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Method of formulating input parameters of neural network for diagnosing gas-turbine engines

    Mykola Kulyk Affiliation
    ; Sergiy Dmitriev Affiliation
    ; Oleksandr Yakushenko Affiliation
    ; Oleksandr Popov Affiliation

Abstract

A method of obtaining test and training data sets has been developed. These sets are intended for training a static neural network to recognise individual and double defects in the air-gas path units of a gas-turbine engine. These data are obtained by using operational process parameters of the air-gas path of a bypass turbofan engine. The method allows sets that can project some changes in the technical conditions of a gas-turbine engine to be received, taking into account errors that occur in the measurement of the gas-dynamic parameters of the air-gas path. The operation of the engine in a wide range of modes should also be taken into account.


First published online: 01 Jul 2013

Keyword : gas-turbine engine, air-gas path, mathematical model of operational process, neural network

How to Cite
Kulyk, M., Dmitriev, S., Yakushenko, O., & Popov, O. (2013). Method of formulating input parameters of neural network for diagnosing gas-turbine engines. Aviation, 17(2), 52-56. https://doi.org/10.3846/16487788.2013.805868
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Jul 1, 2013
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This work is licensed under a Creative Commons Attribution 4.0 International License.