LuFo V DoEfs (Digitally Optimised Engineering for Services): Development of deterioration models for aircraft engine blading
Project leader: Prof. Dr.-Ing. habil. Ronald Mailach
Project member: Dipl.-Ing. Paul Voigt
Scientific cooperation: LuFo V
Financing: BMWi, Rolls-Royce Deutschland Ltd & Co KG
Term: 09/2018 - 12/2020
Over 2000 used high pressure compressor and turbine airfoils were optically scanned as a groundwork for this project. A first step is the parameterization of the geometric variability of the airfoils due to deterioration. For this task, the in house tool Blade2Parameter (B2P) is enhanced. Later on, the deteriorations influence on the performance of the airfoils is investigated by means of a sensitivity study.
Furthermore, the detection of foreign object damages (FOD) on the airfoil surfaces will be automatized. Here, multiple approaches are investigated: the training and applying of an artificial neural network, the calculation and assessment of the surface curvature information and last but not least the approach of the digital stoning to detect surface defects. The most suitable approach to detect FOD is implemented in the newly developed program FOD-Detector.
Scope of this project is the development of comprehensive deterioration models which can be used to investigate correlations between the deterioration or impact characteristics and operational parameters like flight route and flown cycles. The derived correlations can be fed to digital twin models of aircraft engines in order to improve their forecasts. Ultimately, the life cycle cost of aircraft engines is optimised by improving the engine MRO (maintenance, repair and overhaul) as well as the service organisation.