Bayesian model identification of higher-order frequency response functions for structures assembled by bolted joints

This paper proposes a procedure to identify stochastic Bouc-Wen model for describing the dynamics of structure assembled by bolted joints considering vibration data. The proposed identification approach is expressed into Bayesian framework take account data fluctuations related uncertainties in measurement process. calibration parameters uses analytical expressions higher-order frequency response functions (FRFs) approximating experimental measurements. Metropolis-Hastings algorithm employed posterior distributions. Once calibrated, applicability probabilistic evaluated, and its dynamical behavior compared with measurements from structure. results show that version can predict adequate agreement, including hysteretic effects, output jointed several excitation amplitudes.