基于数字图像的盾构隧道衬砌裂缝病害诊断

doi:10.13722/j.cnki.jrme.2020.0157

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

Download: PDF (674 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract It has become a developing trend to use computer vision to detect structural defects of tunnel lining surface quickly and nondestructively. However，the existing methods for defect diagnosis cannot evaluate the severity of structural defects objectively according to the results of image recognition. In order to overcome the shortcoming，a novel and objective diagnosis index，named tunnel defect index-crack(TDI-C)，and grading standard for structural cracks of shield tunnel lining are proposed through binary images. Firstly，three parameters including length，maximum width and fractal dimension are adopted for the quantification of cracks using digital image processing. A dynamic block algorithm is proposed to calculate the length and maximum width of cracks. The fractal dimensions are calculated by box-counting algorithm. The larger the fractal dimension of cracks，the more complex the morphology of cracks. Secondly，taking tunnel section of 200 ring linings as the diagnostic scale，the accumulative value of the defect quantification parameter is calculated. The defect sample space composed of 21 tunnel sections is established. Three levels of structural defect grading and the defect level of each sample in the defect sample space are also determined rationally using the algorithm of K-means++ cluster. Through the method of partial least square regression analysis，a novel diagnosis index named TDI-C is proposed，and the grading standard of structural cracks for shield tunnels is established subsequently. Finally，a case study of structural crack diagnosis for metro shield tunnels is introduced to point out that the proposed method has more advantages than the existing methods.

Key words： tunnelling engineering shield tunnel lining structure digital image crack diagnosis index grading standard

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	LI Qingtong1
	HUANG Hongwei2
	3

Cite this article:

LI Qingtong1,HUANG Hongwei2,3. Diagnosis of structural cracks of shield tunnel lining based on digital images#br#[J]. , 2020, 39(8): 1658-1670.

URL:

https://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2020.0157 OR https://rockmech.whrsm.ac.cn/EN/Y2020/V39/I8/1658

