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23 April 2020 Application of wavelet denoising and a masking signal for flutter boundary prediction
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The most important step of flutter analysis is to predict the flutter boundary of the aircraft to ensure that there will be no flutter in the flight envelope. However, due to the low signal-to-noise ratio and modal density of flutter signal, traditional modal identification methods cannot effectively extract the modal information of the data. Therefore, in order to solve this problem, this paper proposes a method which combines wavelet denoising and a masking signal. Wavelet denoising can effectively reduce the noise interference, and masking signal can effectively alleviate the problem of mode mixing which improves the accuracy of the signal modal identification.
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Chao Bian and Li Zhou "Application of wavelet denoising and a masking signal for flutter boundary prediction", Proc. SPIE 11379, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020, 1137921 (23 April 2020);


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