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Estimation of Performance Parameters of Turbine Engine Components Using Experimental Data in Parametric Uncertainty Conditions

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SE Ivchenko-Progress, 69068 Zaporizhia, Ukraine
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Aircraft Engine Department, National Aerospace University, “Kharkiv Aviation Institute”, 61070 Kharkiv, Ukraine
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Instytut Techniczny Wojsk Lotniczych (ITWL), ul. Księcia Bolesława 6, 01-494 Warszawa, Poland
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Technology Partners, ul. Pawińskiego 5A, 02-106 Warszawa, Poland
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Author to whom correspondence should be addressed.
Aerospace 2020, 7(1), 6; https://doi.org/10.3390/aerospace7010006
Received: 30 November 2019 / Revised: 3 January 2020 / Accepted: 10 January 2020 / Published: 16 January 2020
(This article belongs to the Special Issue 9th EASN International Conference on Innovation in Aviation & Space)
Zero-dimensional models based on the description of the thermo-gas-dynamic process are widely used in the design of engines and their control and diagnostic systems. The models are subjected to an identification procedure to bring their outputs as close as possible to experimental data and assess engine health. This paper aims to improve the stability of engine model identification when the number of measured parameters is small, and their measurement error is not negligible. The proposed method for the estimation of engine components’ parameters, based on multi-criteria identification, provides stable estimations and their confidence intervals within known measurement errors. A priori information about the engine, its parameters and performance is used directly in the regularized identification procedure. The mathematical basis for this approach is the fuzzy sets theory. Synthesis of objective functions and subsequent scalar convolutions of these functions are used to estimate gas-path components’ parameters. A comparison with traditional methods showed that the main advantage of the proposed approach is the high stability of estimation in the parametric uncertainty conditions. Regularization reduces scattering, excludes incorrect solutions that do not correspond to a priori assumptions and also helps to implement the gas path analysis with a limited number of measured parameters. The method can be used for matching thermodynamic models to experimental data, gas path analysis and adapting dynamic models to the needs of the engine control system. View Full-Text
Keywords: gas turbine engine; performance model; gas path analysis; robust estimation; identification; regularization; fuzzy set; membership function gas turbine engine; performance model; gas path analysis; robust estimation; identification; regularization; fuzzy set; membership function
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Khustochka, O.; Yepifanov, S.; Zelenskyi, R.; Przysowa, R. Estimation of Performance Parameters of Turbine Engine Components Using Experimental Data in Parametric Uncertainty Conditions. Aerospace 2020, 7, 6.

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