关键词: 频域信息, NARX模型, 系统辨识, 转子系统, 谐波激励

Abstract: The identification of rotor systems via traditional Nonlinear Auto Regressive eXogenous (NARX) models was not feasible due to the absence of random excitation signals. A novel frequency domain model structure and an accompanying frequency sweep identification method were proposed to address this limitation. The system′s time-domain response spectrum during the frequency sweep was captured using Fast Fourier Transform (FFT). Key frequency components′ data were extracted to construct a candidate model term library within the frequency domain model framework. The Orthogonal Forward Regression algorithm,based on the Predictive Residual Sum of Squares (PRESS-based OFR),was employed for model term selection. The proposed modeling method′s effectiveness and applicability were validated using simulation data from a simple rotor system′s mathematical model and actual data from a rotor test rig. The influence of different frequency component information introduced during the frequency sweep on prediction accuracy was also explored. The models derived from frequency domain data were found to accurately predict the system′s time-domain response. The Normalized Mean Square Error (NMSE) of the model predictions was less than 0.3 % for simulation data and further reduced to 0.2 % for experimental data. Additionally,the model incorporating data for the second harmonic (Model 2) demonstrated higher accuracy in predicting the amplitude at the system′s second harmonic compared to the model using only fundamental frequency data (Model 1),with a 95.58 % increase in NMSE at a rotational speed of 339.3 rad/s. The inclusion of rich frequency domain data information in the model term library is advantageous for achieving greater model accuracy,offering a new perspective for the identification of systems subjected to harmonic excitation.

Key words: frequency domain information, NARX model, system identification, rotor system, harmonic excitation