基于贝叶斯网络的煤矿顶板事故致因研究

Study on causes of coal mine roof accidents based on Bayesian network

为研究煤矿顶板事故致因及预防煤矿顶板事故的发生,基于顶板事故调查报告,从人为、设备、环境、管理4个方面选取导致煤矿顶板事故致因变量,通过变量间的相关关系,利用贝叶斯网络软件GeNie构建煤矿顶板事故致因分析的贝叶斯网络模型(BN),采用交叉验证法检验贝叶斯网络模型的精准度,并对模型进行结构和参数学习,计算出各节点的条件概率分布和后验概率等,最后通过变量敏感性和事故最大致因链分析,找出事故发生的关键因素路径,有助于降低顶板事故的发生率。研究结果表明:在人为因素方面,未履行作业规程和监督检查不到位的比例较高,概率值均大于84%;在管理因素方面,安全管理混乱是导致顶板事故发生的主要诱因,概率值大于95%;顶板垮落、支护问题、是否进入垮落区是导致顶板事故发生的重要因素。

In order to study the causes of coal mine roof accident and prevent the occurrence of roof accident, based on the roof accident investigation report, the cause variables of coal mine roof accident were selected from four aspects of human, equipment, environment and management. Through the correlation among variables, Bayesian network software GeNie was used to build the Bayesian network model(BN) of the cause of coal mine roof accident, and the accuracy of Bayesian network model was tested by cross validation method, the structure and parameters of the model were studied, and the conditional probability distribution and posteriori probability of each node were calculated. Finally, the variable sensitivity and maximum cause chain analysis were explored to find out the path of key factors of accident, which was helpful to reduce the incidence of accident. The results show that in terms of human factors, the proportion of failing to fulfill the operation regulations and inadequate supervision and inspection is high, and the probability values are all greater than 84%;in terms of management factors, the confusion of safety management is the main inducement leading to accidents, and the probability value is greater than 95%;roof collapse, support problems, and whether to enter the caving area are the important factors leading to roof accidents.