关键词:  , 载荷识别；经验模态分解（EMD）；无迹卡尔曼滤波（UKF）；非线性系统

Abstract:  To address the low accuracy of traditional load identification methods caused by structural geometric nonlineari鄄 ties, this paper proposes a load identification method based on empirical mode decomposition (EMD) and the un鄄 scented Kalman filter (UKF). First, the vibration signal is decomposed and its features are extracted using the EMD method. Then, the nonlinear UKF algorithm is applied to identify loads in geometrically nonlinear systems. Based on the GARTEUR standard aircraft model with modified flexible wings, the effectiveness of the proposed method is verified through numerical simulation. The results show that the UKF-based load identification method, combined with EMD-based signal analysis and reconstruction, can significantly improve the load identi鄄 fication accuracy for geometrically nonlinear systems and exhibits strong noise robustness.

Key words:  loadidentification, empirical mode decomposition (EMD), unscented Kalman filter (UKF), nonlinear systems