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基于SNA的露天矿爆破安全风险评估 被引量:5

Safety risk assessment of blasting in open-pit mine based on SNA
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摘要 为减少露天矿爆破安全事故带来的人员伤亡和事故损失,采用社会网络分析法(SNA),构建露天矿爆破安全风险因素关系网络模型(A型模网)和安全风险因素与安全事故之间的关系网络模型(B型模网),研究风险因素之间以及爆破事故与风险因素的关联关系,提出基于SNA的露天矿爆破安全风险评估模型。确定爆破技术指导和检查不到位、安全意识薄弱、违规操作等因素是影响露天矿爆破安全的核心风险因素,重点管控的关键关系为天气恶劣→违规操作等;风险管控后模网的整体网络密度和中间中心势分别下降75%和100%。研究表明:通过靶向干预核心风险因素并切断关键关系,可有效管控风险。 In order to reduce casualties and accident losses caused by blasting safety accidents in open-pit mines,SNA was used to construct the relationship network model of blasting safety risk factors in open-pit mines(A model network)and the relationship network model between safety risk factors and safety accidents(B model network).The relationship between risk factors and blasting accidents and risk factors was studied,and the risk assessment model of open-pit blasting safety based on SNA was proposed.It is determined that the core risk factors affecting the blasting safety of open-pit mines were inadequate guidance and inspection of blasting technology,weak safety awareness and illegal operation.And the key relationship of key control is from bad weather to illegal operation.After risk control,the overall network density and intermediate center potential of the network decreased by 75%and 100%,respectively.Researches has shown that risk can be effectively controlled through targeted intervention of core risk factors and cutting off key relationships.
作者 柯丽华 陈魁香 胡南燕 谭铭 张光权 孟欢欢 KE Lihua;CHEN Kuixiang;HU Nanyan;TAN Ming;ZHANG Guangquan;MENG Huanhuan(School of Resource and Environmental Engineering,Wuhan University of Science and Technology,Wuhan Hubei 430081,China;Industrial Safety Engineering Technology Research Center of Hubei Province,Wuhan Hubei 430081,China;Wulongquan Mining Co.,Ltd,WISCO Resources Group,Wuhan Hubei 430213,China)
出处 《中国安全科学学报》 CAS CSCD 北大核心 2022年第10期48-56,共9页 China Safety Science Journal
基金 湖北省重点研发计划项目(2020BCA082)。
关键词 露天矿 爆破安全事故 社会网络分析法(SNA) 安全风险评估 关系网络模型 open-pit mine blasting safety accident social network analysis(SNA) safety risk assessment relationship network model
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