Point cloud modelling based on the tunnel axis and block estimation for monitoring the Badaling Tunnel, China

Recent years have witnessed a growing investigation of terrestrial laser scanning (TLS) for monitoring the deformation of tunnels. TLS provides the ability to obtain a more accurate and complete description of the tunnel surfaces, allowing the determination of the mechanism and magnitude of tunnel deformation, because the entire surface of the tunnel is more concretely modelled rather than being represented by a number of points. This paper models and analyses the point clouds from TLS to detect the possible deformation of a newly built tunnel. In the application of monitoring the Badaling Tunnel for the Winter Olympics 2020 in Beijing, China, the proposed method includes the following components: the tunnel axis is automatically estimated based on a 3D quadratic form estimation; all of the point clouds are segmented into axis-based blocks; and representative points, solved by a singular value decomposition (SVD) method, are estimated to describe the tunnel surface and establish the correspondence of data between days. The deformations are detected in the form of the distance discrepancies of representative points and verified by the measurements using total station.