基于隧道铣挖施工适应性的围岩质量分级方法

doi:10.13722/j.cnki.jrme.2019.0040

Abstract
Figure/Table
References (0)
Related Citation (15)

Download: PDF (468 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract The classification result of surrounding rock quality is important to select the road-header as the tunnel excavation method or not，so the classification method should be proposed. Firstly，a classification standard of surrounding rock quality was presented based on the instantaneous cutting rate(ICR)，which can comprehensively reflect the influence of engineering geological condition and mechanical equipment factors on tunnel milling excavation. Secondly，the influence of the affecting factors and the evaluation indexes，their fuzzy and hierarchical characteristics on the classification result of surrounding rock quality was discussed. Then，a three-stage fuzzy synthetic judgment model of classify surrounding rock quality for tunnel excavation with road-header was suggested，and a method for determining the membership degrees and weight vectors of continuous and discrete evaluation indices was proposed. A corresponding strategy was also proposed to reduce the subjectivity of determining the membership degrees and weight vectors. Finally，the proposed method was applied to three different practical projects，and comparison between the calculation and measured results shows that the proposed method is feasible and reasonable.

Key words： tunnelling engineering tunnel milling excavation method surrounding rock mass classification instantaneous cutting rate three-stage fuzzy synthetic judgment

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	CAO Wengui1
	LI Shulin1
	2
	ZHANG Yongjie3

Cite this article:

CAO Wengui1,LI Shulin1,2, et al. A classification method of surrounding rock mass quality based on tunnel milling excavation construction adaptability[J]. , 2019, 38(8): 1513-1522.

URL:

https://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2019.0040 OR https://rockmech.whrsm.ac.cn/EN/Y2019/V38/I8/1513

