Modal parameters identification for short data sequences based on stratified sampling and optimism complex Morlet wavelet
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Abstract:
A novel modal parameter identification method based on stratified sampling and optimism complex Morlet wavelet is proposed for short data sequences. Stratified sampling is applied to divide the structure response signal into different layers which called subsamples with different thresholds, and then free decrement response signal of each layer is extracted by random decrement technique. The optimism complex Morlet wavelet transform is applied to identify modal parameter of each layer, and the weight of the layer is also determined based on the sample standard deviation. The modal parameter of the structure can be obtained by weighted calculation.The engineering application shows that the proposed method has the ability to identify modal parameter accurately, decouple lowfrequency intensive modal composition and restrain highfrequency fake modal effectively.
