Automated Quality Inspection of Precast Concrete Elements with Irregular Shapes Using Terrestrial Laser Scanner and BIM Technology

Abstract

Nowadays precast concrete elements are widely used in buildings, bridges, and other civil infrastructure facilities because precast elements allow rapid construction and high precision quality control. However, the quality inspection of precast concrete elements primarily relies on manual inspection, which is time consuming and error-prone. Recently, terrestrial laser scanner (TLS) has been used to improve quality inspection. The authors’ group has previously developed an automated dimension estimation technique for precast concrete elements, but its applicability is limited only to precast elements with rectangular shapes. This study advances our previous work so that the dimensions of precast elements with irregular shapes can also be automatically estimated. First, a density-based clustering algorithm is adopted to extract target objects from 3D point cloud data acquired by a TLS. Then, coarse registration is conducted to match each object extracted from the 3D point cloud with the asdesign objects in building information models (BIM) one by one. Thirdly, all point cloud data points are registered onto different surfaces of the as-designed objects in BIM through fine registration. Lastly, the as-built dimensions of the precast concrete element are extracted and compared with the as-design ones in BIM. The effectiveness and accuracy of the developed technique are examined using point cloud data obtained from a laboratory-scale precast concrete bridge deck panel.