LI Shihui, SHEN Tao, QIN Ruxiang, et al. Classification analysis and quantitative efficacy evaluation of coal mine accident prevention measuresJ. Safety in Coal Mines, 2026, 57(1): 247−256. DOI: 10.13347/j.cnki.mkaq.20241712
    Citation: LI Shihui, SHEN Tao, QIN Ruxiang, et al. Classification analysis and quantitative efficacy evaluation of coal mine accident prevention measuresJ. Safety in Coal Mines, 2026, 57(1): 247−256. DOI: 10.13347/j.cnki.mkaq.20241712

    Classification analysis and quantitative efficacy evaluation of coal mine accident prevention measures

    • Coal mine accident prevention measures are of extremely crucial significance for safeguarding the lives of miners and ensuring the stable operation of coal mines. Assessing the efficacy of these measures is a core component in optimizing accident prevention strategies and enhancing prevention capabilities. However, current accident prevention measures lack systematic means for efficacy validation, making it difficult to precisely quantify their actual impact. This study focuses on this issue, conducting a comprehensive analysis of accident prevention measures and developing a quantitative model for efficacy assessment from a resource perspective. The study thoroughly reviewed the research, practice, and evaluation status of coal mine accident prevention measures, categorizing them into six types: technical, managerial, regulatory and policy, economic incentive, social participation, and emergency response measures. The differences in resource utilization among these types were carefully analyzed. Based on this analysis, a quantitative model for assessing the effectiveness of coal mine accident prevention measures was developed, incorporating four indicators: types of resource allocation, allocation ratios, effectiveness duration, and utilization capabilities. Taking Pan’er Mine of Huainan Mining Group as a case study, the efficacy value of its accident prevention measures was calculated using a combination of expert ratings, questionnaires, and on-site data. A refined resource allocation plan was then proposed as the output of the model, dividing resources into eight categories: human, technical, financial, material, physical, informational, managerial, and emergency resources. The efficacy of the optimized plan was re-evaluated. By comparing the results before and after optimization, suggestions for improving accident prevention measures were put forward. Additionally, the data validity of eight key indicators within the model was examined to verify the accuracy and rationality of the model results. The study results indicate that the efficacy value increased from 1.235 5 before optimization to 1.300 4 after optimization. The quantitative model can effectively assess the efficacy level of coal mine accident prevention measures and provide an optimization direction for resource allocation plans.
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