Phase-based motion analysis for high-precision measurement of bridge deflection using drone imagery

Jiaxing Ye, Shien Ri

Abstract: Recent advancements in unmanned aerial vehicles (drones) technology have significantly broadened the avenue for enhancing the ability to perform precise deflection measurements for bridges using aerial imagery. Utilizing drones for such purposes offers numerous advantages, such as enabling access to hard-to-reach areas, superior cost efficiency, a simplified process in onsite inspection preparation, and the prospective feature of automation. This study delves into the core technique for achieving high-precision deflection measurement of bridges through the analysis of drone imagery data. Unlike conventional studies that typically adopt an approach focusing on image stabilization, we develop a novel method from an orthogonal perspective by reformulating the problem through motion analysis. The proposed method is specifically designed to disentangle the geometrical movements caused by drone motion from the actual structural displacement of the bridge, thereby isolating and accurately capturing the bridge’s deflection characteristics. Extensive validation analysis demonstrated the proficiency of the proposed scheme, showcasing its superior precision, reduced computational cost, and robust performance to environmental factors. The proposed approach has broad applicability for automated inspection of aging and critical infrastructures using drones, addressing sustainability and resilience challenges crucial to global society. © 2024 Elsevier Science. All rights reserved.

External IDs:doi:10.1016/j.ymssp.2025.112433