际发展情景基本吻合,验证了该预测模型的合理性。研究成果可为火区瓦斯爆炸事故风险的防范、应急预案的完善、应急决策等提供技术支持。
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Abstract
In order to prevent serious casualties and property losses caused by gas explosion accidents in coalmine fire areas,the evolution process of gas explosion accidents in coal mine fire areas is studied by usingknowledge elements, scenario construction, and deduction theory.Taking the gas explosion accident in acertain mine in July 2014 as an example,a coal mine fire area gas explosion accident scenario network basedon dynamic Bayesian network prediction model is constructed from four dimensions:scenario state,emergencyobjectives,disposal measures,and disaster environment.The probability of accident scenario occurrence is calculated,and its evolution law is analyzed.The results indicate that the inferred results of gas explosion accidents in coal mine fire areas are basically consistent with the actual development scenario,verifying the ration61ality of the prediction model.The research results can provide technical support for the prevention of gas explosion accident risk in fire areas,the improvement and improvement of emergency plans,and emergency decision-making.
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关键词
情景推演瓦斯爆炸贝叶斯网络知识元
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KeyWords
scenario deduction; gas explosion;Bayesian network; knowledge element
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DOI
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引用格式
兰泽全,李玉麟,旷永华,等 .基于贝叶斯网络的煤矿火区瓦斯爆炸事故情景推演[J].华北科技学院学报,2023,20(6):16-22
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Citation
LAN Zequan,LI Yulin,KUANG Yonghua,et al.Scenario deduction of gas explosion accidents in coal minefire areas based on Bayesian network[J].Journal of North China Institute of Science and Technology,2023,20(6):16-22
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