A comparison of correlation technique and random decrement algorithm for modal identification from nonstationary ambient vibration data only

Modal identification from response data only is studied for structural systems under nonstationary ambient vibration. By assuming the ambient excitation to be nonstationary white noise in the form of a product model and introducing a technique of curve fitting, the practical problem of insufficient data samples available for evaluating nonstationary correlation functions or randomdec signatures can be approximately resolved by first extracting the amplitude-modulating function from the response and then transforming the nonstationary responses into stationary ones. Modal-parameter identification can then be performed using the Ibrahim time-domain method in conjunction with the correlation technique and random decrement algorithm, respectively. A comparison of correlation technique and random decrement algorithm is demonstrated through numerical simulations, which also confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data.