房柱法采场结构参数优化研究  

Study on Optimization of Stope Structure Parameters with Room-pillar Method

作　　者：贾敬锎 甄利兵 蔡泳 JIA Jingkai;ZHEN Libing;CAI Yong(School of Resources and Safety Engineering,Chongqing University,Chongqing 400044,China;State Key Laboratory of Coal Mine Disaster Dynamics and Control,Chongqing University,Chongqing 400044,China)

机构地区：[1]重庆大学资源与安全学院,重庆400044 [2]重庆大学煤矿灾害动力学与控制国家重点实验室,重庆400044

出　　处：《矿业研究与开发》2021年第11期5-9,共5页Mining Research and Development

摘　　要：为解决某钨矿深部采空区稳定性差的问题,基于数值模拟、熵权法、BP神经网络和混沌优化算法,对深部采场结构参数进行综合研究,提出了一种采场结构参数优化的方法。研究结果表明:合理的采场结构参数是保证采空区稳定性的关键;采用此方法获得了采场结构的最佳参数:边缘矿柱宽度为4.8 m,采场内点柱宽度为7.8 m,矿房宽度为17 m,矿柱个数为9个。矿山应用后,获得的实际回采率为79%左右,为采场优化结构参数设计提供了一种新的思路。In order to solve the problem of poor stability of deep goaf in a tungsten mine,based on numerical simulation,entropy weight method,BP neural network and chaos optimization algorithm,the structure parameters of deep stope were comprehensively studied,and a optimization method of stope structure parameters was put forward.The research results show that reasonable stope structure parameters are the key to ensure the stability of the goaf.The best parameters of stope structure are obtained by this method:the width of the marginal pillar is 4.8 m,the width of the point pillar in the stope is 7.8 m,the width of the mine room is 17 m,and the number of pillars is 9.After the application in this mine,the obtained actual recovery rate is about 79%,which provides a new idea for the optimization of the structure parameter design of the stope.

关 键 词：房柱法 采场结构 数值模拟 熵权法 BP神经网络 混沌优化算法 

分 类 号：TD853[矿业工程—金属矿开采]