基于模糊聚类方法的煤巷围岩稳定性分类研究
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摘要
针对赵庄矿大断面煤巷围岩稳定性展开研究,采用模糊聚类法对赵庄矿3个盘区的15条巷道进行分类。选取巷道顶板强度σ_(c1)、巷道两帮围岩强度σ_(c2)、巷道底板围岩强度σ_(c3)、巷道埋深H、顶高比N、煤柱宽度X、最大水平主应力σ_h作为围岩稳定性分类的指标。根据现场调研数据获得判别矩阵,计算得到分类指标的权值分别为0.13、0.05、0.05、0.07、0.21、0.17、0.21。采用模糊聚类法分析,将选取煤巷分为6类最为合理,同类别煤巷围岩具有相似的稳定性,可采取相同或相似的支护手段来维护巷道。现场试验表明,模糊聚类方法对巷道的分类结果可有效指导煤巷围岩支护参数设计,保持巷道围岩变形量在可控范围内。
Aiming at the stability of surrounding rock of large section coal roadway in Zhaozhuang mine,the fuzzy clustering method is used to classify 15 roadways in 3 panels in Zhaozhuang Mine. Through the statistical analysis of the classification indicators,the strength of the roof,σ_(c1),the strength of ribs,σ_(c2),the strength of floor,σ_(c3),the depth of the roadway,H,the ratio of Roadway height and mining height,N,pillar width,X,the maximum horizontal principal stress σhwere selected as an indicator of rock stability classification. According to the field investigation data,the discernibility matrix is obtained,and the weight of the classification index calculated is respectively 0. 13,0. 05,0. 05,0. 07,0. 21,0. 17,0. 21. Using fuzzy clustering method to calculate and analyze,it is most reasonable to divide the selected coal roadway into six categories,and the surrounding rock of each category has similar stability. The same or similar support means can be adopted to maintain the same category roadway. Field tests show that the fuzzy clustering results of the classification of roadway can effectively guide the design of surrounding rock support parameters of the roadway to keep the surrounding rock deformation within the controllable range.
Aiming at the stability of surrounding rock of large section coal roadway in Zhaozhuang mine,the fuzzy clustering method is used to classify 15 roadways in 3 panels in Zhaozhuang Mine. Through the statistical analysis of the classification indicators,the strength of the roof,σ_(c1),the strength of ribs,σ_(c2),the strength of floor,σ_(c3),the depth of the roadway,H,the ratio of Roadway height and mining height,N,pillar width,X,the maximum horizontal principal stress σhwere selected as an indicator of rock stability classification. According to the field investigation data,the discernibility matrix is obtained,and the weight of the classification index calculated is respectively 0. 13,0. 05,0. 05,0. 07,0. 21,0. 17,0. 21. Using fuzzy clustering method to calculate and analyze,it is most reasonable to divide the selected coal roadway into six categories,and the surrounding rock of each category has similar stability. The same or similar support means can be adopted to maintain the same category roadway. Field tests show that the fuzzy clustering results of the classification of roadway can effectively guide the design of surrounding rock support parameters of the roadway to keep the surrounding rock deformation within the controllable range.
引文
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[2]Zhang Lianyang,Einstein H H.Using RQD to estimate the deformation modulus of rock masses[J].International Journal of Rock Mechanics&Mining Sciences,2004,41(2):337-341.
[3]张亦飞,程传国,张海丰,等.公路隧道围岩的区间数组合分类法[J].岩土工程学报,2008,30(12):1915-1920.Zhang Yifei,Cheng Chuanguo,Zhang Haifeng,et al.Interval numbers based integrated classification method for surrounding rock of highway tunnel[J].Chinese Journal of Rock Mechanics and Engineering,2008,30(12):1915-1920.
[4]李兴斌.围岩稳定性分类技术的现状和展望[J].现代工业经济和信息化,2013,26(16):46-47,60.Li Xingbin.Status and prospect of surrounding rock stability classification technology[J].Modern Industrial Economy and Information,2013,26(16):46-47,60.
[5]Barton N,Grimsta E.Rockmass conditions dictate choice between NMT and NATM[J].Tunnels and Tunneling,1994,13(1):14-18.
[6]Bieniawski Z T.Engineering rock mass classification-a complete manual for engineers and geologists in mining,civil and petroleum engineering[M].Wiley:Interscience Publication,1989.
[7]申艳军,徐光黎.国标岩体分级标准BQ的图解法表示[J].岩石力学与工程学报,2012,31(增2):3659-3665.Shen Yanjun,Xu Guangli.Using graphic method to represent national standard for rock masses classification BQ[J].Chinese Journal of Rock Mechanics and Engineering,2012,31(S2):3659-3665.
[8]Laubscher DH,Steffen,Robertson,等.采矿用岩体分值地质力学分类法[J].有色矿山,1990,28(6):17-30.Laubscher DH,Steffen,Robertson,et al.Mining rock mass fraction geomechanical classification[J].China Mine Engineering,1990,28(6):17-30.
[9]康红普,王金华,林健.煤矿巷道支护技术的研究与应用[J].煤炭学报,2010,35(11):1809-1814.Kang Hongpu,Wang Jinhua,Lin Jian.Study and applications of roadway support techniques for coal mines[J].Journal of China Coal Society,2010,35(11):1809-1814.
[10]乔兰,丁立丰.围岩稳定性分类的灰色优化模型及其在新城金矿的应用[J].有色金属,2000,31(2):30-33.Qiao Lan,Ding Lifeng.Gray optimization model of surrounding rock stability classification and its application in Xincheng Gold Mine[J].Nonferrous Metal,2000,31(2):30-33.
[11]赵洪波,冯夏庭,尹顺德.基于支持向量机的岩体工程分级[J].岩土力学,2002,23(6):698-701.Zhao Hongbo,Feng Xiating,Yin Shunde.Classification of engineering rock based on support vector machine[J].Rock and Soil Mechanics,2002,23(6):698-701.
[12]朱一丁,马文涛.回采巷道围岩分类的支持向量机方法[J].采矿与安全工程学报,2006,23(3):362-365.Zhu Yiding,Ma Wentao.Method of support vector machines for classifying surrounding rocks of gateways[J].Journal of Mining&Safety Engineering,2006,23(3):362-365.
[13]宫凤强,李夕兵.隧洞围岩稳定性评价的Bayes判别分析法及应用[J].地下空间与工程学报,2007,3(6):1138-1141.Gong Fengqiang,Li Xibing.The Bayes discriminant analysis method for stability evaluation of rock surrounding in tunnel and its application[J].Chinese Journal of Underground Space and Engineering,2007,3(6):1138-1141.
[14]莫元彬,张清.围岩分类专家系统中的不确定性推理处理方法[J].土木工程学报,1989(2):65-77.Mo Yuanbin,Zhang Qing.Uncertainty reasoning method in surrounding rock classification expert system[J].China Civil Engineering Journal,1989(2):65-77.
[15]谭云亮,王泳嘉.回采巷道分类指标的神经网络聚类分析模型[J].岩石力学与工程学报,1995,14(2):139-144.Tan Yunliang,Wang Yongjia.Neural network clustering analysis model of mining lane classification[J].Chinese Journal of Rock Mechanics and Engineering,1995,14(2):139-144.