[1]	骆驰. 软弱破碎围岩地铁隧道掘进机施工力学研究[硕士学位论文][D]. 成都：西南交通大学，2009.(LUO Chi. Study on mechanical behavior of metro tunnel construction by tunneling machine in weak-broken surrounding rock[M. S. Thesis][D]. Chengdu：Southwest Jiaotong University，2009.(in Chinese))
[2]	曹文贵，翟友成，王江营. 基于漂移度的隧道围岩质量分级组合评价方法[J]. 岩土工程学报，2012，34(6)：978-984.(CAO Wengui，ZHAI Youcheng，WANG Jiangying. Combination evaluation method for classification of surrounding rock quality of tunnel based on drifting degree[J]. Chinese Journal of Geotechnical Engineering，2012，34(6)：978-984.(in Chinese))
[3]	曹文贵，张永杰. 地下结构岩体质量分类的变权重二级模糊综合评判方法研究[J]. 岩石力学与工程学报，2006，25(8)：1 612-1 618. (CAO Wengui，ZHANG Yongjie. Study on two-stage fuzzy synthetic judgment method with changing weight value for rock quality classification in underground structures[J]. Chinese Journal of Rock Mechanics and Engineering，2006，25(8)：1 612-1 618.(in Chinese))
[4]	BARTON N. TBM tunneling in jointed and faulted rock[M]. Rotterdam：Balkema，2000：39-70.
[5]	孙金山，卢文波，苏利军，等. 基于TBM掘进参数和渣料特征的岩体质量指标辨识[J]. 岩土工程学报，2008，30(12)：1 847-1 854. (SUN Jinshan，LU Wenbo，SU Lijun，et al. Rock mass rating identification based on TBM performance parameters and muck characteristics[J]. Chinese Journal of Geotechnical Engineering，2008，30(12)：1 847-1 854.(in Chinese))
[6]	祁生文，伍法权. 基于模糊数学的TBM施工岩体质量分级研究[J]. 岩石力学与工程学报，2011，30(6)：1 225-1 229.(QI Shengwen，WU Faquan. Surrounding rockmass quality classification of tunnel cut by TBM with fuzzy mathematics method[J]. Chinese Journal of Rock Mechanics and Engineering，2011，30(6)：1 225-1 229.(in Chinese))
[7]	宋克志，袁大军，王梦恕. 基于盾构掘进参数分析的隧道围岩模糊判别[J]. 土木工程学报，2009，42(1)：107-113.(SONG Kezhi，YUAN Dajun，WANG Mengshu. Fuzzy identification of surrounding rock conditions based on analysis of shield tunneling data[J]. China Civil Engineering Journal，2009，42(1)：107-113.(in Chinese))
[8]	闫长斌，路新景. 基于改进的距离判别分析法的南水北调西线工程TBM施工围岩分级[J]. 岩石力学与工程学报，2012，31(7)：1 446-1 451. (YAN Changbin，LU Xinjing. Classification of surrounding rock mass by TBM tunneling based on improved distance discriminant analysis method in west route of south-to-north water transfer project[J]. Chinese Journal of Rock Mechanics and Engineering，2012，31(7)：1 446-1 451.(in Chinese))
[9]	吴东鹏，杨新安. 铣挖法隧道围岩分级方法研究[J]. 现代隧道技术，2016，53(4)：16-21.(WU Dongpeng，YANG Xinan. Rock classification for a tunnel excavated by rotary drum cutter[J]. Modern Tunnelling Technology，2016，53(4)：16-21.(in Chinese))
[10]	EBRAHIMABADI A，GOSHTASBI K，SHAHRIAR K，et al. Predictive models for roadheaders' cutting performance in coal measure rocks[J]. Yerbilimleri/ Earth Sciences，2011，32(2)：89-104.
[11]	EBRAHIMABADI A，GOSHTASBI K，SHAHRIAR K，et al. A model to predict the performance of roadheaders based on the Rock Mass Brittleness Index[J]. Journal of the Southern African Institute of Mining and Metallurgy，2011，111(5)：355-364.
[12]	BILGIN N，DINCER T，COPUR H，et al. Some geological and geotechnical factors affecting the performance of a roadheader in an inclined tunnel[J]. Tunnelling and Underground Space Technology，2004，19(6)：629-636.
[13]	FOWELL R J，JOHNSON S T. Rock classification and assessment for rapid excavation[J]. Developments in Geotechnical Engineering，1981，32：241-244.
[14]	中华人民共和国国家标准编写组. GB/T50218—2014 工程岩体分级标准[S]. 北京：中国计划出版社，2014.(The National Standards Compilation Group of People?s Republic of China. GB/T50218—2014 Standard of engineering classification of rock masses[S]. Beijing：China Planning Press，2014.(in Chinese))
[15]	EBRAHIMABADI A，AZIMIPOUR M，BAHREINI A. Prediction of roadheaders? performance using artificial neural network approaches (MLP and KOSFM)[J]. Journal of Rock Mechanics and Geotechnical Engineering，2015，7(5)：573-583.
[16]	ORIGLIASSO C，CARDU M，KECOJEVIC V. Surface miners：evaluation of the production rate and cutting performance based on rock properties and specific energy[J]. Rock Mechanics and Rock Engineering，2014，47(2)：757-770.
[17]	AVUNDUK E，TUMAC D，ATALAY A K. Prediction of roadheader performance by artificial neural network[J]. Tunnelling and Underground Space Technology，2014，44(3)：3-9.
[18]	KELE? S. Cutting performance assessment of a medium weight roadheader at Çayirhan coal mine[M. S. Thesis][D]. Ankara：Middle East Technical University，2005.
[19]	李晓豁. 掘进机截割的关键技术研究[M]. 北京：机械工业出版社，2008：4-60.(LI Xiaohuo. Research on key technologies of cutting of roadheader[M]. Beijing：China Machine Press，2008：4-60.(in Chinese))
[20]	苏永华. 岩土参数模糊隶属函数的构造方法及应用[J]. 岩土工程学报，2007，29(12)：1 772-1 779.(SU Yonghua. Constructing method of fuzzy membership function of geotechnical parameters and its application[J]. Chinese Journal of Geotechnical Engineering，2007，29(12)：1 772-1 779.(in Chinese))
[21]	龚秋明. 掘进机隧道掘进概论[M]. 北京：科学出版社，2014：118-150.(GONG Qiuming. TBM tunnelling：an overview[M]. Beijing：Science Press，2014：118-150.(in Chinese))
[22]	盛骤. 概率论与数理统计[M]. 4版. 北京：高等教育出版社，2008：130-135.(SHENG Zhou. Probability and mathematical statistics[M]. 4th ed. Beijing：High Education Press，2008：130-135.(in Chinese))
[23]	ZHANG Q，HAN Z，ZHANG M，et al. New model for predicting instantaneous cutting rate of axial-type roadheaders[J]. Ksce Journal of Civil Engineering，2017，21(1)：1-10.
[24]	张倩倩. 掘进机截齿截割硬岩的试验与数值模拟研究[博士学位论文][D]. 太原：太原理工大学，2016.(ZHANG Qianqian. Experimental and numerical research on rock cutting by roadheader picks[Ph. D. Thesis][D]. Taiyuan：Taiyuan University of Technology，2016.(in Chinese))
[25]	李刚，李建平，孙晓蕾，等. 主客观权重的组合方式及其合理性研究[J]. 管理评论，2017，29(12)：19-28.(LI Gang，LI Jianping，SUN Xiaolei，et al. Research on a combined method of subjective- objective weighing and the its rationality[J]. Management Review，2017，29(12)：19-28.(in Chinese))