Here, aiming at problems of ill Hessian matrix inversion under multi-DOF conditions using Bayesian FFT method and uncertainty evaluation of modal parameters, Bayesian TDD-FFT (time domain decomposition-fast Fourier transform) modal identification method was proposed.Firstly, Bayesian TDD method was used to convert a multi-DOF signal into SDOF (single degree of freedom) signals.Then, Bayesian FFT method combined with Monte-Carlo one was used to acquire the optimal estimation and posterior probability distribution of modal parameters, and do uncertainty analysis.The effectiveness of Bayesian TDD-FFT method was verified with numerical simulation.Finally, the contrastive analysis was performed for the actual measured data at Shanghai center tower.The results showed that the proposed Bayesian TDD-FTT method can be used to acquire the same result accuracy as that of the fast Bayesian FFT one; there is no correlation between frequency and damping, while there is an obvious correlation between excitation spectral density and prediction error one.
Key words
modal identification /
Bayesian TDD-FFT /
Fast Bayesian FFT /
Monte Carlo method /
Shanghai tower
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