A Method for Deformation Detection and Reconstruction of Shield Tunnel Based on Point Cloud

Detecting deformation and segment assembly quality in the construction or as-built phase of the shield tunnel is crucial and significant to ensure structural safety. The traditional detection methods consume much cost and are prone to errors. This study applies point cloud to develop robust algorithms for the deformation detection and reconstruction of shield tunnels. The methodology initially extracts the tunnel axis, serving as the base for deformation detection and reconstruction. A segmentation algorithm for continuous slice point clouds along the tunnel axis is proposed, and the deformation of the section is evaluated by ellipse fitting. In addition, a novel method of creating a binary image using the unrolled point cloud is adopted based on the extracted tunnel axis, and the segmentation of the segment point cloud is realized via image processing. This process is based on the geometric features of the unrolled point cloud, avoiding tedious parameter adjustment. Finally, a novel segment point cloud fitting method is used to create the as-built model of the tunnel in the BIM platform. To evaluate the performance of the proposed method, we select the shield tunnel case for experimental verification. The results show that (1) using point cloud information can realize an automated solution to complete the tunnel deformation detection task and meet accuracy requirements; and (2) the reconstruction method adopted in this study can realize the visualization of segment dislocation and has better efficiency and accuracy than previous algorithms. The work of this study has a certain guiding significance for the automated detection of the shield tunnel.