Determination of Damage Geometry and Crack Propagation in Reinforced Concrete Elements Using a Lidar Sensor

This study investigates the applicability of built-in LİDAR sensors in mobile devices for detecting cracks and surface deformations in reinforced concrete structural elements. The experimental work was conducted using Apple devices, and 3D scanning was primarily performed with the Scaniverse application, selected for its user-friendly interface, fixed-resolution output, and reduced data complexity. The point-clouds acquired via Scaniverse were analyzed using CloudCompare software. Various techniques such as cross-sectional extraction, raster analysis, scalar field generation from RGB, and photo-to-model alignment were employed to determine crack geometry and dimensions.

In addition, the study presents a comparative evaluation of multiple LİDAR-based mobile scanning applications, including RealityScan, Canvas, PIX4Dcatch, Sitescape, and Abound. RealityScan and Kanvas yielded relatively accurate results, while PIX4Dcatch and Sitescape exhibited overlayering issues that caused dimensional overestimations despite their high point density. Canvas stood out due to its balanced performance and high processability. A separate sensitivity analysis was conducted using three scanning models: one with spatial measurement targets (SMTs), one with reflective markers, and one without calibration aid. Results showed that SMT-supported models achieved precision within 0.10 mm, while unreferenced scans deviated up to 1.30 mm.

Ultimately, the findings demonstrate that mobile LİDAR scans obtained via platforms like Scaniverse can detect sub-millimeter cracks in concrete elements when paired with proper scaling and analysis procedures. This highlights the potential of mobile devices as accessible and low-cost platforms for structural diagnostics in civil engineering applications.