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分析瓦斯爆炸事故的特点和原因:对中国煤矿事故的历史回顾。

Analysis of characteristics and causes of gas explosion accidents: a historical review of coal mine accidents in China.

机构信息

School of Emergency Management and Safety Engineering, China University of Mining and Technology (Beijing), China.

出版信息

Int J Occup Saf Ergon. 2024 Mar;30(1):168-184. doi: 10.1080/10803548.2023.2284015. Epub 2023 Dec 12.

Abstract

This study aimed to provide greater insight into the characteristics of severe and extraordinarily severe gas explosion accidents (SESGEAs). . The study analyzed the accident characteristics and causes of SESGEAs. As an example, we conducted a specialized case analysis using the 24Model (fourth edition) on the recent Baoma coal mine gas explosion. . SESGEA data are characterized by greater volatility, with significant differences in the geographical distribution, temporal distribution and attributed characteristics of the accidents. From the accident analysis: chaotic ventilation management was the most serious accident cause of SESGEAs; unsafe acts related to ventilation operations accounted for 18.51% of all unsafe acts; coal miners lack professional safety knowledge and have a serious fluke mentality in mining work; enterprises have insufficient enforcement of safety procedure documents, and lack of attention to the allocation of underground human resources and safety training systems; and the importance of safety, the role of the safety department and satisfaction with safety facilities have become the most serious missing items of safety culture. This study can provide important data support and management basis to assist mine operators in developing more targeted accident prevention strategies.

摘要

本研究旨在深入了解严重和极严重瓦斯爆炸事故(SESGEAs)的特点。研究分析了 SESGEAs 的事故特征和原因。以宝玛煤矿瓦斯爆炸事故为例,采用 24 模型(第四版)进行了专门的案例分析。SESGEA 数据的特点是波动性更大,事故在地理分布、时间分布和归因特征上存在显著差异。从事故分析来看:通风管理混乱是 SESGEAs 最严重的事故原因;与通风作业有关的不安全行为占所有不安全行为的 18.51%;矿工在采矿工作中缺乏专业安全知识,存在严重的侥幸心理;企业在安全程序文件的执行、对地下人力资源的重视和安全培训制度的分配方面存在不足;安全意识、安全部门的作用和对安全设施的满意度已成为安全文化最严重的缺失项目。本研究可为煤矿经营者制定更有针对性的事故预防策略提供重要的数据支持和管理依据。

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