Publications / 2016 Proceedings of the 33rd ISARC, Auburn, USA

Automatic Reconstruction of As-built BIM from Laser Scanned Data of Precast Concrete Elements for Dimensional Quality Assessment

Q. Wang, J. C. P. Cheng and H. Sohn
Pages 114-122 (2016 Proceedings of the 33rd ISARC, Auburn, USA, ISBN 978-1-5108-2992-3, ISSN 2413-5844)

Precast concrete elements are popularly used in the construction of buildings and infrastructures because they enable higher construction quality, less construction time, and less environmental impact. To ensure the performance of complete precast concrete systems, dimensional quality of individual precast concrete elements must be assessed before they are transported to the construction sites. However, the current quality assessment methods mainly rely on manual inspection with traditional measurement devices, which are inefficient and inaccurate. Besides, the quality assessment results are not well managed. To realize efficient and accurate quality assessment of precast concrete elements and to facilitate the management of quality assessment results, this study proposes a technique which can automatically reconstruct the as-built Building Information Models (BIM) from laser scan data of precast concrete elements for dimensional quality assessment. The proposed technique firstly performs a scan planning to determine the number of scans and the locations of scanners. Then, the pre-processing of scan data removes noisy data and registers multiple scans in a global coordinate system. Afterwards, the as-built geometries of the element are extracted from the registered scan data, and finally the as-built BIM is reconstructed. To validate the proposed technique, a scanning experiment was conducted on a small-scale test specimen. The experimental results demonstrate that the proposed technique can accurately and efficiently create as-built BIM of precast concrete elements.

Keywords: Building Information Models, Laser scanning, As-built BIM reconstruction, Precast concrete elements, Quality assessment