Innovative AR and GPR techniques for enhanced modelling and condition assessment of bridge structures

Abstract. The integration of Structural Health Monitoring (SHM) and diagnosis data into Building Information Modelling (BIM) workflows enables engineers to optimize the planning, design, and maintenance of infrastructure projects, fostering a more efficient, sustainable, and data-driven approach throughout the lifecycle of the structures. This contribution presents an innovative approach for the advanced documentation and deterioration assessment of a pedestrian concrete bridge structure. Augmented reality (AR) devices were used to create a deterioration map for SHM, focusing on mapping the observed surface defects. For this purpose, a new “AR Scanner-Labeller” tool was developed for on-site real-time hand scanning and labelling of damages (cracks, detached concrete, etc.). Moreover, a path was developed to assign RTK-GPS coordinates to the geometric labels created. In addition, a terrestrial laser scanning (TLS) was used to generate a 3D model of the whole structure, as a ground truth of the point cloud generated with the AR devices. For more advanced modelling and structural reliability, a Ground-Penetrating Radar (GPR) survey was conducted to know the real condition of the internal structure. A multichannel stepped-frequency GPR system, with modulate frequency range 500 – 3000 MHz, was used to further define the extent and depth of the damage labelled with the AR tool. All this data was finally integrated in a common Building Information Modelling (BIM) model, providing a more realistic scenario of the real condition of the structure and a more reliable analysis. The geometry of the BIM was adopted from the TLS point cloud based on Scan-to-BIM approach. Additionally, the openBIM IFC (Industry Foundation Classes) standard was adopted to ensure interoperability and data exchange. The resulting model demonstrated interoperability by retaining both geometry and semantic information across different BIM platforms. This workflow has shown significant value as a decision-making tool for the maintenance and rehabilitation of civil infrastructure.