Enhanced tunnel construction safety: drill-and-blast construction tunnel deformation detection using LiDAR and cloth simulation filter

作者：Lizhuang Cui, X. Luo, Qian Wang, Gaohang Lv, Jian Liu, Xiao Zhang, Quanyi Xie · 发表于：Measurement Science and Technology · 年份：2025 · DOI：10.1088/1361-6501/ae080b · 被引用次数：4 · 研究领域：3D Surveying and Cultural Heritage、Tunneling and Rock Mechanics、Image Processing and 3D Reconstruction

Abstract The drill-and-blast method remains the primary excavation technique for highway tunnels in mountainous regions, where the shotcrete lining plays a crucial role in the New Austrian Tunneling Method. However, due to blasting disturbances and complex geological conditions, deformation of the shotcrete lining is often unavoidable, posing serious safety risks during construction. Therefore, the necessity of monitoring shotcrete lining deformation and the importance of advanced deformation monitoring methods are self-evident. Traditional single-point monitoring approaches, mainly based on total stations, fail to capture the full-section deformation. In contrast, 3D laser scanning technology (LiDAR) provides new opportunities for tunnel deformation monitoring. A key technical challenge is the automatic extraction of the shotcrete lining from multi-temporal point clouds of tunnel construction scenes and the accurate quantification of its deformation. This study proposes a deformation monitoring framework based on terrestrial laser scanning (TLS) and a cloth simulation filtering (CSF) algorithm. Multi-temporal point cloud data of tunnel construction scenes were acquired using a self-developed TLS system. The CSF algorithm was then employed to accurately extract regions of interest from complex tunnel point clouds, achieving a segmentation accuracy of 96.12%. A deformation monitoring algorithm called GDef was developed to compute the 3D deformation of shotcrete lining, with an...