Automated Intelligent Detection of Truss Geometric Quality Based on BIM and LiDAR

Yakun Zou, Limei Chen, Ting Deng and Yi Tan ()
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Yakun Zou: Sino-Australia Joint Research Center in BIM and Smart Construction, The Shenzhen University
Limei Chen: Sino-Australia Joint Research Center in BIM and Smart Construction, The Shenzhen University
Ting Deng: Sino-Australia Joint Research Center in BIM and Smart Construction, The Shenzhen University
Yi Tan: Sino-Australia Joint Research Center in BIM and Smart Construction, The Shenzhen University

Chapter Chapter 21 in Proceedings of the 28th International Symposium on Advancement of Construction Management and Real Estate, 2024, pp 299-314 from Springer

Abstract: Abstract Nowadays truss structures are commonly utilized in large-span public buildings. In order to ensure the safety of truss structures, it is necessary to regularly check the geometric quality of the structure. However, traditional truss geometric quality inspection still relies on manual work, which is inefficient and costly. Light detection and ranging (LiDAR), considering its efficiency and reliability, is now widely used for geometric quality inspection of structures. This paper proposes an automated intelligent algorithm for truss geometric quality detection. Firstly, the truss structure is separated from the background in the original point cloud through Building Information Model (BIM). Then, the geometric information of the truss is automatically calculated based on key point detection. Finally, the inspection results are obtained by comparing the calculation results with the design information from the BIM. A deformed truss BIM was converted to point clouds to verify the above method in this paper. The experiment results show that the proposed algorithm is effective in automatically processing truss point clouds for truss geometric quality inspection, which can accurately and quickly identify the locations of anomalies in the truss, improving the performance of truss geometric quality inspection.

Keywords: Automation; Truss; Geometric quality; BIM; LiDAR (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-981-97-1949-5_21

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