Quality Inspection Method for Steel Reinforcement Skeleton Based on Computer Point Cloud Automatic Generation

The steel skeleton plays an important supporting role in the building structure, and it is very important to ensure the stability and safety of the building. In order to improve the efficiency of steel skeleton quality detection, the technology of point cloud processing and building information model are adopted. First, a high precision registration algorithm based on the nearest point is designed to perform point cloud registration. Secondly, based on the precision registration algorithm, the overall point cloud acquisition method is constructed. Finally, the semantic design point cloud automatic-generation algorithm is designed, and the final automatic quality-detection algorithm is constructed based on the overall point cloud acquisition method and semantic design point cloud. The results showed that the time consumption and error of the study design were 25.61s and 3.10 mm, respectively. The overall time of the overall point cloud acquisition method was 7.79 min, while the point cloud preprocessing took about 2.25 min. The detection accuracy and accuracy of the steel bar spacing were 80.34 % and 95.79 %, and the average time-consuming and central processor utilization were 34.78 s and 13.27 %, respectively. The research and design precision registration method, the overall point cloud acquisition method and the steel skeleton quality detection method all have good performance, which can provide technical support for the quality detection of the steel skeleton.