The aim of project A3 of the Collaborative Research Centre (CRC) 871 is to develop a novel method for automated condition assessment of aircraft engines. The method is based on a combination of numerical simulations, Background Oriented Schlieren (BOS) measurements, and the use of pattern recognition algorithms. The density distribution in the exhaust gas stream of the engine is first measured using the BOS method and then compared with a damage library which was generated numerically through CFD. The automated classification of damage cases can be realized using pattern recognition algorithms. In the third funding period of the CRC, existing reconstruction algorithms used for the calculation of the density distribution in the exhaust gas were improved to increase the accuracy of the BOS measurements. Subsequently, the method was tested experimentally. First, experiments with a model combustion chamber show that 98.5% of all damage cases can be correctly classified by a suitable choice of integral parameters to describe the density distribution in the exhaust gas jet. In a second experimental test, the method was applied to a research engine in order to take realistic impacts into account.