Automated Reconstruction of Parametric BIM for Bridge Based on Terrestrial Laser Scanning Data

Building information modeling (BIM) in industrialized bridge construction is usually performed based on initial design information. Differences exist between the model of the structure and its actual geometric dimensions and features due to the manufacturing, transportation, hoisting, assembly, and load bearing of the structure. These variations affect the construction project handover and facility management. The solutions available at present entail the use of point clouds to reconstruct BIM. However, these solutions still encounter problems, such as the inability to obtain the actual geometric features of a bridge quickly and accurately. Moreover, the created BIM is nonparametric and cannot be dynamically adjusted. This paper proposes a fully automatic method of reconstructing parameterized BIM by using point clouds to address the abovementioned problems. An algorithm for bridge point cloud segmentation is developed; the algorithm can separate the bridge point cloud from the entire scanning scene and segment the unit structure point cloud. Another algorithm for extracting the geometric features of the bridge point cloud is also proposed; this algorithm is effective for partially missing point clouds. The feasibility of the proposed method is evaluated and verified using theoretical and actual bridge point clouds, respectively. The reconstruction quality of BIM is also evaluated visually and quantitatively, and the results show that the reconstructed BIM is accurate and reliable.

Automated summary

This paper proposes a fully automatic method for reconstructing parameterized BIM using point clouds to address the problems encountered in industrialized bridge construction. Algorithms for bridge point cloud segmentation and extraction of geometric features are developed to improve the accuracy and reliability of the reconstructed BIM. The feasibility of the proposed method is evaluated and verified using both theoretical and actual bridge point clouds.