MATEC Web Conf.
Volume 304, 20199th EASN International Conference on “Innovation in Aviation & Space”
|Number of page(s)||8|
|Section||Propulsion & Engines|
|Published online||17 December 2019|
Estimation of performance parameters of turbine engine components using experimental data in parametric uncertainty conditions
2 Zhukovsky National Aerospace University, “Kharkiv Aviation Institute”, Kharkiv, Ukraine
3 V. N. Karazin Kharkiv National University, Kharkiv, Ukraine
4 Instytut Techniczny Wojsk Lotniczych, Warszawa, Poland
5 Technology Partners Foundation, Warsaw, Poland
Gas Path Analysis and matching turbine engine models to experimental data are inverse problems of mathematical modelling which are characterized by parametric uncertainty. It results from the fact that the number of measured parameters is significantly less than the number of components’ performance parameters needed to describe the real engine. Inthese conditions, even small measurement errors can result in a high variation of results, and obtained efficiency, lossfactors etc. can appear out of the physical range. The paper presents new method for setting a priori information about the engine and its performance in view of fuzzy sets, forming objective functions and scalar convolutions synthesis of these functions to estimate gas-path components’ parameters. The comparison of the proposed approach with traditional methods showed that its main advantage is high stability of estimation in the parametric uncertainty conditions. It reduces scattering, excludes incorrect solutions which do not correspond to a priori assumptions, and also helps to implement the Gas Path Analysis at the limited number of measured parameters.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.