Structural health monitoring and inspection of dams based on unmanned aerial vehicles photogrammetry with 3D model reconstruction

Abstract

Ensuring dam safety requires continuous monitoring to detect structural anomalies such as cracks, displacements, and seepage. This study explores aerial surveys using Unmanned Aerial Vehicles combined with open-source software to enhance dam monitoring capabilities. The methodology enables efficient inspections in difficult-access areas and supports early identification of potential failure indicators. High-resolution aerial imagery was processed to generate detailed three-dimensional representations including point clouds, orthophotos, and textured models. A novel Ground Control Points Finder tool was developed to automate identification and georeferencing, significantly improving spatial accuracy and survey efficiency. The study systematically presents fourteen failure modes detectable through aerial mapping, including piping, hydraulic fracturing, foundation instability, and freeboard loss, with their characteristic surface manifestations. The approach was validated using Lapa Dam as a case study through two aerial surveys conducted ten months apart. Analysis using open-source software successfully identified surface deformations, settlements, and vegetation changes, demonstrating the methodology’s effectiveness in detecting structural anomalies associated with potential failure modes. The results confirm that integrating aerial surveys with open-source processing tools offers a low-cost solution to complement dam safety assessments. The approach improves early detection of various failure modes, reduces inspector exposure to hazardous conditions, and supports informed decisions in monitoring embankment dams through accessible technology.