ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-3, 141-146, 2012
© Author(s) 2012. This work is distributed
under the Creative Commons Attribution 3.0 License.
20 Jul 2012
W. T. Mapurisa1 and G. Sithole2 1South African National Space Agency, Pretoria, South Africa
2Dept. of Geomatics, Architecture and the Built Environment, University of Cape Town, South Africa
Keywords: Segmentation, detection, Modelling, LIDAR, Point Cloud Abstract. As-Built surveys of buildings and installations have received greater attention in recent years. An example is the 3D digital reconstruction of existing piping installations at chemical plants for plant maintenance, upgrades and safety standard concerns. This paper is directed at the reconstruction of piping installations with particular emphasis on the detection of deformities in pipes. Reconstruction begins with the automatic detection of individual piping elements which requires a prior segmentation. For segmentation, the profile intersection technique is used. Surfaces are considered as a network of intersecting curves as opposed to surface patches. Recreating such curves on a point set, and intersecting them, segments are identified. The entire scan is partitioned into a series of scan planes referred to as profiles. Points are then connected in each profile based on the surface they represent forming line segments. The line segments, which represent curves, are then intersected to identify segments. For pipes, line segments are elliptical. The centre of an ellipse lies on the pipes’ axis and the semi minor axis is equivalent to the radius of the pipe. Therefore together the centres and semi minor axis are used to describe the position, orientation, size and radius of a pipe. For deformed pipes, the line segments deviate from the elliptical shape. By identifying deviations of the line segments from the elliptical shape deformations are identified. The algorithm allows for cylinders, spheres, cones and tori to be detected including deformities in their shape. Experimental results show the effectiveness of the algorithm.
Conference paper (PDF, 1064 KB)

Citation: Mapurisa, W. T. and Sithole, G.: DEFORMATION DETECTION IN PIPING INSTALLATIONS USING PROFILING TECHNIQUES, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-3, 141-146, doi:10.5194/isprsannals-I-3-141-2012, 2012.

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