[1]唐 皓,段 钊,唐胜利,等.岩体质量分级的组合赋权云模型[J].西安科技大学学报,2019,(01):79-87.[doi:10.13800/j.cnki.xakjdxxb.2019.0112 ]
 TANG Hao,DUAN Zhao,TANG Sheng-li,et al.Combined weight cloud model of rock mass quality classification[J].Journal of Xi'an University of Science and Technology,2019,(01):79-87.[doi:10.13800/j.cnki.xakjdxxb.2019.0112 ]
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岩体质量分级的组合赋权云模型(/HTML)
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西安科技大学学报[ISSN:1672-9315/CN:61-1434/N]

卷:
期数:
2019年01期
页码:
79-87
栏目:
出版日期:
2019-02-28

文章信息/Info

Title:
Combined weight cloud model of rock mass quality classification
文章编号:
1672-9315(2019)01-0079-09
作者:
唐 皓12段 钊12唐胜利1王东坡2曾 鹏2
(1.西安科技大学 地质与环境学院,陕西 西安 710054; 2.成都理工大学 地质灾害防治与地质环境保护国家重点实验室,四川 成都 610069)
Author(s):
TANG Hao12DUAN Zhao12TANG Sheng-li1WANG Dong-po2ZENG Peng2
(1.College of Geology and Environment,Xi'an University of Science and Technology,Xi'an 710054,China; 2.State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Technology,Chengdu 610069,China)
关键词:
地质工程 岩体质量分级 云模型 组合赋权 云发生器 综合确定度
Keywords:
geology engineering quality classification of rock mass combined weight cloud model cloud generator comprehensive degree of certainty
分类号:
TU 457
DOI:
10.13800/j.cnki.xakjdxxb.2019.0112
文献标志码:
A
摘要:
岩体质量分级是一个复杂的工程决策问题,不仅具有模糊性及不确定性特征,而且用于分级评价的因子权重难以准确确定。基于云模型处理模糊性和不确定性问题的独特优势,同时借助组合赋权技术,提出组合赋权-云模型的岩体质量分级评价模型。该模型选用岩石单轴抗压强度σc,岩石质量指标RQD,结构面间距Jd,结构面摩擦系数f,岩体钻进速度T及岩体声波波速V作为岩体质量等级评价因子,根据单指标岩体质量分级标准计算各评价因子隶属于不同岩体质量等级的云数字特征。同时,以相关岩体质量分级案例为对象,在德尔菲法及变异系数法求得的评价因子权重基础上,基于距离函数约束思路获得组合赋权后的评价因子综合权重。再依据正向正态云发生器,得到待评案例样本的综合确定度,由最大综合确定度判定岩体质量等级。云模型应用结果与其他评价方法应用结果对比分析表明,组合赋权-云模型在岩体质量分级应用中具有良好的适用性和可靠性,为岩体质量分级评价提供了一种新思路。
Abstract:
Quality classification of rock mass is a complicated decision problem of project.It has not only characteristics of fuzzy and uncertainty,but also the weight of evaluation factor is difficult to determine accurately.For this purpose,on the basis of advantage of cloud model for dealing with fuzzy and uncertainty problem and by combined weight technology,an evaluation model for quality classification of rock mass based on combined weight and cloud model is proposed.Uniaxial compressive strength of rock,rock quality indicator,structural face interval,friction coefficient of structural face,drilling speed and acoustic of rock mass are selected as evaluation factors of model,and according to the criterion of quality classification of rock mass,and on the basis of quality classification criterion of rock mass,each evaluation factor is calculated using the characteristics of cloud number of quality levels of rock mass.Taking the relevant cases of quality classification of rock mass as object,and on the basis of evaluation factors weight which are got by Delphi and variance coefficient method,the comprehensive weights of evaluation factors are got based on constrains of distance function.The comprehensive degrees of certainty of samples for evaluation are calculated by the positive normal cloud generator,and the quality level of rock mass is finally specified by the maximum certainty degree.Comparing application of the cloud model with the other methods,it shows that combined weight-cloud model has good applicability and reliability for the quality classification of rock mass,and is a new idea for quality classification of rock mass.

参考文献/References:


