Stochastic Identification of Damped Beams Using Frequency Response Function Data

Stochastic modelling of mass, stiffness as well as damping in structures, is crucial for an accurate prediction of dynamic response and its variability. This is even more challenging for structures with a high level of damping. A new frequency response function-based stochastic FE model updating approach has been proposed to identify the mean and variabilities of parameters related to mass, stiffness and damping matrices. The present work is on the applicability of the proposed method for structures with low, medium, and high level of damping. A simulated study is conducted on beam samples with different damping levels in the presence of noise, incompleteness and modelling errors. Stochastic identification is further demonstrated experimentally on beam samples with low and high level of damping. The efficiency of the proposed method for stochastic updating of damping, mass and stiffness matrices and for prediction of variability in frequency response function (FRFs), modal data, and loss factors is studied.