School of Resource, Environment and Safety Engineering, Hunan University of Science and Technology, Taoyuan Road, Xiangtan, 411201, Hunan Province, China.
Key Laboratory of Gas and Fire Control for Coal Mines, Ministry of Education, China University of Mining and Technology, Xuzhou, 221116, China.
Environ Sci Pollut Res Int. 2024 Sep;31(43):55475-55489. doi: 10.1007/s11356-024-34890-7. Epub 2024 Sep 4.
Large-scale coal mine gas explosion (CMGE) accidents have occurred occasionally and exerted a devastating effect on society. Therefore, it is essential to systematically identify the characteristics and association rules of causes of CMGE accidents through analysis on large-scale CMGE accident reports. In this study, 298 large-scale CMGE accidents in China from 2000 to 2021 were taken as the data sample, and mathematical statistical methods were adopted to analyze their general characteristics, coupling cross characteristics, and characteristics of gas accumulation and ignition sources. Moreover, the text mining technology and the Apriori algorithm were used for exploring the formation mechanism of CMGE accidents, during which 46 main causal factors were identified and 59 strong association rules were obtained. Furthermore, an accident causation network was constructed based on the co-occurrence matrix. The key causal items and sets of CMGE accidents were clarified through network centrality analysis. According to the research results, electrical equipment failure, cable short circuit, mine lamp misfire, hot-line work, and blasting spark are the key ignition sources of CMGE. Fan failure, airflow short circuit, and local ventilation fan damage are the main causes of gas accumulation. Besides, the confidence levels of two association rules of "static spark-fan failure" and "blasting spark-airflow short circuit" are higher than 70%, indicating that they are the two dominant risk-coupling paths of gas explosions. In addition, six causes appear frequently in the shortest risk paths of gas explosion and are closely related to other causes, i.e., fan failure, local ventilation fan damage, static sparks, electrical equipment failure, self-heating ignition, and friction impact sparks. This study provides a new perspective on identifying causes of accidents and their complex association mechanisms from accident report data for practical guidance in risk assessment and accident prevention.
大规模煤矿瓦斯爆炸(CMGE)事故时有发生,对社会造成了毁灭性的影响。因此,通过对大规模 CMGE 事故报告进行分析,系统地识别 CMGE 事故的原因特征和关联规则至关重要。本研究以 2000 年至 2021 年中国发生的 298 起大规模 CMGE 事故为数据样本,采用数理统计方法分析其总体特征、耦合交叉特征和瓦斯积聚及点火源特征。同时,运用文本挖掘技术和 Apriori 算法,挖掘 CMGE 事故的形成机理,共识别出 46 个主要致因项,得到 59 条强关联规则,并基于共现矩阵构建了事故致因网络,通过网络中心性分析明确了 CMGE 事故的关键致因项和集。根据研究结果,电气设备故障、电缆短路、矿灯失爆、带电作业、爆破火花是 CMGE 的关键点火源;风机故障、风流短路、局部通风机损坏是瓦斯积聚的主要原因。此外,“静电火花-风机故障”和“爆破火花-风流短路”这两条关联规则的置信度均高于 70%,表明它们是瓦斯爆炸的两个主要风险耦合路径。同时,在最短的瓦斯爆炸风险路径中,有六个原因频繁出现,与其他原因密切相关,即风机故障、局部通风机损坏、静电火花、电气设备故障、自热点火和摩擦冲击火花。本研究为从事故报告数据中识别事故原因及其复杂关联机制提供了新视角,为风险评估和事故预防提供了实用指导。