Model Updating using Robust Estimation

C Mares (Liverpool University), MI Friswell (University of Wales Swansea) & JE Mottershead (Liverpool University)

Mechanical Systems and Signal Processing, Vol. 16, No. 1, January 2002, pp. 169-183

Abstract

Model updating attempts to correct errors in a finite element model using measured data. However, the measurements are corrupted with noise and the finite element model contains errors. Most updating schemes try to find the best model in some mean sense. This paper takes a different view and uses robust estimation techniques to determine the most robust parameter set. This parameter set is optimum in that the residuals are as small as can be, for a range of bounded uncertainties on the model and measurements. The relationship between this robust identification and Tikhonov regularisation is explored. The use of the 'L' curve method and expected parameter uncertainty to determine the regularisation parameter are shown. The approach is demonstrated using a simulated cantilever beam example, and experimental data from the GARTEUR test structure.

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This material has been published in the Mechanical Systems and Signal Processing, Vol. 16, No. 1, January 2002, pp. 169-183, the only definitive repository of the content that has been certified and accepted after peer review. Copyright and all rights therein are retained by Academic Press. This material may not be copied or reposted without explicit permission.

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Link to paper using doi:10.1006/mssp.2000.1375

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