China Safety Science Journal ›› 2025, Vol. 35 ›› Issue (2): 127-136.doi: 10.16265/j.cnki.issn1003-3033.2025.02.0963

• Safety engineering technology • Previous Articles     Next Articles

Research review and progress of coal mine gas explosion risk assessment

LI Min1,2(), WANG Dan1, HE Shan1, SHI Shiliang1, WANG Deming2, LU Yi1   

  1. 1 School of Resource, Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan Hunan 411201, China
    2 State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Xuzhou Jiangsu 221116, China
  • Received:2024-09-20 Revised:2024-11-24 Online:2025-02-28 Published:2025-08-28

Abstract:

Gas explosion disaster is the most serious coal mine accidents. In order to summarize the research progress of gas explosion risk assessment, firstly, the risk factors of gas explosion were identified. Then the shortcomings of existing risk assessment methods were analyzed, and the following conclusions were drawn by sorting out relevant literature. The analysis shows that there are subjective problems in identification method and evaluation method of coal mine gas explosion risk sources. There are also some problems with risk factors, such as the uncertainty of gas source and change, the unknown ignition source, the uncertainty of ventilation and air control. The application of objective weighting method and evaluation method based on mathematical theory can improve the accuracy of weighting and evaluation results, but the computational complexity limits its wide application. Although the application of computer models has made the assessment of coal mine gas explosion risk more accurate, it is necessary to solve the problem of expanding the integration of data collection and deep learning. Based on the current research status and existing problems, the future risk assessment of coal mine gas explosion can develop in the direction of multi-source data fusion technology, deeply mining precursory warning information, establishing intelligent models of disaster information based on information depth perception and data mining, and realizing dynamic risk assessment of coal mine gas explosion.

Key words: coal mine gas explosion, risk assessment, uncertainty, risk indicators, ignition sources

CLC Number: