Automatic Bayesian modal identification method for structures based on blind source separation

Abstract

ABSTRACT An automatic Bayesian modal identification method is proposed using the blind source separation (BSS) technique. The determination of resonant frequency bands, which is the initial step of the fast Bayesian FFT (fast Fourier transform) method, requires human intervention and hence, is labour-intensive and subjective. To automate the determination of resonant frequency bands, the BSS technique is introduced here for band selection process. After estimating the modal responses from measured data, the hump criterion curves are drawn to sharpen the border of the resonant humps. And the frequency bands can thus be determined automatically by locating the resonant humps with a peak picking algorithm. The proposed method was validated with a simulated 6- degree-of-freedom spring-mass model, a simulated 4-story benchmark model, the Heritage Court Tower in Vancouver, Canada. The robust identification results indicate that the proposed method can identify automatically and accurately the physical modes together with their uncertainty.