Modal Identification of Structures with Closely Spaced Modes Based on Improved Empirical Wavelet Transform
Jiaojiao Guo, Guo Wei, Xinyuan Li, Dongping Jin, Fushou Liu
Abstract: Purpose This paper aims to identify the modal parameter of flexible structures with closely spaced modes under ambient excitation based on improved empirical wavelet transform (IEWT) method.Methods A spectral segmentation is performed based on the standardized autoregressive power spectrum of the structural response under ambient excitation. The response signals are decomposed into several Intrinsic Mode Functions (IMFs) with a single frequency via the filter bank, which is constructed using Meyer wavelets, according to the determined segmentation boundary. The IMFs of each order signals can be processed by the random decrement technique to obtain the free response signal of each mode of the structure. Once the free response signals are obtained, the modal information such as natural frequencies, mode shapes and damping ratios of the structure can be identified by using the nonlinear curve fitting method.Results The standardized autoregressive power spectrum allows for effective spectral segmentation of noisy signals with closely spaced mode even the signal-to-noise ratio (SNR) is low. Finally, the feasibility and accuracy of the IEWT method are verified via the numerical simulation of a planer truss and the ground-based experiment of a spatial truss structure.Conclusions The modal information of structure with closely spaced modes under ambient vibration can be effectively identified by using the IEWT approach.
文章链接：https://link.springer.com/article/10.1007/s42417-022-00508-w
