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某钨矿急倾斜薄矿体采矿方法优选
引用本文:吴礼军,韩晓亮,刘白璞.某钨矿急倾斜薄矿体采矿方法优选[J].金属矿山,2018,47(12):34-38.
作者姓名:吴礼军  韩晓亮  刘白璞
作者单位:1. 中国爆破行业协会,北京 100070;2. 浙江省高能爆破工程有限公司,浙江 杭州 310012;3. 江西理工大学资源与环境工程学院,江西 赣州 341000)
摘    要:为选择适合某钨矿急倾斜薄矿体的最佳采矿方法,以解决该矿开采难度大与开采成本高的问题,根据矿山实际地质情况并通过查阅资料,初选出了适用于急倾斜薄矿体的采矿方法。在此基础上,综合选择了影响采矿方法的9个因素,运用层次分析法确定了各因素的权重,各影响因素权重经过无量纲化处理后建立了隶属度矩阵和综合评价体系。通过综合比较分析,确定了该矿的最佳采矿方法为浅孔留矿法。该方法在矿山生产实践中,年产量提高了12万t,每年可节约成本近400万元,取得了显著的经济效益,可供类似矿山参考。

关 键 词:急倾斜薄矿体  层次分析法  浅孔留矿法  判断矩阵

Mining Method Optimization of Sharply-inclined Thin Orebody of a Tungsten Mine
Wu Lijun,Han Xiaoliang,Liu Baipu.Mining Method Optimization of Sharply-inclined Thin Orebody of a Tungsten Mine[J].Metal Mine,2018,47(12):34-38.
Authors:Wu Lijun  Han Xiaoliang  Liu Baipu
Affiliation:1. China Society of Engineering Blasting,Beijing,100070;2. Zhejiang Gaoneng Corporation of Blasting Engineering Co. Ltd.,Hangzhou 310012,China;3. School of Resources and Environmental Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China
Abstract:In order to select the optimal mining method and solve the problems of high mining difficulty and cost for sharply-inclined thin orebody of a tungsten mine,the preliminary mining method is determined based on the actual geological conditions and some related technical data of the mine.Through comprehensive consideration of determined 9 factors affecting mining method optimization,the index weight is determined by using analytic hierarchy process (AHP).The membership matrix and comprehensive evaluation system are established after the dimensionless treatment.The optimal mining method is determined as short-hole shrinkage method.The engineering practice results show that the annual output of the mine is increased by 120,000 t and the annual cost is saved by nearly 4 million yuan by using short-hole shrinkage method,the achieved remarkable economic benefits are obtained,which can provide reliable reference for the similar mines.
Keywords:Sharply-inclined thin orebody  Analytic hierarchy process  Short-hole shrinkage method  Judgment matrix
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