[1] 邬爱清,柳赋铮.国标《工程岩体分级标准》的应用与进展[J].岩石力学与工程学报,2012,31(8):1513-1523. WU Ai-qing,LIU Fu-zheng.Advancement and application of the standard of engineering classification of rock masses[J].Chinese Journal of Rock Mechanics and Engineering,2012,31(8):1513-1523.
[2]蔡 斌.国标《工程岩体分级标准》应用中的几个问题[J].岩土力学,2003,24(S1):74-76. CAI Bin.Discussion about several problems of the use of standard for engineering classification of rock masses[J].Rock and Soil Mechanics,2003,24(S1):74-76.
[3]Deere D U.Technical description of rock cores for engineering purposes[J].Rock Mechanics and Engineering Geology,1964,1(1):17-22.
[4]Barton N,Lien R,Lunde J.Engineering classification of rock masses for the design of tunnel support[J].Rock Mechanics and Rock Engineering,1974,6(4):189-236.
[5]Bieniawski Z T.Classification of rock masses for engineering:the RMR system and future trends[J].Rock Testing & Site Characterization,1993,1(1):553-573.
[6]陶振宇,彭祖赠.模糊数学在岩石工程分类中的应用[J].岩土工程学报,1981,3(1):36-45. TAO Zhen-yu,PENG Zu-zeng.Application of fuzzy mathematics to the engineering classification of rocks[J].Chinese Journal of Geotechnical Engineering,1981,3(1):36-45.
[7]刘玉成,刘延保.灰色关联理论在矿山岩体质量评价中的应用[J].矿业工程,2006,4(6):16-18. LIU Yu-cheng,LIU Yan-bao.Gray relevancy theory applied in assessment of rock body quality of mine[J].Mining Engineering,2006,4(6):16-18.
[8]原国红,陈剑平,马 琳.可拓评判方法在岩体质量分类中的应用[J].岩石力学与工程学报,2005,24(9):1539-1544. YUAN Guo-hong,CHEN Jian-ping,MA Lin.Application of extenics in evaluating of engineering quality of rock masses[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(9):1539-1544.
[9]贾 超,肖树芳,刘 宁.可拓学理论在洞室岩体质量评价中的应用[J].岩石力学与工程学报,2003,22(5):751-756. JIA Chao,XIAO Shu-fang,LIU Ning.Application of extenics theory to evaluation of tunnel rock quality[J].Chinese of Journal of Rock Mechanics and Engineering,2003,22(5):751-756.
[10]王 彪,陈剑平,李钟旭,等.人工神经网络在岩体质量分级中的应用[J].世界地质,2004,23(1):64-68. WANG Biao,CHEN Jian-ping,LI Zhong-xu,et al.Application of artificial neural network in rockmass quality classification[J].Global Geology,2004,23(1):64-68.
[11]李 强.BP神经网络在工程岩体质量分级中的应用研究[J].西北地震学报,2002,24(3):29-33. LI Qiang.Study on the application of BP nervous network in classification of rockmass quality[J].North Western Seismological Journal,2002,24(3):29-33.
[12]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 Hong-bo,FENG Xia-ting,YIN Shun-de.Classification of engineering rock based on support vector machine[J].Rock and Soil Mechanics,2002,23(6):698-701.
[13]刘志祥,吴蝶媚,唐志祥.基于熵权属性识别模型的岩体质量分级[J].科技导报,2014,32(22):52-56. LIU Zhi-xiang,WU Die-mei,TANG Zhi-xiang.Quality classification of rock mass based on attribute recognition model of entropy weight[J].Science & Technology Review,2014,32(22):52-56.
[14]文畅平.基于属性数学理论的岩体质量分级方法[J].水力发电学报,2008,27(3):75-80. WEN Chang-ping.Classification of rock-mass stability based on attribute mathematical theory[J].Journal of Hydroelectric Engineering,2008,27(3):75-80.
[15]姚银佩,李夕兵,宫凤强,等.加权距离判别分析法在岩体质量等级分类中的应用[J].岩石力学与工程学报,2010,29(S2):4119-4123. YAO Yin-pei,LI Xi-bing,GONG Feng-qiang,et al.Application of weighted mahalanobis distance discriminant analysis method to classification of rock mass quality[J].Chinese Journal of Rock Mechanics and Engineering,2010,29(S2):4119-4123.
[16]邱道宏,陈剑平,阙金声,等.基于粗糙集和人工神经网络的洞室岩体质量评价[J].吉林大学学报(地球科学版),2008,38(1):86-91. QIU Dao-hong,CHEN Jian-ping,QUE Jin-sheng,et al.Evaluation of tunnel rock quality with routh sets theory and artificial neural networks[J].Journal of Jilin University(Earth Science Edition),2008,38(1):86-91.
[17]肖云华,王 清,陈剑平,等.基于粗糙集和支持向量机的融合算法在岩体质量评价中的应用[J].煤田地质与勘探,2008,36(6):49-53. XIAO Yun-hua,WANG Qing,CHEN Jian-ping,et al.Application of data fusion in evaluation of engineering quality of rock mass based on rough sets and support vector machine[J].Coal Geology & Exploration,2008,36(6):49-53.
