研究论文

地下工程岩爆灾害预测的属性综合评价模型

  • 王李管 ,
  • 裴安磊 ,
  • 彭平安
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  • 中南大学资源与安全工程学院; 中南大学数字矿山研究中心; 长沙迪迈数码科技股份有限公司, 长沙 410083
王李管,教授,研究方向为数字矿山,电子信箱:liguan_wang@163.com

收稿日期: 2013-11-15

  修回日期: 2014-01-16

  网络出版日期: 2014-03-26

基金资助

国家高技术研究发展计划(863计划)项目(2011AA060407)

Attribute Synthetic Evaluation Model for Rockburst Disaster Prediction in Underground Engineering

  • WANG Liguan ,
  • PEI Anlei ,
  • PENG Ping'an
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  • School of Resources and Safety Engineering, Central South University; Research Center of Digital Mine, Central South University; Changsha Digital Mine Co., Ltd, Changsha 410083, China

Received date: 2013-11-15

  Revised date: 2014-01-16

  Online published: 2014-03-26

摘要

针对地下工程岩爆灾害预测各种方法的局限性以及预报准确率低的现状,基于属性数学理论与方法,选取围岩最大切向应力与岩石单轴抗压强度之比、脆性系数和弹性能量指数作为岩爆灾害预测的主要评价指标,建立了岩爆灾害预测的属性综合评价模型,对岩爆的发生与否及其烈度进行了预测。应用属性数学理论,构造了各评价指标的属性测度函数,并利用相似数定义相似权的方法确定各指标的权重以计算综合属性测度,最后应用置信度准则进行属性识别,给出评价结果。以10 组典型地下工程为例,对该模型进行了验证,结果表明,该模型评价结果与实际情况有较好的一致性,验证了属性综合评价在岩爆灾害预测中的可行性和适用性,为地下工程岩爆灾害的预测提供了一种新途径。

本文引用格式

王李管 , 裴安磊 , 彭平安 . 地下工程岩爆灾害预测的属性综合评价模型[J]. 科技导报, 2014 , 32(8) : 22 -26 . DOI: 10.3981/j.issn.1000-7857.2014.08.002

Abstract

According to the present situation of the limitation and low accuracy of rockburst disaster prediction in underground engineering, based on the attribute mathematics theory, the ratio of maximum tangential stress to uniaxial compressive strength of rock, brittleness coefficient and elastic energy index are chosen as the discriminant indexes to build an attribute synthetic evaluation model for predicting the rockburst probability and intensity. The attribute measurement functions of each index are constructed based on the attribute mathematics theory, while the synthetic attributive measurement is calculated by the similar weight. Finally, the probability and intensity of rockburst samples are recognized by the confidence criterion. Taking 10 groups of underground engineering projects at home and abroad for example, the model is validated. Results show that the evaluation by this attribute synthetic model has a good consistency with the actual situation, which validates the feasibility and effectiveness of the proposed model for rockburst prediction. The methodology presented in the paper provides a reference for some similar engineering involving rockburst.

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