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Point Cloud Filtering and Classification Methods for Deeply Buried Irregular Tunnels Based on Geometric Morphology
SHI Ying-en
Journal of Changjiang River Scientific Research Institute ›› 2025, Vol. 42 ›› Issue (12) : 143-150.
PDF(2182 KB)
PDF(2182 KB)
Point Cloud Filtering and Classification Methods for Deeply Buried Irregular Tunnels Based on Geometric Morphology
[Objective] The 3D laser scanning technology is characterized by fast scanning speed, high scanning accuracy, non-contact operation, and minimal influence from the scanning environment, which makes it widely applicable in deep engineering fields. However, high in-situ stress and complex geological structures result in complex tunnel surface morphology and a non-linear actual axis, making the filtering and classification of point clouds for deeply buried tunnels more difficult than those for shallow-buried projects. This study aims to address the recognition and classification of point cloud profile for deeply buried irregular tunnels. [Methods] Based on the spatial morphology of the contour of deeply buried irregular tunnel, we established a two-level filtering method for the point cloud of deeply buried irregular tunnels, and developed a tunnel point cloud classification method based on density-based clustering and spatial position classification. [Results] To verify the effectiveness of the proposed methods, the point cloud data of a 30 m-long deep tunnel excavated by the drilling and blasting method were used as the research object. First, two 1 m-long tunnel segment point clouds were selected for analysis. The filtering effects of the tunnel segment point clouds were analyzed under different segment thicknesses L=0.2, 0.4, 0.6 m and distance thresholds dcritical=0.02, 0.04, 0.06, 0.08,0.1 m. Through comprehensive comparison, the optimal parameters were determined as L=0.2 m and dcritical=0.04 m, which were successfully applied in the filtering of the tunnel point cloud. On this basis, according to the spatial distribution characteristics of the tunnel segment point clouds, the DBSCAN algorithm parameters were set to ε=0.1 m and MinPts=50, which enabled the classification of non-profile point clouds of tunnel segments. [Conclusion] This study focuses on the filtering problem of point clouds in deeply buried tunnels. Based on the spatial geometric features of tunnel point clouds, a two-level filtering and classification method for point clouds of deeply buried tunnels with complex morphology is proposed. Case analysis shows that the proposed method realizes effective filtering and classification of tunnel point clouds with complex morphology, solves the recognition problem of contour point clouds in deeply buried tunnels, and provides reliable technical support for applications of 3D laser scanning point clouds in potential risk area identification, lining thickness detection, spatiotemporal deformation monitoring, and health condition assessment of deeply buried tunnels.
deeply buried tunnel / 3D laser scanning technology / tunnel profile recognition / point cloud filtering / point cloud classification
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Mobile laser scanning technology has the advantage of fast data acquisition,high density and high precision,in addition,it doesn't need to stitch the adjacent station after scanning.Based on mobile laser scanning data,the method of tunnel deformation detection and analysis is studied.Firstly,the spatial central axis of the tunnel is calculated by combining the boundary detection algorithm with random sampling consistency algorithm,and the rotation process of a large number of point clouds in traditional method is eliminated.Secondly,the k-nearest neighbor method is used to compute the buffer of each section to block the point clouds,and the sectional point sets are automatically constructed by projection method,increased the calculation speed of cross sections.Finally,an iterative elliptic fitting method is proposed to denoise the cross sections and fit the sectional curve lines.The precision of the method is verified by comparing with cross section obtained by total station.The proposed method is applied on a section of circular shield tunnel,which is intercepted into cross sections in the interval of 2 m based on the point clouds obtained by tunnel scan,and deformation analysis is performed by comparing the cross sections with theoretical one.
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