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Estimation of parameter matrices based on measured data
Journal article   Open access   Peer reviewed

Estimation of parameter matrices based on measured data

Eun-Taik Lee, Salam Rahmatalla and Hee-Chang Eun
Applied mathematical modelling, Vol.35(10), pp.4816-4823
2011
DOI: 10.1016/j.apm.2011.03.048
url
https://doi.org/10.1016/j.apm.2011.03.048View
Published (Version of record) Open Access

Abstract

Finite element structural updating based on measured data may inherent significant errors due to uncertainties in the updated physical parameter matrices. This study presents analytical equations to estimate the change in the physical parameter matrices based on the measured modal data of dynamic systems and the measured displacement data of static systems. The equations for the parameter estimation are derived by minimizing cost functions in the satisfaction of the eigenvalue equation, the mode shape orthogonality requirements for the dynamic system, and the satisfaction of the measured displacement data for the static systems. The proposed method utilizes the Moore–Penrose inverse for the inverse of the rectangular matrices without using Lagrange multipliers. Comparing the analytical results with Berman & Nagy’s method and Yang & Chen’s method, this study demonstrates that the derived equations take simpler forms and produce more accurate results. The proposed method can be widely utilized in predicting static or dynamic parameter matrices for the design and analysis of any structure.
Cost function Minimization Orthogonality Modal data Parameter matrices

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