AUTOMATIC THICKNESS AND VOLUME ESTIMATION OF SPRAYED CONCRETE ON ANCHORED RETAINING WALLS FROM TERRESTRIAL LIDAR DATA
- 1Dept. of Natural Resources and Environmental Engineering, University of Vigo, Maxwell s/n, 36310, Vigo, Spain
- 2Ingeniería Insitu, building CITEXVI, Local 23, R/ Fonte das Abelleiras s/n, 36310, Vigo, Spain
- 3Defense University Center at the Spanish Naval Academy, University of Vigo, Plaza de España s/n, 36920, Marín, Spain
- 4Dept. of Materials Engineering, Applied Mechanics & Construction, University of Vigo, Torrecedeira 86, 36208 Vigo, Spain
Keywords: LiDAR, point cloud, retaining wall, rock bolts, shotcrete, feature extraction, volume calculation
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.