Fundamental study on delamination detection in concrete structures using point clouds

Abstract

The use of point cloud data for inspecting concrete structures is growing. However, for structures like tunnels and bridges, it has been difficult to capture high-precision, high-density data from the ground, making it hard to detect small-scale damage. Recently, UAVs have enabled close-up image capture, allowing for more accurate and dense point cloud generation. This study explores the possibility of detecting internal damage such as delamination and debonding by analyzing point clouds and 3D mesh data created from UAV video using SfM and MVS techniques.The results show that combining depth analysis and mesh normal vector analysis-based on point clouds cleaned with an improved RANSAC method-can help identify areas of damage.