Dislocation Detection of Shield Tunnel Based on Dense Cross-Sectional Point Clouds

护盾 位错 点云 圆柱 接头(建筑物) 点(几何) 直线(几何图形) 材料科学 块(置换群论) 结构工程 几何学 地质学 计算机科学 工程类 数学 计算机视觉 复合材料 岩石学
作者
Liming Du,Rugang Zhong,Hao Sun,Yong Pang,You Mo
出处
期刊:IEEE Transactions on Intelligent Transportation Systems [Institute of Electrical and Electronics Engineers]
卷期号:23 (11): 22227-22243 被引量:6
标识
DOI:10.1109/tits.2022.3156385
摘要

Tunnel dislocation affects the stability and waterproof of the structure and endangers its service life. This paper presents a dislocation calculation method of shield tunnel based on cross sectional point clouds, which contain three main steps. First, a longitudinal joint detection method is proposed based on the circumferential joints detected by the existing gradient accumulation method. The point clouds containing capping block in each ring are converted into gray image to obtain the center line position of the block, and the longitudinal joints are calculated through combining with the tunnel design data. Second, tunnel appendages are removed quickly through unfolding the tunnel point clouds by cylinder projection and adjusting the parameters of the cloth simulation filtering algorithm. Finally, the circumferential dislocations are calculated by selecting multiple denoised sections on both sides of the joint and clustering the points at each angle. Meanwhile, the longitudinal dislocations are calculated through fitting the segments in each ring separately. Experimental results show that the automatic extraction rate of longitudinal joints is higher than 94%. The point clouds filtering method can quickly separate the very long tunnel lining from the close appendages attached to it. Meanwhile, the RMSE of the repeated circumferential and longitudinal dislocation are evaluated to be 1.56 mm and 0.57 mm respectively. Compared with the existing state of art methods, these values reach 1.75 mm and 0.63 mm. Through the method proposed, the dislocation value at any mileage and any angle of tunnel can be displayed intuitively.
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