Borescope inspection is widely used in aircraft engine maintenance because it allows internal turbine components to be examined without full engine disassembly. However, the inspection process remains difficult because image-based observations provide limited geometric context for understanding where a blade defect is located and how it relates to the surrounding surface. Although 3D reconstruction offers a possible route toward more structured inspection support, turbine borescope video is challenging for standard reconstruction pipelines due to restricted viewpoints, weak texture, repetitive blade structures, reflective metallic surfaces, and unstable camera motion.

This thesis presents a defect-aware 3D inspection pipeline for turbine borescope footage. The final method combines fixed region-of-interest cropping, segmented HLOC/COLMAP-based sparse reconstruction, dense mesh generation, and reconstruction-aware transfer of precomputed image-domain defect annotations onto the recovered blade geometry. Rather than treating reconstruction as an isolated end goal, the pipeline uses reconstruction as the geometric basis for defect localization, mesh-level visualization, and inspection-oriented representation.

The final evaluated result shows that a usable defect-aware 3D representation can be produced for a selected turbine inspection sequence. The pipeline yields a sparse reconstruction, dense point cloud, Poisson mesh, defect-colored surface regions, sparse 3D defect support points, and timeline-linked defect outputs. An exploratory user evaluation did not show an overall preference for the 3D view over the current 2D image-based view, but it suggested that 3D geometry may support blade-level spatial interpretation. The current work should therefore be understood as a proof of concept that connects reconstruction, defect evidence, and visualization, while further work is needed to improve robustness, mapping confidence, and practical usability.
... Read more