Journal of Computational Design and Engineering

Society for Computational Design and Engineering (한국CDE학회)
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As-built modeling of piping system from terrestrial laser-scanned point clouds using normal-based region growing

  • Kawashima, Kazuaki (Graduate School of Information Science and Technology, Hokkaido University) ;
  • Kanai, Satoshi (Graduate School of Information Science and Technology, Hokkaido University) ;
  • Date, Hiroaki (Graduate School of Information Science and Technology, Hokkaido University)
  • Received : 2013.09.18
  • Accepted : 2013.11.01
  • Published : 2014.01.01
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Abstract

Recently, renovations of plant equipment have been more frequent because of the shortened lifespans of the products, and as-built models from large-scale laser-scanned data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing plant has an enormous amount of points, captures intricate objects, and includes a high noise level, so the manual reconstruction of a 3D model is very time-consuming and costly. Among plant equipment, piping systems account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which could automatically recognize a piping system from the terrestrial laser-scanned data of plant equipment. The straight portion of pipes, connecting parts, and connection relationship of the piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations of pipes, including straight pipes, elbows, and junctions. Tracing the axes of a piping system enables the recognition of the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fully automatic way. The algorithm was applied to large-scale scanned data of an oil rig and a chemical plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, and junctions, respectively.

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