Displacement analysis of point cloud removed ground collapse effect in SMW by CANUPO machine learning algorithm

Abstract In this paper, a three-dimensional laser scanner was used to monitor the displacement of retaining structures for excavation, including ring beam and reinforced soil mixing wall (SMW) at an open excavation site. Eight scans were taken before after excavation. Three-dimensional point clouds produced with these are registered analyzed determine displacements structures. Cloud Mesh (C2M) method is identify along length depth SMW. The obtained then validated against measured by total station. surface flat so that can be estimated C2M. There collapse deposition on SMW, which affect estimation in cloud comparison. Therefore, CANUPO machine-learning algorithm applied detect areas remove affected deposition. re-estimated based revised clouds. more uniformly changed SMW than results without method, horizontal due calculated.