As-built modeling of piping system from terrestrial laser-scanned point clouds using normal-based region growing. Issue 1 (1st January 2014)

• Record Type: Journal Article
• Authors: Kawashima, Kazuaki; Kanai, Satoshi; Date, Hiroaki
• Is Part Of: Journal of computational design and engineering. Volume 1:Issue 1(2014)
• Page Start: 13
• Page End: 26
• Publication Date: 2014-01-01
• Subjects: Laser scanning -- Object recognition -- As-built model -- Piping system -- Point clouds; Engineering -- Data processing -- Periodicals; Computer-aided design -- Periodicals; Computer-aided design; Engineering -- Data processing; Electronic journals; Electronic journals; Periodicals; 620.0042
• DOI: 10.7315/JCDE.2014.002
• Languages: English
• ISSNs: 2288-4300

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.