Foreign Object Damage (FOD) to compressor airfoils is a common problem in operating aircraft engines that occurs when objects or debris are sucked into the engines. Especially small surface defects or impact damage (100μm — 300μm depth) can be problematic, as it only becomes noticeable during engine maintenance process, but can have a strong influence on the fatigue strength and service life of individual airfoils. Usually the blade and vane inspection during maintenance is carried out by visual examinations. The inspection findings are individually assessed and as a result the airfoils are accepted, repaired or replaced. This manual inspection process has a significant optimization potential by the means of automatization. This paper presents a novel methodology to automatically detect FOD on compressor airfoils. For the investigation and validation, numerous used compressor blades and vanes were digitized on site with a high precision optical 3D scanning system. A first approach is based on a machine learning algorithm. The idea is the surface segmentation of the digitized airfoil into typical affected areas such as the leading edge (LE), trailing edge (TE), pressure side (PS) or suction side (SS), wherein irregularities during the segmentation can be an indication for FOD. For a second approach, the surface curvature of the airfoil is considered. Locally limited regions with high curvature and concave shapes are sought as an indication for FOD. The required parameters position and depth associated to the individual FOD are calculated in both approaches. The results of both approaches are compared to each other and are validated against the results of a commercial software tool, which uses the approach of digital stoning to create surface defect maps. Furthermore, the results are verified by manually examining the airfoil scans. In the case of relatively small FOD , both approaches generate meaningful results. In terms of larger damages and deformations, both approaches have difficulties detecting it. This problem can be compensated by parametrization of the scanned airfoils with a section based approach using NACA like profile parameters. Unusual changes of specific airfoil parameters (e.g. stagger angle and chord length) over the airfoils height can indicate large FOD or deformation.
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