Research on tunnel crack detection based on improved DeepLabV3+ and percolation algorithm
CHEN Zhangxin1,2, WANG Gang1*, LI Wenfeng3, LI Ke3, JIANG Song1, LIU Tingfang1
1. School of Civil Engineering, Fujian University of Technology, Fujian 350118, Fuzhou, China; 2. The Fifth Construction Co. Ltd. of CCCC Fouth Harbor Engineering Co. Ltd., Fujian 350008, Fuzhou, China; 3. China Merchants Chongqing Communications Technology Research & Design Institute Co. Ltd., Chongqing 400074, China
Abstract: To address the problem of poor edge localization in deep learning-based methods and low efficiency of traditional percolation algorithms for tunnel crack detection, a two-stage approach that integrates an improved DeepLabV3+ with a skeleton-guided percolation algorithm was proposed. In the first stage, an improved DeepLabV3+ model with a lightweight backbone network, incorporating a CBAM attention module, an optimized ASPP module, and a Dice loss function, was developed to achieve high-recall crack pre-segmentation.In the second stage, a skeleton-guided percolation growth strategy combined with morphological constraints was applied to refine crack edges and measure crack widths. A tunnel crack dataset containing 20 504 pixel-level annotated images was constructed, covering various tunnel lining regions(crown, haunch, sidewall)and surface conditions(dry, wet, stained). Experimental results on this dataset showed that the pre-segmentation module achieved an accuracy of 90.1% and a recall of 86.7%. The improved percolation algorithm increased the precision to 98.5% while maintaining high recall, and improved computational efficiency by approximately 20 times. Engineering validation demonstrated a detection rate exceeding 84% for cracks wider than 0.1 mm, with a mean absolute error of less than 0.3 mm.The proposed method effectively balanced detection accuracy and computational efficiency, providing a feasible solution for automated tunnel lining crack detection.
陈彰昕,王刚,李文锋,李科,江松,刘廷方. 基于改进DeepLabV3+和渗流算法的隧道裂缝检测研究[J]. 隧道与地下工程灾害防治, 2026, 8(2): 67-78.
CHEN Zhangxin, WANG Gang, LI Wenfeng, LI Ke, JIANG Song, LIU Tingfang. Research on tunnel crack detection based on improved DeepLabV3+ and percolation algorithm. Hazard Control in Tunnelling and Underground Engineering, 2026, 8(2): 67-78.
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