Fully automated generation of parametric BIM for MEP scenes based on terrestrial laser scanning data

Abstract

As-built building information modeling (BIM) has gained much attention in mechanical, electrical and plumbing (MEP) systems for better facility management. To create as-built BIMs, laser scanning technology is widely used to collect raw data due to its high measurement speed and accuracy. Currently, as-built models are mostly drawn by experienced personnel in BIM modeling software with point cloud data as reference, which is labor intensive and time consuming. This study presents a fully automated approach to converting terrestrial laser scanning data to well-connected as-built BIMs for MEP scenes. According to the geometry complexity, MEP components are divided into regular shaped components and irregular shaped components. A 2D to 3D analysis framework is developed to detect objects and extract accurate geometry information for the two categories of MEP components. Firstly, the MEP scene is divided into slices on which rough geometry information of components' cross sections is extracted. Then, the extracted information on different slices is integrated and analyzed in 3D space to verify the existence of MEP components and obtain refined geometry information used for modeling. Following the detection stage, an MEP network construction approach is developed for MEP components connection and position fine-tuning. Finally, the extracted geometry information and connection relationships are imported into Dynamo to automatically generate the parametric BIM model. To validate the feasibility of the proposed technique, experiments were conducted with point clouds acquired from three scenes in Hong Kong. A comprehensive assessment is presented to evaluate the as-built model quality with three indices: retrieval rate, geometry parameter accuracy and deviation from point clouds to as-built model. The experiment results show that the proposed technique could successfully transform laser scanning data of MEP scenes to as-built BIMs with sufficient accuracy for facility management purpose.