Geometric Modeling and Surface-Quality Inspection of Prefabricated Concrete Components Using Sliced Point Clouds

Prefabricated buildings, as the development center of architectural industrialization, will produce a lot of point-cloud data in the process of information detection and management. These point-cloud data can be used for reverse modeling to restore the physical characteristics of prefabricated concrete components, which can provide a basis for prefabricated building informatics. However, traditional point-cloud data processing methods have limitations in the high-precision and high-efficiency restoration of physical entities. To solve this problem, this study assumes the reconstruction of the prefabricated point-cloud geometric model as the research object and builds a prefabricated concrete component model in industry foundation class (IFC) format using the equal-interval segmentation slice mapping method. The geometric surface quality of the prefabricated concrete component was determined by comparing the as-built and as-designed models. This study automated the steps in the data processing process through code and established the framework of a three-dimensional (3D) as-built model reconstruction platform on the assembly construction site. The feasibility of this method was verified using the prefabricated concrete component point-cloud data collected on site. This study solves the problems of easy loss of local details, noise point interference, and manual processing in the quality inspection process of prefabricated buildings. It is conducive to the construction quality management process of prefabricated buildings. The experimental results showed that this method is efficient, the code running time is less than 0.12 s, and the accuracy satisfies standard requirements.

Automated summary

This study addresses the challenges in the quality inspection process of prefabricated buildings by using reverse modeling and point-cloud data processing methods. It establishes a three-dimensional reconstruction platform and verifies the feasibility and efficiency of this method.