3D point cloud surface reconstruction algorithm of pantograph slide

Due to the external environment, the discreteness of the laser beam, occlusion, there may be noisy points and outliers in the point cloud data that collected by the 3D laser scanner. These defects can degrade the quality of the point cloud and affect the accuracy of the subsequent three-dimensional point cloud of surface reconstruction. The 5%, 10% and 20% noise was added to the original Bunny point cloud, then the modified Helmholtz algorithm, triangulation algorithm, and Poisson algorithm were used for fitting the surface. The simulation experiment results show that the Poisson algorithm has the best robustness. In this paper, these methods are applied to the collected pantograph point cloud data. The experimental results show that when there is noise in the pantograph point cloud, the Poisson reconstruction algorithm can still better restore the overall distribution of the pantograph slide surface wear.