Automated Estimation of Reinforced Precast Concrete Rebar Positions Using Colored Laser Scan Data

Precast concrete elements are widely adopted and the performance of precast structures is relying on the quality of connections between adjacent elements. For reinforced precast concrete elements, rebar positions are important for the overall structural performance, however, they are usually manually inspected. This study develops a technique for automated position estimation of rebars on reinforced precast concrete elements using colored laser scan data. A novel mixed pixel filter is developed to remove mixed pixels from the raw scan data based on both distance and color difference. A one-class classifier is used for extracting rebars from all the data based on both geometric and color features of points. Furthermore, a novel rebar recognition algorithm is developed to recognize individual rebars based on two newly defined metrics. Experiments on two reinforced precast concrete bridge deck panels were conducted and showed that the proposed technique can accurately and efficiently estimate rebar positions.
Publisher
WILEY
Issue Date
2017-09
Language
English
Keywords

PROGRESS MEASUREMENT; BUILDING MODELS; RECOGNITION; LIDAR; RECONSTRUCTION; SUPPORT; SYSTEM; BRIDGE

Citation

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, v.32, no.9, pp.787 - 802

ISSN
1093-9687
DOI
10.1111/mice.12293
URI
http://hdl.handle.net/10203/225460
Appears in Collection
CE-Journal Papers(저널논문)
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