文章摘要
高岭,李建朋,曹正波.基于反分析赋权方法的岩爆预测云模型研究[J].地震工程学报,2020,42(2):498-504. GAO Ling,LI Jianpeng,CAO Zhengbo.A Cloud Model for Rock Burst Prediction Based onthe Back Analysis Weighting Approach[J].China Earthquake Engineering Journal,2020,42(2):498-504.
基于反分析赋权方法的岩爆预测云模型研究
A Cloud Model for Rock Burst Prediction Based onthe Back Analysis Weighting Approach
投稿时间:2018-05-10  
DOI:10.3969/j.issn.1000-0844.2020.02.498
中文关键词: 岩爆;云模型;因子权重;反分析
英文关键词: rock burst;cloud model;weight;back analysis
基金项目:河北省交通运输厅科技项目(20130012)
作者单位
高岭 河北省交通规划设计院, 河北 石家庄 050011 
李建朋 河北省交通规划设计院, 河北 石家庄 050011 
曹正波 河北省交通规划设计院, 河北 石家庄 050011 
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中文摘要:
      为了综合考虑岩爆预测实践中的随机性与模糊性,云模型理论被引入到岩爆预测方法中。然而现有岩爆预测云模型的指标权重值在客观性和准确性方面尚需提高,为此本文提出基于反分析赋权方法的岩爆云模型。在给出该模型具体实现步骤的基础上,推导建立优化目标函数之后选用洞室最大切向应力与岩石抗压强度的比值、岩石抗压强度与抗拉强度的比值、弹性能量指数等作为评判指标,基于18个岩爆工程实例,利用Matlab软件开展了指标权重的反分析计算。最后,将新建立的岩爆预测云模型应用于江边水电站和马路坪矿的岩爆预测中,并与主观赋权方法云模型的预测结果对比分析,检验了其可行性与有效性。研究表明,基于反分析赋权方法的岩爆预测云模型赋权过程中主观性干扰因素较小,预测结果准确率较高。
英文摘要:
      To comprehensively consider the randomness and ambiguity in rock burst prediction practice, a cloud model theory is introduced into the method. However, the index weight value of the existing rock burst prediction cloud model needs to be improved in terms of objectivity and accuracy. Therefore, this paper proposes a rock burst cloud model based on a back analysis weighting approach. First, the specific implementation steps of the model are given, and the optimization objective function is established. Next, the ratio of maximum tangential stress of cavern to the compressive strength of rock, the ratio of compressive strength of rock to the tensile strength, and the elastic energy index were selected as judging indexes. Based on 18 rock burst engineering examples, the back analysis of index weights was carried out using MATLAB software. Finally, the newly-built cloud model was applied to the rock burst prediction of the Jiangbian hydropower station and Maluping mine. Results were compared with the predictive results of the cloud model based on a subjective weighting method to test the feasibility and effectiveness of the proposed model. The research showed that the subjective interference factors in the weighting process of the rock burst cloud model based on back analysis weighting approach were few, thus the accuracy of prediction results was high.
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