Abstract
The application of Light Detection And Ranging (LiDAR) technology has become increasingly extensive in tunnel structure monitoring. The proposed processing method aims to carry out non-contact monitoring for circular stormwater sewage tunnels and provides an efficient workflow. This allows the automatic processing of raw point data and the acquisition of visualization results to analyze the health state of a tunnel within a short period of time. The proposed processing method employs a series of algorithms to extract the point cloud of a single tunnel segment without obvious noise by main three steps: axis acquisition, segment extraction, and denoising. The tunnel axis is extracted by fitting boundaries of the tunnel point cloud projection in the plane. With the guidance of the axis, the entire preprocessed tunnel point cloud is segmented by equal division to get a section of the tunnel point cloud which corresponds to a single tunnel segment. Then, the noise in every single point cloud segment is removed by clustering the algorithm twice, based on the distance and intensity. Finally, clean point clouds of tunnel segments are processed by an effective deformation extraction processor to determine the ovality and to get a three-dimensional visual deformation nephogram. The proposed method can significantly improve the efficiency of LiDAR data processing and extend the application of LiDAR technology in circular stormwater sewage tunnel monitoring.
Highlights
Full automatic deformation monitoring technology based on Light Detection And Ranging (LiDAR) technology can monitor structures in a non-contact way and is expected to be one of the most important directions in the field of SHM in the future [1,2,3]
Tunnel monitoring based on LiDAR technology has developed rapidly, but insufficient attention has been paid to practical engineering applications, and automation in the point cloud processing stage has apparently been ignored
This article proposed an automatic circular stormwater sewage tunnel point cloud processing method based on LiDAR data that measures the tunnel deformation by its ovality and a three-dimensional visualization nephogram
Summary
Full automatic deformation monitoring technology based on Light Detection And Ranging (LiDAR) technology can monitor structures in a non-contact way and is expected to be one of the most important directions in the field of SHM (structure health monitoring) in the future [1,2,3]. Han and his colleagues [19] improved the approach to be a real 3D approach and estimated the MDP algorithm by directly using the 3D dispersed point clouds, whereas the method is rarely put into use due to the huge computational costs it involves The automation of these LiDAR processing technology has been a research focus, which contributes to the application. Extended the already extensive range of algorithms for automatic or semiautomatic modeling of cylindrical objects These two studies are significant as they made it possible to extend the application of the proposed processing method to irregular section tunnels. Our aim is to achieve full-automation and visualization in LiDAR data processing to significantly improve the efficiency compared to the conventional manual method and to extend the application of LiDAR technology to circular stormwater sewage tunnels during construction and operation
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