金属矿山岩体质量评价方法进展与展望  

Advances and prospects for rock mass evaluation methods in metal mines

作　　者：王运森[1] 郑贵平[1] 李元辉[1] 吴钦正 WANG Yunsen;ZHENG Guiping;LI Yuanhui;WU Qinzheng(Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines,Northeastern University,Shenyang 110819,China;Deep Mining Laboratory of Shandong Gold Group Co.,Ltd.,Yantai 261442,China)

机构地区：[1]东北大学深部金属矿山安全开采教育部重点实验室,辽宁沈阳110819 [2]山东黄金集团有限公司深井开采实验室,山东烟台261442

出　　处：《中国矿业》2019年第8期149-153,共5页China Mining Magazine

基　　金：国家重点研发计划项目资助(编号:2017YFC0602905);中央高校基本科研业务费专项资金资助(编号:N150104007)

摘　　要：本文概述了岩体质量由定性单因素评价到定量多因素综合评价的发展历程,介绍了RMR和BQ两种矿山常用的传统岩体质量评价方法,总结了神经网络法、可拓理论法、模糊评价法与灰色聚类法等智能岩石力学评价方法在金属矿山的应用情况。通过研究现有的岩体质量分级方法在矿山的应用情况,分析其存在的不足,提出在未来金属矿山岩体质量评价中应先建立岩体力学数据库,借助综合信息管理平台,运用计算机技术进行快速、实时评价,并将评价结果进行可视化展示。同时,应根据深部开采的特点,建立适用于深部环境的岩体质量评价方法。This paper summarizes the development of evaluation for rock mass from qualitative to quantity,from single to multi factors,and introduces the traditional rock mass evaluation methods of RMR and BQ.some intelligent rock evaluation methods in metal mine such as neural network,extenics theory,fuzzy evaluation and gray clustering are summarized.By studying the application of the existing rock mass grading methods in mines,the paper analyzes the shortcomings of the current methods,and puts forward that the rock mechanics database should be set up in the future rock evaluation,with the comprehensive information management platform and technology to do rapid and real-time evaluation,and visualize the evaluation results.At the same time,the mine builds rock mass evaluation methods for the deep environment according to the characteristics of deep mining.

关 键 词：岩体质量评价方法 金属矿山 岩体质量分级 深部开采 

分 类 号：TD88[矿业工程—矿山开采]