Continuous wavelet transform for modal parameter identification of flutter data

This paper implements modal parameter identification of the wing response signal under environmental excitation using continuous wavelet transform. A suitable wavelet basis function was selected based on the characteristics of flutter data to achieve good time-frequency analysis of the data. The endpoint effect was effectively suppressed by using support vector machine regression. By employing the Crazy Climbing algorithm to identify the wavelet ridges and obtain the wavelet cross section, the modal damping of flutter data was identified. Finally, this method was applied to wind tunnel test data of a 3D printed wing to identify its modal parameters, and the results were compared with numerical simulation data, which validated the reliability of Continuous Wavelet Transform-Based Analysis of Aircraft Wing Flutter Data (CWT) in identifying modal parameters of wing flutter data under environmental excitation.