Automatic recognition of piping system from laser scanned point clouds using normal-based region growing
In recent years, renovations of plant equipment have been more frequent, and constructing 3D as-built models of existing plants from large-scale laser scanned data is expected to make rebuilding processes more efficient. However, laser scanned data consists of enormous number of points, captures t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2013-10-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-5-W2/121/2013/isprsannals-II-5-W2-121-2013.pdf |
| Summary: | In recent years, renovations of plant equipment have been more frequent, and constructing 3D as-built models of existing plants from
large-scale laser scanned data is expected to make rebuilding processes more efficient. However, laser scanned data consists of
enormous number of points, captures tangled objects and includes a high noise level, so that the manual reconstruction of a 3D
model is very time-consuming. Among plant equipment, piping systems especially account for the greatest proportion. Therefore, the
purpose of this research was to propose an algorithm which can automatically recognize a piping system from large-scale laser
scanned data of plants. The straight portion of pipes, connecting parts and connection relationship of the piping system can be
automatically recognized. Normal-based region growing enables the extraction of points on the piping system. Eigen analysis of the
normal tensor and cylinder surface fitting allows the algorithm to recognize portions of straight pipes. Tracing the axes of the piping
system and interpolation of the axes can derive connecting parts and connection relationships between elements of the piping system.
The algorithm was applied to large-scale scanned data of an oil rig and a chemical plant. The recognition rate of straight pipes,
elbows, junctions achieved 93%, 88% and 87% respectively. |
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| ISSN: | 2194-9042 2194-9050 |