[1] TTARD L，DEBONO C J，VALENTINO G，et al. Tunnel inspection using photogrammetric techniques and image processing：A review[J]. Journal of Photogrammetry and Remote Sensing，2018，144：180–188.
[2] 李庆桐，黄宏伟，薛亚东，等. 隧道衬砌图像清晰度影响因素的模型试验研究[J]. 岩石力学与工程学报，2017，36(增2)：3 915–3 926. (LI Qingtong，HUANG Hongwei，XUE Yadong，et al. Model test study on factors affecting image sharpness of tunnel lining[J]. Chinese Journal of Rock Mechanics and Engineering，2017，36(Supp.2)：3 915–3 926.(in Chinese))
[3] HUANG H W，LI Q T，ZHANG D M. Deep learning based image recognition for crack and leakage defects of metro shield tunnel[J]. Tunnelling and Underground Space Technology，2018，77：166–176.
[4] CHA Y J，CHOI W，BÜYÜKÖZTÜRK O. Deep learning-based crack damage detection using convolutional neural networks[J]. Computer-aided Civil and Infrastructure Engineering，2017，32(5)：361–378.
[5] SHIGETA Y，TOBITA T，KAMEMURA K，et al. Propose of tunnel crack index(TCI) as an evaluation method for lining concrete[J]. Journal of Japan Society of Civil Engineers Ser F1，2006，62(4)：628–632.
[6] 王平让. 隧道衬砌裂缝机器视觉检测方法及结构安全评估研究[博士学位论文][D]. 上海：同济大学，2013.(WANG Pingrang. Study on machine vision inspection method for cracks and structural safety assessment in tunnel lining[Ph. D. Thesis][D]. Shanghai：Tongji University，2013.(in Chinese))
[7] CHIU Y C，LEE C H，WANG T T，et al. Lining crack evolution：A qualitative and quantitative index for degradation of tunnels in operation[C]// Proceedings of the ITA World Tunnel 2015 Congress. Dubrovnik，Croatia：Lacroma Valamar Congress Center，2015：4.8.
[8] WU X Z，JIANG Y J，WANG J H，et al. A new health assessment index of tunnel lining based on the digital inspection of surface cracks[J]. Applied Sciences，2017，7(5)：507.
[9] 中华人民共和国行业标准编写组. CJJ/T 164－2011盾构隧道管片质量检测技术标准[S]. 北京：中国建筑工业出版社，2011.(The Professional Standards Compilation Group of People’s Republic of China. CJJ/T 164－2011 Standard for quality inspection of shield tunnel segment[S]. Beijing：China Architecture and Building Press，2011.(in Chinese))
[10] 中华人民共和国行业标准编写组. JTG H12－2015公路隧道养护技术规范[S]. 北京：人民交通出版社，2015.(The Professional Standards Compilation Group of People’s Republic of China. JTG H12－2015 Technical specifications of maintenance for highway tunnel[S]. Beijing：China Communication Press，2015.(in Chinese))
[11] 中华人民共和国国家标准编写组. GB 50446－2017盾构法隧道施工及验收规范[S]. 北京：中国建筑工业出版社，2017.(The National Standards Compilation Group of People¢s Republic of China. GB 50446－2017 Code for construction and acceptance of shield tunneling method[S]. Beijing：China Architecture and Building Press，2017.(in Chinese))
[12] LI Q T，XUE Y D，HUANG H W. Image recognition of shield tunnel cracks by deep learning[C]// Proceedings of the 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure. Brisbane，Australia：Queensland University of Technology， 2017：RS5–3–6.
[13] 孙 ?. 盾构隧道衬砌表观病害检测系统与裂损隧道结构性能研究[博士学位论文][D]. 上海：同济大学，2018.(SUN Yan. Study on defect image inspection and effect of inspected crack propagation on behavior[Ph. D. Thesis][D]. Shanghai：Tongji University，2018.(in Chinese))
[14] YANG W R，HE X J，DAI L. Damage behaviour of concrete beams reinforced with GFRP bars[J]. Composite Structures，2017，161：173–186.
[15] 谭小刚，张洪伟. 基于小尺度分形维数的裂缝图像分割方法[J]. 公路交通科技，2018，35(5)：34–39.(TAN Xiaogang，ZHANG Hongwei. A crack image segmentation method based on small scale fractal dimension[J]. Journal of Highway and Transportation Research and Development，2018，35(5)：34–39.(in Chinese))
[16] 彭瑞东，谢和平，鞠杨. 二维数字图像分形维数的计算方法[J]. 中国矿业大学学报，2004，33(1)：22–27.(PENG Ruidong，XIE Heping，JU Yang. Computation method of fractal dimension for 2D digital image[J]. Journal of China University of Mining and Technology，2004，33(1)：22–27.(in Chinese))
[17] 栾海洋，范颖芳，王大为，等. 基于分形理论的CFRP布增强混凝土梁抗弯性能研究[J]. 工程力学，2015，32(4)：160–168.(LUAN Haiyang，FAN Yingfang，WANG Dawei，et al. Study on the flexural behavior of the CFRP-reinforced concrete beam with fractal theory[J] Engineering Mechanics，2015，32(4)：160–168.(in Chinese))
