关键词: 航空发动机, 动态模型, 非线性系统辨识, NARX网络

Abstract: According to the nonlinear dynamic characteristics of aero engine, a dynamic identification model of engine parameters based on NARX neural network is presented. The main idea is based on the nonlinear time series prediction characteristics of NARX network, combined with the steady state and dynamic parameters of the engine parameters, a dynamic model structure of NARX parameters is proposed, which is based on the difference between the partial and steady state. The structure of SP-P identification is designed, and the internal structure parameters of the model are established, and the N1（low rotor speed）, N2（high rotor speed）, and EGT（the temperature at the exit of high-pressure turbine） parameters are established. On the basis of an engine test samples, simulating the accelerating and decelerating N1, N2, EGT dynamic identification models. The simulation results show that the relative error of N2 is less than 0.2%, the relative error of N1 is less than 0.3%, and the relative error of EGT is less than [1℃], which meets the requirements of engine test simulation. Finally, the engine simulation system of the model is applied to the A320 maintenance training device.

Key words: aircraft engine, dynamic model, nonlinear system identification, NARX network