Final Report Summary - AEROTEST (Remote Sensing Technique for Aeroengine Emission Certification and Monitoring) The aim of the AEROTEST project was to achieve a high level of confidence in aircraft engine emission measurements with a view of using the remote optical technique for engine certification. Aircraft engine industry stressed the need for a measurement method compatible with cost effectiveness, short-term implementation, fast availability of results and accuracy, meeting International Civil Aviation Organization (ICAO) emission certification needs, advantages that can be reached with optical methods.Two main objectives were defined to meet the engine manufacturers needs:- first and major objective: address the standardisation issues, the ultimate aim being to promote non intrusive techniques to ICAO for engine emission certification, following a complete quality assurance and quality control approach, and developing procedures for calibration, set up and operation;- second objective: to develop validated techniques for gas turbine monitoring, using emission data to be used routinely by engine manufacturers, both in development test programmes and for engine health monitoring (EHM).It has been demonstrated in previous European projects, Aerojet and Aerojet II, that non intrusive techniques like Fourier transform infrared spectroscopy (FTIR) and laser induced incandescence (LII) are relevant to aero-engine exhaust gases measurement. These methods have been compared with intrusive methods within AEROJET II. This success has opened the path for their standardisation.The pollutants addressed in the project were CO2, CO, NO, NO2, UHC and soot particles. All gases have been measured with a single remote sensing system, composed of a FTIR spectrometer linked to a 'White' mirror system, and soot particles have been detected with the laser induced incandescence (LII) equipment. The FTIR measurement principle is based on a passive collect of a high resolution infrared spectrum; each line emitted by a species is function of the gas temperature as well as of the species concentration; an accurate analyse of the lines shape and intensity enables to retrieve the concentration of gases present in the exhausts; During AEROTEST project, the FTIR equipment has been adapted, allowing to perform optical measurement of a good quality in a test bed environment. A selection of wavelengths appropriate to each molecule to detect can be made using an automatic rotating optical filter system installed in the FTIR equipment. The collected spectrum is analysed using inversion software, in which the measured spectrum is compared to a simulated spectrum till a good fitting between the two spectra is obtained. The pollutant concentration is then quantified.One of the most promising techniques for in-situ measurements of soot volume fractions is LII. In this technique soot particles are exposed to a rapid nano-second laser pulse that heats the particles to their sublimation temperature (around 4 000 K at atmospheric pressure). The increased thermal emission from the particles can readily be detected using photomultiplier tubes (time-resolved) or CCD cameras (imaging). The LII signal collected is proportional to the soot volume fraction. For both FTIR and LII systems, an important work has been done on calibration means. Based on existing standards, on our knowledge on optical systems, and on results from testing campaigns, procedures for calibration and measurement phases have been written by the consortium. Several tests have been done throughout the project on an ATAR 101 jet engine located in the RWTH test bed, allowing to validate the improvements applied to the equipment, and to characterise both LII and FTIR systems in term of accuracy and detection limit. Conventional intrusive measurements (gas analysers, SMPS) have been used for correlation with the optical measurements.Testing campaigns have been done on a SGT300 industrial turbine from SIEMENS and in ROLLS-ROYCE facilities, on small engines (Gnome helicopter, Viper) and on large engines in the 57 test bed, showing the feasibility of using the equipment in different applications. The capability to interrelate engine performance with semi-empirical correlations has been established. A large number of semi-empirical correlations have been identified in open literature and assessed through their application to existing data. It was found that these correlations can predict with a varying degree of accuracy the emitted pollutants when they are applied as published. If however the physical mechanism for the various factors influence is taken into account, it is possible to derive values of the corresponding parameters, such that a specific engine is represented. Thus, a method that can be used to adjust a correlation and develop a set of parameters which gives the best fit to given experimental data has been established and verified.The adapted emissions correlations were used in conjunction to engine performance models to investigate the effects of different engine malfunctions to produced pollutants. a sensitivity study and application of different deterioration scenarios of an industrial single shaft turbine has been carried out. It was found that the accuracy of the employed correlations is of high importance for diagnostic purposes, since it affects the predicted levels of emissions at certain engine operating conditions and health. Thus, criteria for the selection of the adapted emissions correlations to be used for health monitoring purposes were formulated. a study for performance diagnostics enhancement has been also carried out. Extending aero thermodynamic data sets with emissions-derived quantities (e.g. fuel air ratio, airflow rate, and turbine inlet temperature) was shown to improve diagnostic ability. Systematic study for the selection of measurements and diagnostic parameters was carried out and produced information on optimal diagnostic sets. A method for exploiting additional information from emissions, independently from performance quantities was also developed. The method allows an automated recognition of the presence of deviations that could indicate malfunctions, from measurements of emissions distribution in the exhaust plume of an engine. The method is based on pattern recognition through the use of PNN (Probabilistic Neural Networks). A first application of the proposed method on data from a high by pass turbofan engine (Rolls Royce RB211) has shown that it can be an efficient tool for the diagnosis of engine faultsThe final aim of AEROTEST project was the acceptance of non-intrusive methods for gas turbine monitoring. A first step has been reached at the end of the project by a presentation of AEROTEST work and results to the SAE E31 committee (Aircraft Exhaust Emissions Measurement Committee). An Aerospace Information Report (AIR) on non-intrusive emissions measurement has also been produced, outlining technology for discussion, with supporting data. 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