Distributed parameter estimation of a stochastic beam structure via sensitivity-based model updating using experimental FRFs
Marcela Machado1; Sondipon Adhikari2; Jose Maria Campos Dos Santos1; Jose Roberto Arruda1
1 Unicamp; 2 Swansea University
doi:10.20906/CPS/USM-2016-0055
Resumo
Structural parameter estimation is affected not only by measurement noise, but also by unknown uncertainties which are present in the system model. Deterministic structural model updating methods minimize the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. The structural model includes parameters such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. These parameters are usually considered homogeneous and deterministic along the structure. In this paper the distributed and non homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields, and are expanded in a spectral Karhunen-Loeve (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam structure is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam structure with distributed bending rigidity and mass density are used to verify the proposed method. This extension to standard model updating procedures can enhance the dynamic description of structural dynamic models.
Palavras-chave: Wave propagation; Stochastic method; Sensitivity analysis