As-built modeling of piping system from terrestrial laser-scanned point clouds using normal-based region growing

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.