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

Han, Jen-Yu; Guo, Jenhwa; Jiang, Yi-Syuan

doi:10.1016/j.tust.2012.08.008

Cited by 72 publications

(38 citation statements)

References 15 publications

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“…Deformation monitoring using TLS as discussed above has been applied in the monitoring of several structures such as dams for instance (Alba et al, 2006;Gonzalez Aguilera et al, 2008), tunnels (van Gosliga et al, 2006;Li et al, 2012;Gikas, 2012;Han et al, 2013), viaducts and bridges (Zogg and Ingensand, 2008;Lovas et al, 2008), buildings and towers (Pesci et al, 2013;Schneider 2006), concrete and timber beams (Gordon et al, 2003) and the monitoring of a pipeline as described in Vezocnik et al (2009). TLS has also been applied with success in land deformation monitoring (Wujanz et al, 2013;Teza et al, 2007) and rock slopes as described in Abellan et al (2009).…”

Section: Discussionmentioning

confidence: 99%

“…The method and computational program developed were able to detect deformations using laser scanning data (van Gosliga et al, 2006). Han et al (2013) present a TLS approach which was applied to detect the deformation signals of tunnel profiles. In situ control features were used for the registration of tunnel profiles.…”

Section: Terrestrial Laser Scanning and Deformation Monitoringmentioning

confidence: 99%

“…Monitoring structural deformation is one of the major concerns when dealing with structures such as bridges, tunnels, dams and tall buildings (Han et al, 2013). These engineering structures are examples of structures that are routinely surveyed and monitored for their stability as they are subject to deformation due to factors such as changes of ground water level, tidal phenomena, tectonic phenomena, etc.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

et al. 2016

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Section: Discussionmentioning

confidence: 99%

Section: Terrestrial Laser Scanning and Deformation Monitoringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

et al. 2016

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“…These new technologies have been introduced to measure displacements (Kim et al, 2007) or monitor deformations on tunnel profiles (Han and Jiang, 2013). In (Pejić, 2013), an optimized laserscanning solution is proposed for inspecting the geometry of railway tunnels.…”

Section: Related Workmentioning

confidence: 99%

Accuracy Assessment of a Canal-Tunnel 3d Model by Comparing Photogrammetry and Laserscanning Recording Techniques

Charbonnier¹,

Chavant

Foucher³

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:With recent developments in the field of technology and computer science, conventional methods are being supplanted by laser scanning and digital photogrammetry. These two different surveying techniques generate 3-D models of real world objects or structures. In this paper, we consider the application of terrestrial Laser scanning (TLS) and photogrammetry to the surveying of canal tunnels. The inspection of such structures requires time, safe access, specific processing and professional operators. Therefore, a French partnership proposes to develop a dedicated equipment based on image processing for visual inspection of canal tunnels. A 3D model of the vault and side walls of the tunnel is constructed from images recorded onboard a boat moving inside the tunnel. To assess the accuracy of this photogrammetric model (PM), a reference model is build using static TLS. We here address the problem comparing the resulting point clouds. Difficulties arise because of the highly differentiated acquisition processes, which result in very different point densities. We propose a new tool, designed to compare differences between pairs of point cloud or surfaces (triangulated meshes). Moreover, dealing with huge datasets requires the implementation of appropriate structures and algorithms. Several techniques are presented : point-to-point, cloud-to-cloud and cloud-to-mesh. In addition farthest point resampling, octree structure and Hausdorff distance are adopted and described. Experimental results are shown for a 475 m long canal tunnel located in France.

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“…But the authors manually processed the data; it wasn't automatic. Jen-Yu Han et al [19] generated tunnel profiles at multiple epochs and proposed the minimum-distance projection (MDP) algorithm to establish point correspondences after which deformation signals can be identified. But the authors still extracted the centerline of the tunnel manually.…”

Section: Introductionmentioning

confidence: 99%

Automatic Processing Method for Deformation Monitoring of Circle Tunnels Based on 3D LiDAR Data

Xie¹,

Zhao²,

He³

et al. 2018

Preprint

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Abstract:The application of 3D LiDAR technology has become increasingly extensive in tunnel monitoring due to the large density and high accuracy of the acquired spatial data. The proposed processing method aims at circle tunnels and provides a clear workflow to automatically process raw point data and easily interpretable results to analyze tunnel health state. The proposed automatic processing method employs a series of algorithms to extract point cloud of a single tunnel segment without obvious noise from entire raw tunnel point cloud mainly by three steps: axis acquisition, segments extraction and denoising. Tunnel axis is extracted by fitting boundaries of the tunnel point cloud rejection in plane with RANSAC algorithm. With guidance of axis, the entire preprocessed tunnel point cloud is segmented by equal division to get a section of tunnel point cloud which corresponds to a single tunnel segment. Then the noise in every single point cloud segment is removed by clustering algorithm twice, based on distance and intensity. Finally, clean point clouds of tunnel segments are processed by effective deformation extraction processor to get ovality and three-dimensional deformation nephogram.

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

Cited by 72 publications

References 15 publications

A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

Accuracy Assessment of a Canal-Tunnel 3d Model by Comparing Photogrammetry and Laserscanning Recording Techniques

Automatic Processing Method for Deformation Monitoring of Circle Tunnels Based on 3D LiDAR Data

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