Inspection of infrastructure under construction has become an active research topic in the past few decades. Due to rising costs and safety concerns of current inspection methods, automated inspection methods are proposed. In this context, this dissertation has developed a framework that uses 3D point cloud data from the bridge under construction and evaluates the design specifications and the strength capacity of the structure while is being built. This study presents a slicing algorithm for automatically evaluating rebar placement using 3D point cloud data. The outcomes of this research provide structural engineering with (i) automatic inspection of reinforcement during construction; (ii) objective quantification of bridge quality with a new strength index associated with the quality of rebar in the field. The broader impact of this research enhances construction safety, lowers economic costs, and reduces ambiguity and subjectivity in the field by providing an objective assessment during construction.
LiDAR; Reinforced concrete; Automatic inspection; Construction inspection; Rebar spacing recognition.
Level of Degree
First Committee Member (Chair)
Second Committee Member
Third Committee Member
Fourth Committee Member
Yuan, Xinxing. "MONITORING OF STRUCTURAL QUALITY UNDER CONSTRUCTION USING 3D POINT CLOUD DATA." (2022). https://digitalrepository.unm.edu/ce_etds/261
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