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

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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

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	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.

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

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