Prediction of state aviation fuel unit in the GTE limited information

Authors

  • Dmitriy Aleksandrovich Smyshlyaev
  • Anas Saidovich Gishvarov
  • Anas Saidovich Gishvarov

Keywords:

mathematical model; vibration load; an artificial neural network; working hours; multilayer perseptoron; Fast Fourier Transform; multiple regression.

Abstract

Solve the problem of forecasting the technical state of the fuel assembly aircraft gas turbine engine (GTE) using a mathematical model relating the output parameters that characterize the state of the unit, with its vibration load. 

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Published

2018-25-10

Issue

Vol. 18 No. 4 (65) (2014): Вестник УГАТУ

Section

AIRCRAFT AND ROCKET AND SPACE TECHNOLOGY