Geotechnical and operational applications for 3-dimensional laser scanning in drill and blast tunnels

Fekete, Stephanie; Diederichs, Mark S.; Lato, Matthew J.

doi:10.1016/j.tust.2010.04.008

Cited by 211 publications

(108 citation statements)

References 9 publications

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“…This model is then updated by new images in order to detect changes and defects. Apart from image-based systems, 3D laser scanners, either time-of-flight, or phase-shift scanners have been tested for tunnel inspection (Fekete et al, 2010;Yoon et al, 2009;Yu et al, 2007;Yuan et al, 2012). The obtained data are processed off line and the 3D structure of the tunnel is reconstructed.…”

Section: Related Workmentioning

confidence: 99%

Autonomous Robotic Inspection in Tunnels

Protopapadakis¹,

Stentoumis²,

Doulamis³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In this paper, an automatic robotic inspector for tunnel assessment is presented. The proposed platform is able to autonomously navigate within the civil infrastructures, grab stereo images and process/analyse them, in order to identify defect types. At first, there is the crack detection via deep learning approaches. Then, a detailed 3D model of the cracked area is created, utilizing photogrammetric methods. Finally, a laser profiling of the tunnel's lining, for a narrow region close to detected crack is performed; allowing for the deduction of potential deformations. The robotic platform consists of an autonomous mobile vehicle; a crane arm, guided by the computer vision-based crack detector, carrying ultrasound sensors, the stereo cameras and the laser scanner. Visual inspection is based on convolutional neural networks, which support the creation of high-level discriminative features for complex non-linear pattern classification. Then, real-time 3D information is accurately calculated and the crack position and orientation is passed to the robotic platform. The entire system has been evaluated in railway and road tunnels, i.e. in Egnatia Highway and London underground infrastructure.

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Section: Related Workmentioning

confidence: 99%

Autonomous Robotic Inspection in Tunnels

Protopapadakis¹,

Stentoumis²,

Doulamis³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…A laser scanner is able to emit and collect thousands of laser beams in a second, and form a dense point cloud that depicts the surface of the object (Klein et al, 2012). Fekete, Diederichs, & Lato (2010) reported their study on applying laser scanning for the as-built modeling and other geotechnical and operational applications in a drill and blast tunnel.…”

Section: Review Of As-built Modeling Techniquesmentioning

confidence: 99%

Real-Time As-Built Tunnel Product Modeling and Visualization by Tracking Tunnel Boring Machines

Wu¹,

Lu²,

Mao³

et al. 2013

Proceedings of the 30th International Symposium on Automation and Robotics in Construction and Mining (ISARC 2013): Building Th

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Tunnel Boring Machines (TBMs) are widely used for tunneling in urban areas because of their high advance rate, precise as-built profile and minimal impact to buildings and traffic on the ground. For a tunnel built by a TBM, there are strict requirements on alignment control and safety. To meet these requirements, it is important to monitor the position of the TBM. In the current practice, the TBM position data, including advance distance and line and level deviations, are reported manually to the managers on a daily basis. To interpret and analyze the position data, the managers also need to refer to various construction drawings. This practice is untimely, inefficient, and error prone for decision making. To improve the current practice, an automatic approach for real-time as-built tunnel product modeling and visualization is proposed, based on TBM position and orientation data autonomously sourced from the Virtual Laser Target Board (VLTB) TBM Guidance System developed at University of Alberta. Related information of the tunnel project, such as the as-designed alignment, soil layers, the ground, existing utility lines, is also visualized together with the model of the as-built tunnel. The modeling algorithm is presented step by step. Its application in a real-life drainage tunnel project is discussed and limitations are also identified.

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“…This interest is surely due to the key advantages of Terrestrial Laser Scanning (TLS), which acquires high density, high accuracy point clouds in a short time span. In particular, TLS can remotely obtain extensive information on rock slopes, excavations, underground environments and data of inaccessible outcrops without costly delays or disruption of the construction workflow and is therefore a suitable instrument for the abovementioned task (Abellán et al, 2014;Fekete et al, 2010). However, TLS data processing is time consuming and it is obvious that introducing more automated processes towards a change detection, e.g., to detect the amount of sprayed concrete on the scene, will minimize the manual work and save time and money.…”

Section: Introductionmentioning

confidence: 99%

Automatic Thickness and Volume Estimation of Sprayed Concrete on Anchored Retaining Walls From Terrestrial Lidar Data

Martínez-Sánchez

Puente

González-Jorge

et al. 2016

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

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ABSTRACT:When ground conditions are weak, particularly in free formed tunnel linings or retaining walls, sprayed concrete can be applied on the exposed surfaces immediately after excavation for shotcreting rock outcrops. In these situations, shotcrete is normally applied conjointly with rock bolts and mesh, thereby supporting the loose material that causes many of the small ground falls. On the other hand, contractors want to determine the thickness and volume of sprayed concrete for both technical and economic reasons: to guarantee their structural strength but also, to not deliver excess material that they will not be paid for. In this paper, we first introduce a terrestrial LiDAR-based method for the automatic detection of rock bolts, as typically used in anchored retaining walls. These ground support elements are segmented based on their geometry and they will serve as control points for the co-registration of two successive scans, before and after shotcreting. Then we compare both point clouds to estimate the sprayed concrete thickness and the expending volume on the wall. This novel methodology is demonstrated on repeated scan data from a retaining wall in the city of Vigo (Spain), resulting in a rock bolts detection rate of 91%, that permits to obtain a detailed information of the thickness and calculate a total volume of 3597 litres of concrete. These results have verified the effectiveness of the developed approach by increasing productivity and improving previous empirical proposals for real time thickness estimation.

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Geotechnical and operational applications for 3-dimensional laser scanning in drill and blast tunnels

Cited by 211 publications

References 9 publications

Autonomous Robotic Inspection in Tunnels

Autonomous Robotic Inspection in Tunnels

Real-Time As-Built Tunnel Product Modeling and Visualization by Tracking Tunnel Boring Machines

Automatic Thickness and Volume Estimation of Sprayed Concrete on Anchored Retaining Walls From Terrestrial Lidar Data

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