基于ISM-BN的煤矿瓦斯爆炸风险评判方法及其应用
Risk evaluation method of coal mine gas explosion based on ISM-BN and its application
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摘要: 为有效评估煤矿瓦斯爆炸风险，提出了一种基于解释结构模型（ISM）和贝叶斯网络（BN）的瓦斯爆炸风险评估方法；首先利用扎根理论对65起典型瓦斯爆炸事故案例进行3级编码，提取出13个瓦斯爆炸风险致因因素；其次通过解释结构模型建立贝叶斯网络结构，引入云模型计算贝叶斯网络节点的先验概率和条件概率，并将概率值导入GeNie软件中进行贝叶斯网络参数学习，对煤矿瓦斯爆炸发生可能性进行评价；最后对贝叶斯网络模型进行敏感性分析和诊断推理，分析诱发煤矿瓦斯爆炸的关键致因因素，并提出相应对策措施。以山西某矿为例进行评价方法应用，结果表明：除瓦斯超限和产生点火源2个瓦斯爆炸必要条件之外，煤尘爆炸、通风系统缺陷、瓦斯涌出、机电设备火花、煤自燃、设备失爆、违规爆破等因素是煤矿瓦斯爆炸的关键致因因素，且导致这些关键致因因素发生的深层原因是管理层因素，评价结果与实际情况相符。Abstract: In order to effectively assess the risk of gas explosion in coal mines, a gas explosion risk assessment method based on ISM-BN is proposed. Firstly, 65 typical gas explosion accident cases were coded at level 3 using grounded theory, and 13 risk factors of gas explosion were extracted; secondly, the Bayesian Network structure is established by interpreting the structure model, and the cloud model is introduced to calculate the prior probability and conditional probability of Bayesian Network nodes, and the probability value is imported into GeNie software for Bayesian Network parameter learning to evaluate the possibility of coal mine gas explosion; finally, the sensitivity analysis and diagnostic reasoning of Bayesian Network model are carried out to analyze the key causative factors of coal mine gas explosion, and put forward corresponding countermeasures. Taking a mine in Shanxi Province as an example to apply the evaluation method, the results show that, in addition to the two necessary conditions of gas explosion, gas overrun and ignition source, coal dust explosion, ventilation system defects, gas emission, electromechanical equipment sparks, coal spontaneous combustion, equipment explosion loss, illegal blasting and other factors are the key factors causing coal mine gas explosion. The underlying reasons for these key causative factors are management factors, and the evaluation results are consistent with the actual situation.
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[1] Tong R, Yang Y, Ma X, et al. Risk assessment of miners’ unsafe behaviors: A case study of gas explosion accidents in coal mine, China[J]. International Journal of Environmental Research and Public Health, 2019, 16（10）: 1765. [2] 谷新保，任寰，王毅恒.基于AHP-云模型在煤矿瓦斯爆炸危险性评价中的应用[J].南阳理工学院学报，2021，13（6）：20-24. GU Xinbao, REN Huang, WANG Yiheng, et al. The application of risk assessment about the gas explosion of coal mines based on AHP cloud model[J]. Journal of Nanyang Institute of Technology, 2021, 13（6）: 20-24.
[3] 鲁锦涛，任利成，戎丹，等.基于灰色-物元模型的煤矿瓦斯爆炸风险评估[J].中国安全科学学报，2021，31（2）：99-105. LU Jintao, REN Licheng, RONG Dan, et al. Assessment of coal mine gas explosion risk based on grey-matter element model[J]. China Safety Science Journal, 2021, 31（2）: 99-105.
[4] 汪圣伟，李希建，代芳瑞，等.基于改进AHP-SPA的煤矿瓦斯爆炸风险评价[J].矿业研究与开发，2021，41（4）：113-117. WANG Shengwei, LI Xijian, DAI Fangrui, et al. Risk assessment of gas explosion based on improved AHP-SPA[J]. Mining Research and Development, 2021, 41（4）: 113-117.
[5] 李爽，李丁炜，犹梦洁，等.基于BN-ELM的煤矿瓦斯安全态势预测方法[J].系统工程，2020，38（3）：132. LI Shuang, LI Dingwei, YOU Mengjie, et al. Coal mine gas security situation forecasting method based on BN-ELM[J]. Systems Engineering, 2020, 38（3）: 132.
[6] Li M, Wang H, Wang D, et al. Risk assessment of gas explosion in coal mines based on fuzzy AHP and bayesian network[J]. Process Safety and Environmental Protection, 2020, 135: 207-218. [7] 张津嘉，许开立，王贝贝，等.特别重大煤矿瓦斯爆炸事故致因分析及管理模式研究[J].中国安全科学学报，2016，26（2）：73-78. ZHANG Jinjia, XU Kaili, WANG Beibei, et al. Extraordinarily serious gas explosion accidents in coal mines: analysis of causes and research on management mode[J]. China Safety Science Journal, 2016, 26（2）: 73-78.
[8] Strauss A L. Qualitative analysis for social scientists[M]. London: Cambridge University Press, 1987: 5. [9] 陈向明.扎根理论的思路和方法[J].教育研究与实验，1999（4）：58-63. CHEN Xiangming. Grounded theory: its train of thought and methods[J]. Educational Research and Experiment, 1999（4）: 58-63.
[10] Suddaby R. From the editors: What grounded theory is not[J]. Academy of management journal, 2006, 49（4）: 633-642. [11] 杨爱武，李战武，徐安，等.基于加权动态云贝叶斯网络空战目标威胁评估[J].飞行力学，2020，38（4）：87. YANG Aiwu, LI Zhanwu, XU An, et al. Threat level assessment of the air combat target based on weighted cloud dynamic Bayesian network[J]. Flight Dynamics, 2020, 38（4）: 87.
[12] 熊钰，孔德中，杨胜利，等.大倾角工作面煤壁稳定性的云模型综合辨识[J].中国安全科学学报，2022，32（3）：144-151. XIONG Yu, KONG Dezhong, YANG Shengli. et al, Cloud model identification of coal face stability in steeply inclined working faces[J]. China Safety Science Journal, 2022, 32（3）: 144-151.
[13] 杨三军，朱新菲，谭波.基于云模型的矿山应急救援队伍能力评估标准研究[J].煤矿安全，2021，52（11）：250-255. YANG Sanjun, ZHU Xinfei, TAN Bo. Evaluation standard of mine emergency rescue force capability based on cloud model[J]. Safety in Coal Mines, 2021, 52（11）: 250-255.
[14] Gao P, Li W, Sun Y, et al. Risk assessment for gas transmission station based on cloud model based multilevel Bayesian network from the perspective of multi-flow intersecting theory[J]. Process Safety and Environmental Protection, 2022, 159: 887-898. [15] Zou X, Yue W L. A bayesian network approach to causation analysis of road accidents using netica[J]. Journal of Advanced Transportation, 2017, 2017: 2525481. [16] Castillo E, Gutiérrez J M, Hadi A S. Sensitivity analysis in discrete Bayesian networks[J]. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 1997, 27（4）: 412-423.
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