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黄金科学技术 ›› 2018, Vol. 26 ›› Issue (3): 365-371.doi: 10.11872/j.issn.1005-2518.2018.03.365

• 采选技术与矿山管理 • 上一篇    下一篇

基于AHP和熵权TOPSIS模型的岩爆预测方法

卢富然,陈建宏   

  1. 中南大学资源与安全工程学院,湖南 长沙 410083
  • 收稿日期:2017-05-27 修回日期:2017-08-09 出版日期:2018-06-30 发布日期:2018-07-28
  • 作者简介:卢富然(1992-),男,辽宁铁岭人,硕士研究生,从事采矿工艺与技术研究工作。1670635059@qq.com
  • 基金资助:
    国家自然科学基金项目“地下金属矿采掘计划可视化优化方法与技术研究”(编号:51374242)和国家自然科学基金青年基金项目“基于人工智能的矿山技术经济指标动态优化研究”(编号:51404305)联合资助
     

Rockburst Prediction Method Based on AHP and Entropy Weight TOPSIS Model

LU Furan,CHEN Jianhong   

  1. School of Resources and Safety Engineering,Central South University,Changsha 410083,Hunan,China
  • Received:2017-05-27 Revised:2017-08-09 Online:2018-06-30 Published:2018-07-28

摘要: 为了准确预测地下金属矿的岩爆情况,建立了AHP和熵权TOPSIS模型。运用AHP和熵权法的基本原理,从岩性条件、应力条件和围岩条件3个方面选取预测指标,最终确定的指标为岩石的单轴抗压强度〖σ〗_c、压拉比〖σ〗_c/σ_t、弹性变形指数〖W〗_et、切应力与单轴抗压强度的比值〖σ〗_θ/σ_c和完整性系数〖K〗_v,分别为各预测指标分配合理的权重。然后,运用TOPSIS的基本原理,结合AHP和熵权法得到的权重来计算各岩爆等级临界值和实际矿山数据的贴近度,通过对比这2个贴近度来预测岩爆是否发生。实例研究表明:所建模型得到的预测结果与工程实际情况相一致,因此认为AHP和熵权TOPSIS模型可用于准确预测地下矿山的岩爆问题。

关键词: 层次分析法, 熵权法, 逼近理想解排序法, 岩爆, 预测指标, 权重分配, 金属矿山, 深部开采

Abstract: To accurately predict the rockburst of underground metal mine,a AHP and entropy weight TOPSIS model was established.The predictors of rockburst were selected from lithological,stress and rock conditions,the weight of uniaxial compressive strength 〖σ〗_c,the rate of rock’s compressive tensile strength 〖σ〗_c/σ_t,the elastic energy index of rock 〖W〗_et,the stress coefficient of rock 〖σ〗_θ/σ_c and integrality coefficient 〖K〗_v were calculated as the predictors of rockburst by AHP and entropy weight method.Then the closeness of rockburst levels’ critical values and realistic mines’ data were calculated by TOPSIS,combined with the weight calculated by AHP and entropy weight method.The occurrence of rockburst was predicted by comparing these two closenesses.Case study shows the predicted result of the established model is consistent well with the practical engineering,so the AHP and entropy weight TOPSIS model can be used to predict rockburst of underground metal mine accurately.

Key words: analytic hierarchy process, entropy weight method, technique for order preference by similarity to ideal solution, rockburst, prediction index, weight allocation, metal mine, deep mining

中图分类号: 

  • TU45
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