S.V. Zhernakov, R.F. Ravilov

The neural network algorithms of technical condition checking and diagnosis for aeroengine gas-turbine engines oil system are considered. The problem of complex evaluation of GTE rotor thermal condition in the neural network basis is formalized. The engineering technique for applying at the stages of stand and on-board tests of aviation GTE is proposed. The comparative analysis of neural networks and «classical» methods for checking and diagnosing parameters of Aeroengine oil system is presented. The recommendations on applying the developed method in practice are given.