A DEMATEL-ISM-BN Model of Mine Water Inrush Accidents
A DEMATEL-ISM-BN Model of Mine Water Inrush Accidents
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DOI：
10.1007/s10230-022-00907-1
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发表时间：
2023-02
影响因子：
2.8
通讯作者：
Weibin Hong;Wu Sheng
中科院分区：
文献类型：
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作者：
Weibin Hong;Wu Sheng
通过深入了解矿井大规模突水事故的原因及各因素之间的内在联系，可以减少大规模突水事故的发生次数和严重程度。基于2010年至2020年的70起重大事件，我们利用DEMATEL和ISM技术构建了多层次的分层结构模型，然后将模型映射到BN网络，利用后验概率计算实现反向诊断推理识别。结果表明，对水灾害认识不足和水文地质探测不充分是影响灾害发生的关键因素，后验概率分别为91%和82%，最高中心度分别为5.400和4.917。安全管理混乱和监管不到位是造成事故的根本原因，其因果度分别为1.402和2.038。模型的因果结构和最大因果链分析表明，这些因素很可能是大多数突水事故的原因。关注这些基本因素，可以更有效地控制事故，减少损失。
Large-scale mine water inrush accidents can be reduced in number and severity by better understanding the causes of these accidents and the internal relationships between the various causal factors. Based on 70 major events from 2010 to 2020, we constructed a multi-level hierarchical structural model using DEMATEL and ISM techniques, and then mapped the model to a BN network, using posterior probability computation to enable reverse diagnosis reasoning recognition. The results indicated that inadequate knowledge of water disasters and inadequate hydrogeological detection are the key factors, with posterior probabilities of 91 and 82%, and the highest centre degrees of 5.400 and 4.917. The fundamental contributing factors are disordered safety management and imperfect supervision, with causal degrees of 1.402 and 2.038. It is clear from the model’s causal structure and maximum causal chain analysis that these factors are quite likely the cause of most water inrush accidents. Paying closer attention to these fundamental factors can help to more effectively control these accidents and minimize losses.