基于关联规则的煤矿机电运输事故不安全行为分析

为系统分析矿工在机电运输过程中产生不安全行为的关联因素,降低事故发生概率,本文从煤矿安全生产网和应急管理部公布的煤矿事故案例中选取2015-2021年发生的90起机电运输事故作为案例样本,统计分析煤矿机电运输中不安全行为在动作分类、班次、月份、地点和岗位5个维度的分布特征;运用Apriori算法研究煤矿机电运输事故这5个维度之间存在的关联规则。研究表明:在3个班次中,中班时间段出现的不安全行为比率最高;在一年中8月份出现的不安全行为最多;处于工作面中的不安全行为出现最多;一线工人的不安全行为出现最多。重点防治一线工人在中班发生的不安全行为和晚班时冒险作业这一行为,有利于加强工作面的巡检力度,提高检查效率。

Analysis on Unsafe Behavior in Electromechanical Transportation of Coal Mine Based on Related Rules

In order to systematically analyze the related factor of the miner's unsafe behavior in electromechanical transportation and reduce the probability of the accident,in this paper,90 electromechanical transport accidents from 2015-2021 were selected as case examples from the accident cases published by www.mkaq.com and Ministry of Emergency Management of the People's Republic of China.The distribution characteristics of the unsafe behavior in electromechanical transportation of coal mine were counted from the five dimensions of action classification,shift,month,place and post.The Apriori algorithm was used to study related rules among the above five dimensions.The research shows that the highest rate of unsafe behaviors occurs in the middle shift time of three shifts;that the highest number of unsafe behaviors occurs in August of the year;that most of the unsafe behaviors occurs in the work face and front-line workers.Focusing on the first-line worker's unsafe behaviors in the middle shift and risky operation in the night shift is useful to strengthen the inspection of the work face and improve the inspection efficiency.