期刊
AUTOMATION IN CONSTRUCTION
卷 72, 期 -, 页码 102-114出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.autcon.2016.08.035
关键词
Building information modeling (BIM); Dimensional quality assurance (DQA); Full-scale test; Geometry matching; Laser scanning; Precast concrete elements
资金
- Smart Civil Infrastructure Research Program - Ministry of Land, Infrastructure (MOLIT) and Transport of the Korea Government [13SCIPA01]
- Korea Agency for Infrastructure Technology Advancement (KAIA)
- School of Engineering of the Hong Kong University of Science and Technology (HKUST)
- Korea Advanced Institute of Science and Technology (KAIST)
- HKUST
- Korea Agency for Infrastructure Technology Advancement (KAIA) [66000] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This study presents a quality inspection technique for full-scale precast concrete elements using laser scanning and building information modeling (BIM). In today's construction industry, there is an increasing demand for modularization of prefabricated components and control of their dimensional quality during the fabrication and assembly stages. To meet these needs, this study develops a non-contact dimensional quality assurance (DQA) technique that automatically and precisely assesses the key quality criteria of full-scale precast concrete elements. First, a new coordinate transformation algorithm is developed taking into account the scales and complexities of real precast slabs so that the DQA technique can be fully automated. Second, a geometry matching method based on the Principal Component Analysis (PCA), which relates the as-built model constructed from the point cloud data to the corresponding as-designed BIM model, is utilized for precise dimension estimations of the actual precast slab. Third, an edge and corner extraction algorithm is advanced to tackle issues encountered in unexpected conditions, i.e. large incident angles and external steel bars being located near the edge of precast concrete elements. Lastly, a BIM-assisted storage and delivery approach for the obtained DQA data is proposed so that all relevant project stakeholders can share and update DQA data through the manufacture and assembly stages of the project. The applicability of the proposed DQA technique is validated through field tests on two full-scale precast slabs, and the associated implementation issues are discussed. Field test results reveal that the proposed DQA technique can achieve a measurement accuracy of around 3.0 mm for dimension and position estimations. (C) 2016 Elsevier B.V. All rights reserved.
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