TY - JFULL AU - Pashayev A. and Askerov D. and C. Ardil and Sadiqov R. and Abdullayev P. PY - 2011/2/ TI - Identification of Aircraft Gas Turbine Engine's Temperature Condition T2 - International Journal of Aerospace and Mechanical Engineering SP - 267 EP - 276 VL - 5 SN - 1307-6892 UR - https://publications.waset.org/pdf/6874 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 49, 2011 N2 - Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made. ER -