3D Reconstruction of a Precast Concrete Bridge for Damage Inspection Using Images from Low-Cost Unmanned Aerial Vehicle

Abstract

Early damage detection in bridges is fundamental to their continued safety, and therefore of utmost importance to the bridge managers and policy makers. The traditional visual inspection which is the common practice for bridge inspection is inefficient, time-consuming, costly, risky, subjective and require the expertise of highly qualified inspectors. Consequently, the use of unmanned aerial systems (UASs) has gained significant attention in the area of bridge inspection. Most UAVs are quite expensive, ranging between $8000-$25000 for the best categories. It however requires the use of UAV equipped with high-cost sensors and longer battery duration, and adequate man power for real-time inspection. The expense of the UAV based inspection makes it unaffordable for many African countries. More recently, 3D models are increasingly deployed for image-based damage identification in bridges and other structures. The 3D models are constructed inform of a digital twin, and allow for computerized inspection using low-cost drones. This paper presents 3D Reconstruction approach for damage inspection and condition assessment of a bridge using images from low-cost unmanned aerial vehicle (UAV). The overall approach was illustrated in form of a case study on a precast concrete bridge. The 3D Reconstructed model of the bridge was virtually inspected to detect damages such as cracks, delamination, concrete deterioration, etc. The results showed that 3D reconstruction using low-cost UAV has great potential in its applications in bridge assessment.