Tunnel Point Cloud Filtering Method Based on Elliptic Cylindrical Model

Abstract

ABSTRACT:The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points), therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.

Automatic Tunnel Steel Arches Extraction Algorithm Based on 3D LiDAR Point Cloud

“…The papers [11,12,13] specialized in extracting tunnel axis and splicing the tunnel point cloud. Zhu et al [14] extracted the tunnel line by fitting one circular surface. Kang et al [13] extracted the tunnel line by obtaining the middle line parallel to both sides of the tunnel.…”