[18] CARRILLO J，AVILA W. Assessment of seismic damage of thin and lightly reinforced concrete walls using fractal dimension of cracking[J]. Earthquake Engineering and Structural Dynamics，2017，46(4)：661–675.
[19] LI X J，LIN X D，ZHU H H，et al. Condition assessment of shield tunnel using a new indicator：The tunnel serviceability index[J]. Tunnelling and Underground Space Technology，2017，67：98–106.
[20] 朱合华，李晓军，林晓东. 基础设施智慧服务系统(iS3)及其应用[J]. 土木工程学报，2018，51(1)：1–12.(ZHU Hehua，LI Xiaojun，LIN Xiaodong. Infrastructure smart service system(iS3) and its application[J]. China Civil Engineering Journal，2018，51(1)：1–12.(in Chinese))
[21] 吴江滨. 浅谈隧道病害分级技术[J]. 岩石力学与工程学报，2003，22(增1)：2 422–2 425.(WU Jiangbin. Discussion about the technique of tunnel disease classification[J] Chinese Journal of Rock Mechanics and Engineering，2003，22(Supp.1)：2 422–2 425.(in Chinese))
[22] 罗鑫，夏才初. 隧道病害分级的现状及问题[J]. 地下空间与工程学报，2006，2(5)：877–880.(LUO Xin，XIA Caichu. Current situation and problems of classification of tunnel diseases[J] Chinese Journal of Underground Space and Engineering，2006，2(5)：877–880.(in Chinese))
[23] 李宇杰，王梦恕，徐会杰，等. 地铁矿山法区间隧道病害分级标准及补强对策[J]. 都市快轨交通，2014，27(1)：86–89.(LI Yujie，WANG Mengshu，XU Huijie，et al. Study on the damage classification criterion and reinforcement strategies of mine construction subway[J] Urban Rapid Rail Transit，2014，27(1)：86–89.(in Chinese))
[24] 北京市地方标准编写组. DB11/T 718－2016城市轨道交通设施养护维修技术规范[S]. 北京：北京市质量技术监督局，2016.(The Professional Standards Compilation Group of Beijing City. DB11/T 718－2016 Code for maintenance of urban rail transit facility[S]. Beijing：Beijing Municipal Bureau of Quality and Technical Supervision，2016.(in Chinese))
[25] 罗建春，高菊如. 既有线铁路隧道病害分级方法与评价体系研究[J]. 现代隧道技术，2016，53(6)：12–17.(LUO Jianchun，GAO Juru. A defect classification and evaluation system for existing railway tunnels[J]. Modern Tunnel Technology，2016，53(6)：12–17.(in Chinese))
[26] 中华人民共和国行业标准编写组. CJJ/T 289－2018城市轨道交通隧道结构养护技术标准[S]. 北京：中国建筑出版社，2018.(The Professional Standards Compilation Group of People¢s Republic of China. CJJ/T 289－2018 Technical standard for maintenance of tunnel structures in urban rail transit[S]. Beijing：China Architecture and Building Press，2018.(in Chinese))
[27] ARTHUR D，VASSILVITSKII S. K-means++：The advantages of careful seeding[C]// Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms. New Orleans，USA：Society for Industrial and Applied Mathematics，2007：1 027–1 035.
[28] KAUFMAN L，ROUSSEEUW P J. Finding groups in data：An introduction to cluster analysis[M]. Hoboken，N.J.：John Wiley and Sons，Inc.，1990：342.
[29] 邵华，黄宏伟，张东明，等. 突发堆载引起软土地铁盾构隧道大变形整治研究[J]. 岩土工程学报，2016，38(6)：1 036–1 043. (SHAO Hua，HUANG Hongwei，ZHANG Dongming，et al. Case study on repair work for excessively deformed shield tunnel under accidental surface surcharge in soft clay[J]. Chinese Journal of Geotechnical Engineering，2016，38(6)：1 036–1 043.(in Chinese))
[30] HUANG H W，SHAO H，ZHANG D M，et al. Deformational responses of operated shield tunnel to extreme surcharge：A case study[J]. Structure and Infrastructure Engineering，2017，13(3)：345–360.
[31] 吴俊，袁大军. 大连极硬岩地层复合盾构刀具磨损的分析与预测[J]. 土木工程学报，2015，48(增1)：250–255.(WU Jun，YUAN Dajun. Analysis and prediction on composite shield cutters wear in extremely hard rock in Dalian metro[J]. China Civil Engineering Journal，2015，48(Supp.1)：250–255.(in Chinese))
[32] 中华人民共和国行业标准编写组. DG/TJ08–2123－2013盾构法隧道结构服役性能鉴定规范[S]. 上海：上海市建筑建材业市场管理总站，2013.(The Professional Standards Compilation Group of People¢s Republic of China. DG/TJ08–2123－2013 Code for structural appraisal of shield tunnel[S]. Shanghai：Shanghai Market Management Center for Construction and Materials，2013.(in Chinese))
[33] 林晓东. 盾构隧道服役性能指标(TSI)评估预测模型与应用研究[博士学位论文][D]. 上海：同济大学，2018.(LIN Xiaodong. Study on evaluation，prediction and application of shield tunnel serviceability index[Ph. D. Thesis][D]. Shanghai：Tongji University，2018.(in Chinese))