operational modal analysis by updating autoregressive model

this paper presents improvements of a multivariable autoregressive (ar) model for applications in operational modal analysis considering simultaneously the temporal response data of multi-channel measurements. the parameters are estimated by using the least squares method via the implementation of the qr factorization. a new noise rate-based factor called the noise rate order factor (nof) is introduced for use in the effective selection of model order and noise rate estimation. for the selection of structural modes, an orderwise criterion called the order modal assurance criterion (omac) is used, based on the correlation of mode shapes computed from two successive orders. specifically, the algorithm is updated with respect to model order from a small value to produce a cost-effective computation. furthermore, the confidence intervals of each natural frequency, damping ratio and mode shapes are also computed and evaluated with respect to model order and noise rate. this method is thus very effective for identifying the modal parameters in case of ambient vibrations dealing with modern output-only modal analysis. simulations and discussions on a steel plate structure are presented, and the experimental results show good agreement with the finite element analysis.