Digital pre-assembly method for steel box segments based on point cloud data
In order to complete manufacturing error inspection and pre-assembly swiftly for prefabricated bridge steel box segments,a novel digital pre-assembly method utilizing 3D laser scanning point cloud models was introduced.At first,3D laser scanning measurement technology was used to create the steel box segments'foot-scale point cloud models,which were then improved using pre-processing techniques to reduce noise and maintain integrity.Subsequently,a rapid boundary extraction algorithm and a planar point cloud projection algorithm was developed,enabling automatic boundary delineation of the 3D foot-scale point cloud models and facilitating dimension reduction of preassembled cross-sectional data.Additionally,an automatic feature corner point extraction algorithm for boundary point clouds was presented,as well as a method for aligning preassembled cross-sections of steel box segments using these feature points.This approach also included new evaluation indices to assess the pre-assembly's efficacy.Finally,the digital pre-assembly method's feasibility and accuracy were demonstrated,through method comparison and accuracy verification,using simulated point clouds from steel box segments of arch ribs in a specific tied arch bridge,and on-site scanning experiments validated the method's practicality.The results show that this method achieves efficient and high-precision virtual pre-assembly of steel box segments with a maximum manufacturing dimension error of 0.02 mm,outperforming traditional methods under simulated conditions.Pre-assembly accuracy from on-site scanning point cloud data can reach up to 1 cm,with a scanning distance of 10 m and a minimum component size of 8 mm.This method provides a substantial reference and algorithmic support for the digital pre-assembly of prefabricated bridge segments.7 tabs,12 figs,22 refs.
bridge engineeringintelligent constructiondigital pre-assemblylaser point cloudquality inspection
NETL
NSTL
万方数据
