Affiliation:
1. Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan
Abstract
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-scamied data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing plant has an enormous amount ofpoints, captures inmcate objects, and includes a high noise level, so the manual reconstmction 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 plant equipment. The straight pomon pipes, connecting parts, and connection relationship ofthe piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations ofpipes, 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 scamied data of an oil rig and a chemical plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, andjunctions, respectively.
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computer Graphics and Computer-Aided Design,Human-Computer Interaction,Engineering (miscellaneous),Modelling and Simulation,Computational Mechanics
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