Continuously Vertical Section Abstraction for Deformation Monitoring of Subway Tunnel Based on Terrestrial Point Clouds
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摘要: 提出了一种可应用于变形监测的基于三维激光点云的隧道断面连续截取方法。该方法分为点云拼接、中轴线提取和断面截取。隧道中轴线的提取通过随机采样一致性算法和最小二乘平差算法完成;断面截取过程先基于隧道轴线信息调整隧道姿态,再对隧道数据采取局部曲面拟合进行,其中引用了限制最小二乘算法和随机采样一致性算法。采用RIEGL VE-400获取的地铁隧道点云数据进行了验证。实验证明了本文方法在三维激光扫描技术的应用方面具有一定的实践意义。Abstract: Intelligent total station is the general approach for deformation monitoring of the subway tunnel in current use,but the data size is limited and the labor cost is high during information extracting.A method for vertical section Abstraction based on 3D point cloud is proposed in this paper,which can be applied for deformation monitoring.This approach includes 3 parts:point cloud registration,tunnel central axis calculation and vertical section Abstraction.The central axis of a subway tunnel can be determined through RANSAC algorithm and least square adjustment;the orientation of tunnel firstly has to be adjusted in terms of the central axis,then the data can be fitted by local quadric fitting,which includes constrained least squares algorithm and RANSAC algorithm.The feasibility and accuracy of the proposed method have been verified using the point clouds acquired by RIEGL VZ-400 laser scanner,and the practical significance for applications of 3D laser scanning is reflected to some extent.
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