With the development of the Chinese transportation industry, the number of bridges has increased significantly, but this results in high pressure of structural maintenance and management. Bridge management system (BMS) is critical for efficient maintenance and ensured safety of bridge structures during long-term operation. Building information modeling (BIM) is an emerging technology with powerful visualization and informatization capability, making it an ideal tool for developing modern management systems. This paper introduces the development of a bridge management system based on the BIM technology. Industry Foundation Classes (IFC) and International Framework for Dictionaries (IFD) standards are studied and extended, and coding rules are proposed for the Chinese bridge industry. Also, a standard structural modeling method is proposed to fast build the bridge BIM model. Web-BIM oriented bridge management is proposed, and portable devices are introduced into the system. Collaborative management is realized for different users. The BIM-based maintenance management system is designed. Finally, a practical BIM-based BMS is established for a long-span cable-stayed bridge in China. This system integrates the BIM with the geographic information system (GIS) and contains information management, inspection management, technical condition evaluation, and enables users to cooperate with each other. Such a BMS could help to improve the management efficiency and ensure its normal operation, providing a useful platform for the maintenance of massive bridges in China.

Due to a higher efficiency and lower cost, prefabricated construction is gradually gaining acceptance within the market. Laser scanning has already been adopted in civil engineering to reconstruct a three-dimensional (3D) model of a structure, to monitor the deformation, and so on. This paper seeks to explore a more automated and accurate quality control process, focusing on the surface defects in prefabricated elements. Laser scanning is adopted for data collection and the 3D reconstruction of the prefabricated components. Besides, a new point cloud preprocessing, involving the $K$ -nearest neighbors (KNN) algorithm, a reduction of the data dimension, and data gridding, is developed to improve the efficiency and accuracy of subsequent algorithms. The Delaunay triangle is used to extract the contour of the point cloud, and then the contour is fitted to further determine the geometric data. Meanwhile, a comprehensive quality control system of prefabricated components based on relevant specifications is proposed, and the quality of prefabricated components is monitored intuitively by the values of indicators. In order to integrate it into the building information modeling (BIM) platform and better store the obtained quality information, the production quality information is designed to be extended to the Industry Foundation Classes (IFC) standard. The proposed approach will be applied to analyze the causes of quality problems in the production process and strengthen the quality control. This study designs a more efficient and accurate quality evaluation process, including data collection, data processing, indicator calculation, and quality evaluation. Moreover, the results moving forward can provide feedback to the cause of the quality issues and further improve the production quality of prefabricated elements.

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.