ABSTRACT
This chapter illustrates the suitability of advanced Bayesian techniques to extract the modal properties of vibrating structures and stochastic model updating. A technique for variable separation is presented so that the interaction between spectrum variables (e.g. frequency, damping ratio as well as the amplitude of modal excitation and prediction error) and spatial variables (e.g. mode shape components) can be decoupled completely. Based on the uncertainties of the modal properties, a novel Bayesian methodology is developed for structural stochastic model updating by incorporating the local mode shape components identified from different clusters automatically without prior assembling. The suitability and potential of the presented methodology is illustrated using a numerical example and an experimental case study.
