Online EMD-Wavelet Method for Flutter Test Excited by Atmospheric Turbulence

Abstract

Empirical Mode Decomposition (EMD) and Wavelet method have been widely used in the vibration signal analysis, mainly because of the powerful ability of blind modal separation. In the flutter test, modal identification and modal trajectories tracking online can help to ensure the test safety. However, traditional EMD method is only suitable for offline data batching, which limits its applications to the real-time or near real-time signal analysis. For this reason, according to the online processing requirements of flutter test under the turbulent excitation conditions, combining with wavelet spectrum analysis, an online EMD method based on a sliding window for structural modal identification and flutter boundary prediction (FBP) is proposed in this paper. The corresponding mathematical principles and implementation algorithms are given as well, which decompose the measured signal into the Intrinsic Mode Function (IMF) firstly, and then estimate the modal parameters by using the wavelet power spectrum method. The FBP result is typically obtained online during the test process by using curve fitting and extrapolation of the modal damping. The numerical simulations and test data from a low-speed wind tunnel flutter test are used to verify the effectiveness and engineering feasibility of the proposed method.