Continuous wavelet transform for modal parameter identification of flutter data

Qingyu Guo; Li Zhou

doi:10.1117/12.2657940

18 April 2023 Continuous wavelet transform for modal parameter identification of flutter data

Qingyu Guo, Li Zhou

Proceedings Volume 12487, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVII; 124871K (2023) https://doi.org/10.1117/12.2657940
Event: SPIE Smart Structures + Nondestructive Evaluation, 2023, Long Beach, California, United States

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Abstract

This paper is based on the continuous wavelet transform to achieve modal parameter identification of the response signal of a wing under environmental excitation. Suitable wavelet basis functions are selected for the characteristics of flutter data to achieve a good time-frequency analysis of flutter data. And the endpoint effect is effectively suppressed by the predictive extension method of support vector machine. The identification of wavelet ridges and the wavelet cross-section are obtained through a crazy creep algorithm to achieve the identification of modal damping in the chattering data. Finally, the method is applied to the wind tunnel test data of a 3d-printed wing to identify its modal parameters, and is compared with its numerical simulation data to verify the reliability of CWT applied to the identification of modal parameters of wing flutter data under environmental excitation.

Citation Download Citation

Qingyu Guo and Li Zhou "Continuous wavelet transform for modal parameter identification of flutter data", Proc. SPIE 12487, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVII, 124871K (18 April 2023); https://doi.org/10.1117/12.2657940

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