Abstract: To improve the model updating efficiency of high-speed train wheel and reduce model updating errors, considering the influence of uncertainty factors, a Bayesian model updating method based on DREAM and Kriging models is proposed and applied to the finite element model updating of high-speed train wheels.Initially, a finite element model of a specific high-speed train wheel is established based on design parameters, and the Latin Hypercube Sampling method is used to design the initial sample of parameters to be updated for the wheel.The frequency functions corresponding to different samples are analyzed, and wavelet coefficients are extracted.Subsequently, a Kriging model that meets accuracy requirements is constructed with the initial sample of parameters to be updated as inputs and the wavelet coefficients as outputs.Finally, the finite element model is replaced with the constructed Kriging model for finite element analysis, and the DREAM algorithm is used to update the parameters of the high-speed train wheel finite element model to be updated.Results show that the Bayesian model updating method based on the DREAM and Kriging models can save a significant amount of model updating time, enhance model updating efficiency, and the errors in the updated high-speed train wheel finite element model are small.