The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components

Abstract

Abstract There is a growing need for tools automating the processing of as-built 3D laser scanned data, and more particularly the comparison of this as-built data with planned works. This paper particularly considers the case of tracking MEP components with circular cross-sections, which essentially include pipes, and some conduits and ducts. Discrepancies between the as-built and as-planned status of pipes, conduit and ductwork result from changes that occur in the field and that are either unnoticed (human error) or not reflected in the 3D model. Previous research has shown that the Hough transform, with judiciously applied domain constraints, is a practical and cost-effective approach to find, recognize and reconstruct cylindrical MEP works within point clouds automatically. Previous research has also shown that “Scan-vs-BIM” systems that are based on the geometric alignment and comparison of as-built laser scans with as-designed BIM models can effectively recognize and identify MEP components as long as they are constructed near their as-planned locations. The research presented in this paper combines the two techniques in a unified approach for more robust automated comparison of as-built and as-planned cylindrical MEP works, thereby providing the basis for automated earned value tracking, automated percent-built-as-planned measures, and assistance for the delivery of as-built BIM models from as-designed ones. The proposed approach and its improved performance are validated using data acquired from an actual construction site. The results are very encouraging and demonstrate the added value of the proposed integrated approach over the rather simpler Scan-vs-BIM system. The two main areas of improved performance are: (1) the enabled recognition and identification of objects that are not built at their as-planned locations; and (2) the consideration for pipe completeness in the pipe recognition and identification metric.