Research on causes of coal mine gas explosion accidents based on association rule

被引:15
|
作者
Li, Li [1 ]
Guo, Huimin [1 ]
Cheng, Lianhua [1 ]
Li, Shugang [1 ]
Lin, Haifei [1 ]
机构
[1] Xian Univ Sci & Technol, Coll Safety Sci & Engn, Xian 710054, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Gas explosion; Data mining; Association rules; Carma algorithm; RISK-ASSESSMENT;
D O I
10.1016/j.jlp.2022.104879
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Statistical analysis of accidents is an important part of safety management and accident prevention. In this study, the case information of gas explosion accidents was analysed to deeply explore the accident characteristics. A total of 125 coal mine gas explosion accident reports in China from 2010 to 2020 were considered as the original data, and 30 causal factors of gas explosion accidents were extracted from the macro, meso, and micro levels. The Carma algorithm was used to mine the frequent itemsets of the sample data. The potential regular characteristics of gas explosion accidents were further explored by determining the association rules between the causal factors of the itemsets. The results show that the probability of gas explosion accidents caused by the violation of operating procedures, disordered ventilation systems, or illegal production organisations is high. Many strong association rules generated by human-management coupling were observed. The strong association rules of multi-factor coupling mainly include human-equipment-management coupling. This study provides new ideas for the prevention of gas explosion accidents.
引用
收藏
页数:7
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