Kulyk, MykolaDmitriev, SergiyYakushenko, OleksandrPopov, Oleksandr2019-04-062019-04-062013-051648-7788http://er.nau.edu.ua/handle/NAU/38320A method of obtaining test and training data sets has been developed. 弻ese sets are intended for train- ing a static neural network to recognise individual and double defects in the air-gas path units of a gas-turbine engine. 弻ese data are obtained by using operational process parameters of the air-gas path of a bypass turbofan engine. 弻e 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. 弻e op- eration of the engine in a wide range of modes should also be taken into accountengas-turbine engineair-gas pathmathematical model of operational processneural networkArticle