[18]李德毅,孟海军,史雪梅.隶属云和隶属云发生器[J].计算机研究与发展,1995,32(6):15-20. LI De-yi,MENG Hai-jun,SHI Xue-mei.Membership clouds and membership cloud generators[J].Computer R & D,1995,32(6):15-20.
[19]周科平,林 允,胡建华,等.基于熵权—正态云模型的岩爆烈度分级预测研究[J].岩土力学,2016,37(S1):596-602. ZHOU Ke-ping,LIN Yun,HU Jian-hua,et al.Grading prediction of rockburst intensity based on entropy and normal cloud model[J].Rock and Soil Mechanics,2016,37(S1):596-602.
[20]郝 杰,侍克斌,王显丽,等.基于模糊C-均值算法粗糙集理论的云模型在岩爆等级评价中的应用[J].岩土力学,2016,37(3):859-866. HAO Jie,SHI Ke-bin,WANG Xian-li,et al.Application of cloud model to rating of rockburst based on rough set of FCM algorithm[J].Rock and Soil Mechanics,2016,37(3):859-866.
[21]王迎超,靖洪文,张 强,等.基于正态云模型的深埋地下工程岩爆烈度分级预测研究[J].岩土力学,2015,36(4):1189-1194. WANG Ying-chao,JING Hong-wen,ZHANG Qiang,et al.A normal cloud model-based study of grading prediction of rockburst intensity in deep underground engineering[J].Rock and Soil Mechanics,2015,36(4):1189-1194.
[22]李 健,汪明武,徐 鹏,等.基于云模型的围岩稳定性分类[J].岩土工程学报,2014,36(1):83-87. LI Jian,WANG Ming-wu,XU Peng,et al.Classification of stability of surrounding rock using cloud model[J].Chinese Journal of Geotechnical Engineering,2014,36(1):83-87.
[23]张 军,陈征宙,刘登峰.基于云模型的岩质边坡稳定性评估研究[J].水文地质工程地质,2014,41(6):44-50. ZHANG Jun,CHEN Zheng-miao,LIU Deng-feng.Stability evaluation of a rock slope based on the cloud model[J].Hydrogeology & Engineering Geology,2014,41(6):44-50.
[24]江强强,方 堃,章广成.基于新组合赋权法的地质灾害危险性评价[J].自然灾害学报,2015,24(3):28-36. JIANG Qiang-qiang,FANG Kun,ZHANG Guang-cheng.Assessment of geohazards risk based on new combined weight method[J].Journal of Natural Disasters,2015,24(3):28-36.
[25]贾贵义,全永庆,黎志恒,等.基于组合赋权法的白龙江流域甘肃段地质灾害危险性评价[J].冰川冻土,2014,36(5):1227-1236. JIA Gui-yi,QUAN Yong-qing,LI Zhi-heng,et al.Geo-hazards assessment for the Gansu segment in Bailongjiang River basin by using combined weight method[J].Journal of Glaciology and Geocryology,2014,36(5):1227-1236.
[26]匡乐红,徐林荣,刘宝琛.组合赋权法确定地质灾害危险性评价指标权重[J].地下空间与工程学报,2006,2(6):1063-1067. KUANG Le-hong,XU Lin-rong,LIU Bao-chen.A combination weighting method for determining the index weight geological hazards risk assessment[J].Chinese Journal of Underground Space and Engineering,2006,2(6):1063-1067.
[27]李军霞,王常明,王钢城.基于组合赋权-未确知测度理论的滑坡险性评价[J].岩土力学,2013,34(2):468-474. LI Jun-xia,WANG Chang-ming,WANG Gang-cheng.Landslide risk assessment based on combination weighting-unascertained measure theory[J].Rock and Soil Mechanics,2013,34(2):468-474.
[28]张 晨,王 清,陈剑平,等.金沙江流域泥石流的组合赋权法危险度评价[J].岩土力学,2011,32(3):831-836. ZHANG Chen,WANG Qing,CHEN Jian-ping,et al.Evaluation of debris flow risk in Jinsha River based on combined weight process[J].Rock and Soil mechanics,2011,32(3):831-836.
[29]郭庆清,刘磊磊,张绍和,等.基于组合赋权法和聚类分析法的岩爆预测[J].长江科学院院报,2013,30(12):54-59. GUO Qing-qing,LIU Lei-lei,ZHANG Shao-he,et al.Prediction of rockburst by combined weight method and cluster analysis method[J].Journal of Yangtze River Scientific Research Institute,2013,30(12):54-59.
[30]初建宇,马丹祥,苏幼坡.基于组合赋权TOPSIS模型的城镇固定避难场所选址方法研究[J].土木工程学报,2013,46(S2):307-312. CHU Jian-yu,MA Dan-xiang,SU You-po.Study on site selection of resident emergency congregate shelters based on combined weighting TOPSIS[J].China Civil Engineering Journal,2013,46(S2):307-312.
[31]王国胤,李德毅,姚一豫,等.云模型与粒度计算[M].北京:科学出版社,2012. WANG Guo-yin,LI De-yi,YAO Yi-yu,et al.Cloud model and granular computing[M].Beijing:Science Press,2012.

备注/Memo

备注/Memo:
收稿日期:2018-05-20 责任编辑:李克永
基金项目:国家自然科学基金(41602305,41572287,41602304)
通信作者:唐 皓(1985-),男,陕西勉县人,讲师,E-mail:329689614@qq.com
更新日期/Last Update: 2019-02-28