Feasibility Study of Drone-Based 3-D Measurement of Defects in Concrete Structures

Abstract

Recognition of defects in concrete structures, identification of cracks, concrete spalling, or other geometrical defects are important tools for structural damage detection. Defects in structures can include cracks, but also missing parts, due to the wear caused by weather or aging phenomena. These last types of defects in structures can be identified using red-green-blue (RGB) cameras, but the level of damage could be difficult to evaluate with 2-D images. In this sense, the application of 3-D reconstruction techniques can be helpful to determine the 3-D dimensions of spalling, swelling of concrete or the presence of visible steel parts of reinforced concrete. The use of drones for this type of measurement is very attractive for reducing the costs and time of measurement campaigns. However, the lack of accurate trajectory information and the vibrations affect the accuracy of 3-D measurements. In this article, a metrological characterization of measurement systems for the evaluation and recognition of defects in concrete structures is presented, starting from the acquisition of 3-D point clouds by low-cost time-of-flight (ToF) sensors, placed on drones. To evaluate the uncertainty of these systems, a mock-up with realistic defects was developed and characterized using a reference 3-D scanner. The 3-D reconstructions obtained via the selected sensors were used to evaluate the discrepancies of the 3-D shape compared to a ground truth model and the uncertainty of the selected scanners. The results show that, for all the defects tested, the standard deviation of the discrepancies between the defect reconstructed using the drone and the ground truth is below 2.5 mm.