Causative association analysis of coal mine roof accidents based on SIF model and Apriori algorithm
LI Yan;CHEN Tao;KANG Yufeng
为更科学地预防煤矿顶板事故的发生,对煤矿顶板事故致因及其关联规则进行识别十分关键。首先,通过文本挖掘并结合SIF事故致因模型,确定56个影响顶板事故发生的致因;其次,通过构建顶板事故数据库并运用Apriori算法进行顶板事故致因关联规则挖掘;最后,绘制顶板事故致因关联规则复杂网络图,并综合分析顶板事故的核心致因及各致因间的关联规则。结果表明:安全培训教育和安全监督管理、作业人员安全意识淡薄和违反作业规程、当班管理人员在现场的管理不到位和其他事故致因之间有着很高的关联度以及提升度,这些因素是造成煤矿顶板事故发生的核心因素。
In order to prevent the occurrence of coal mine roof accidents more scientifically, it is crucial to identify the causal factors of coal mine roof accidents and their association rules. First, 56 causal factors affecting the occurrence of roof accidents were identified through text mining and combined with the SIF accident causal model. Second, we constructed a roof accident database and utilized the Apriori algorithm to mine the association rules of roof accidents. Finally, the complex network diagram of the causal factors of roof accidents was drawn, and the core causal factors of roof accidents and the correlation rules between the causal factors were comprehensively analyzed. The results show that there is a high degree of correlation and enhancement between safety training and education, safety supervision and management, low safety awareness and violation of work procedures by operators, inadequate management of the on-duty management and other causes of accidents, and these factors are the core factors causing roof accidents in coal mines.
roof accident;SIF model;association rules;complex network diagram;Apriori algorithm;accident cause
主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会