Automated alignment deviation measurement for precast concrete assembly using point cloud-image fusion

Current Precast concrete (PC) column assembly methods face difficulties in precisely measuring the deviation between rebars and sleeves. This paper proposes an automated assembly alignment deviation measurement (AADM) method that integrates 3D point cloud data with 2D images through complementary algorithms. The proposed method comprises a Virtual Trial Assembly (VTA) module that extract sleeve and rebar assembly points and an Alignment Deviation Measurement (ADM) module that calculate rebar-sleeve deviation using three non-collinear points extracted from VTA module. Deviation measurement experiments were conducted on both a PC column model and a real component. Results show that the proposed AADM method outperforms the investigated benchmark methods, with extraction errors lower than 1 mm and positioning accuracy within 3 mm, both meeting the specification requirements. These findings indicate the proposed method enables precise deviation measurement before and during hoisting, providing assistance for automated alignment of precast concrete columns.