State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University
School of Resources and Safety Engineering, Chongqing University

为充分汲取煤与瓦斯突出历史事故经验,发挥事故调查报告中专家意见的价值,构建了一种基于案例推理的CBR突出预警模型,并依据历史案例数据库搭建了突出预警系统。以突出的多类别指标数据作为输入,运用K最近邻算法计算当前案例与历史案例的局部相似度。同时,为进一步提高案例检索准确度,采用灰狼优化(GWO)算法优化各指标的特征权重,计算得到全局相似度。通过当前案例与历史案例的相似匹配,对突出危险进行预警,并提出突出防治决策方案。利用河南鹤煤六矿突出事故进行验证,结果表明所搭建的预警系统可实现突出危险的有效预警与决策。

In order to fully learn the experience of coal and gas outburst historical accidents and give full play to the value of expert opinions in accident investigation reports, an CBR outburst early warning model based on case-based reasoning was proposed, and an outburst early warning system was built based on historical case database. With the multi-category index data of outburst as input, the K-nearest neighbor algorithm was used to calculate the local similarity between the current instance and the past instance. At the same time, in order to further improve the accuracy of case retrieval, the grey wolf optimization (GWO) algorithm was used to optimize the feature weight of each index, and the global similarity was calculated. By conducting similarity matching between the current instance and the past instance, the outburst risk was early warned, and the prevention and control decision scheme of outburst was put forward. Using the outburst accident in Hemei No. 6 Mine in Henan Province to verify, the results show that the established early warning system can realize effective early warning and decision-making of outburst danger.

国家重点研发计划项目(2022YFC3004704)

李全贵,李建波,胡千庭,等. 基于案例推理的煤与瓦斯突出预警模型研究[J]. 矿业安全与环保,2023,50(5):24-29.

LI Quangui,LI Jianbo,HU Qianting,et al. Research on early warning model of coal and gas outburst based on case-based reasoning[J]. Mining Safety & Environmental Protection,2023,50(5):24-29.