煤矿事故不安全动作原因识别及作用研究  

Causes Identification and Influence of Unsafe Acts in Coal Mine Accidents

作　　者：付净 傅贵[2] 聂方超 刘虹 王泽恒 FU Jing;FU Gui;NIE Fangchao;LIU Hong;WANG Zeheng(College of Resources and Environmental Engineering,Jilin Institute of Chemical Technology,Jilin 132022,China;College of Resource and Safety Engineering,China University of Mining and Technology(Beijing),Beijing 100083,China)

机构地区：[1]吉林化工学院资源与环境工程学院,吉林吉林132022 [2]中国矿业大学(北京)资源与安全工程学院,北京100083

出　　处：《煤矿安全》2020年第1期242-245,共4页Safety in Coal Mines

基　　金：国家自然科学基金重点资助项目(51534008);吉林市科技发展计划资助项目(201831715)

摘　　要：为了有效减少由不安全动作引发的煤矿事故,基于FTA和24 Model,构建不安全动作识别及作用分析模型;通过实证研究,具体化6步骤应用过程,共识别出不安全动作致因因素22项,涉及30条作用路径。结果表明:FTA识别程序可有效展示各致因要素间逻辑关系,UA-UA及UA-UC共涉及20条路径,关联性较强;Gephi0.9.2分类特征可视化突出显示动作分类、人员类别及具体违章条目之间的关联性,违章操作占违章动作总数54.6%,共违反法规条款25项。To effectively reduce coal mine accidents caused by unsafe acts, it is necessary to construct the identification and role analysis model based on FTA and 24 Model. Through empirical research, the 6-step application process was concretized and 22 causes of unsafe actions were identified, involving 30 action paths. The results show that the FTA identification program can effectively display the logical relationship among various factors, and UA-UA and UA-UC involve a total of 20 paths, with a strong correlation. Gephi 0.9.2 classification features visualization highlights the correlation between the classification of actions,categories of personnel and specific violations, with violations accounting for 54.6% of the total number of violations, a total of 25 articles of the regulations.

关 键 词：煤矿事故 不安全动作 24 Model 作用路径 违章操作 

分 类 号：TD791[矿业工程—矿井通风与安全]