Modal Identification from Nonstationary Ambient Vibration Data Using Random Decrement Algorithm

Abstract

An effective identification method is developed for the determination of modal parameters of a structure from its measured ambient nonstationary vibration data. It has been shown in a previous paper of the authors that by assuming the ambient excitation to be nonstationary white noise in the form of a product model, the nonstationary response signals can be converted into free-vibration data via the correlation technique. In the present paper, if the ambient excitation can be modeled as a nonstationary white noise in the form of a product model, then the nonstationary cross random decrement signatures of structural response evaluated at any fixed time instant are shown theoretically to be proportional to the nonstationary cross-correlation functions. The practical problem of insufficient data samples available for evaluating nonstationary random decrement 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 technique, which is effective at identifying closely spaced modes. Numerical simulations confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data.