摘要
立足于现有的岩爆预测研究现状,充分考虑到岩爆的众多影响因素如岩性、能量等,选择了σ_(θ)、σ_(c)、σ_(t)、σ_(θ)/σ_(c)、σ_(c)/σ_(t)、Wet这六个指标作为岩爆倾向性评价指标。基于所收集的岩爆数据,运用箱线图法进行数据清洗,得到567组岩爆数据。利用云模型这一数学方法对其进行分级预测评价,同时基于组合赋权法优化各个评价指标的权重分配,最终评价准确率能达到82%,相比于用其他权重法的云模型评价准确率更高。基于实际工程背景,运用组合赋权—多维正态云模型对深井矿山岩爆倾向性进行综合评价,得到了某深井矿山深部岩体的岩爆倾向性,相比于其他单一指标的岩爆判据要更为准确且符合实际。
Built upon the current state of rockburst prediction research and fully considers the numerous influencing factors of rockbursts,such as lithology and energy.Six indicators—σ_(θ),σ_(c),σ_(t),σ_(θ)/σ_(c),σ_(c)/σ_(t),and Wet—were selected as evaluation criteria for rockburst tendency.Based on collected rockburst data,the box plot method was employed for data cleansing,resulting in 567 sets of valid data.A cloud model was then used for graded prediction and evaluation.At the same time,the combined weighting method was applied to optimize the weight distribution of each evaluation indicator.The final evaluation accuracy reached 82%,which is higher than that of cloud models using other weighting methods.Based on a real engineering context,the combined weighting-multidimensional normal cloud model was used to comprehensively evaluate the rockburst tendency of deep mines.The evaluation of the deep rock mass in the deep mine proves to be more accurate and realistic compared to traditional single-indicator rockburst criteria.
作者
李奇
王雷
李建壮
徐柳
王堃
LI Qi;WANG Lei;LI Jianzhuang;XU Liu;WANG Kun(Anhui Lujiang Longqiao Mining Co.,Ltd.,Hefei 231551,China;Tongkeng Mining Branch of Guangxi Huaxi Mining Co.,Ltd.,Nandan 547205,China;Jiaojia Gold Mine,Shandong Gold Mining(Laizhou)Co.,Ltd.,Laizhou 261441,China;School of Resources and Safety Engi neering,University of Science and Technology Beijing,Beijing 100083,China;BGRIMM Technology Group,Beijing 100160,China)
出处
《有色金属(中英文)》
北大核心
2025年第8期1386-1395,共10页
Nonferrous Metals
基金
地球深部探测与矿产资源勘查国家科技重大专项资助(2024ZD1003702)。
关键词
多维正态云模型
岩爆倾向性
弹性应变能
组合权重法
multidimensional normal cloud model
rockburst tendency
elastic strain energy
combined weighting method
