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Monitoring tunnel profile by means of multi-epoch dispersed 3-D LiDAR point clouds

机译:通过多时间分散的3-D LiDAR点云监控隧道轮廓

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摘要

Monitoring tunnel profiles is constantly one of the major routines when long-term tunnel stability is to be evaluated. Among many modern 3-D measurement techniques, the Light Detection and Ranging (LiDAR) technique is capable of collecting detailed spatial data in a fast and automatic manner and is thus a tool that can potentially be implemented for a tunnel monitoring task. However, raw LiDAR datasets usually contain non-specific and dispersive information and thus lack explicit geometric interpretation. In this study, an efficient approach for extracting tunnel profile geometry from raw LiDAR datasets will be presented. By utilizing in situ control features, tunnel profiles at multiple epochs can be automatically generated and expressed in a common datum definition. Then by applying a minimum-distance projection (MDP) algorithm, point correspondences are established so that deformation signals along any given profile can be immediately identified. Based on the results of simulation tests and a real case study of a highway tunnel, it is proven that the LiDAR technique makes possible an efficient and accurate solution for monitoring tunnel profile deformations when the proposed approach is implemented in such a task.
机译:当要评估隧道的长期稳定性时,监视隧道剖面一直是主要的日常工作之一。在许多现代的3D测量技术中,光检测和测距(LiDAR)技术能够以快速,自动的方式收集详细的空间数据,因此是可以潜在地用于隧道监视任务的工具。但是,原始LiDAR数据集通常包含非特定且分散的信息,因此缺乏明确的几何解释。在这项研究中,将提出一种从原始LiDAR数据集中提取隧道剖面几何形状的有效方法。通过利用原位控制功能,可以自动生成多个时期的隧道剖面,并以公共基准定义表示。然后通过应用最小距离投影(MDP)算法,建立点对应关系,以便可以立即识别沿任何给定轮廓的变形信号。基于仿真测试的结果和公路隧道的实际案例研究,证明了当在此任务中实施所提出的方法时,LiDAR技术为监控隧道轮廓变形提供了一种有效而准确的解决方案。

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