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Title
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Frequency-domain generalized total least-squares identification for modal analysis
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Author
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Abstract
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| This contribution focuses on the area of modal analysis and studies the applicability of total least-squares (TLS) algorithms for the estimation of modal parameters in the frequency-domain from input-output Fourier data. These algorithms can be preferable to classical frequency response function based curve-fitting methods. This is certainly the case when periodic excitation is applied and an errors-in-variables noise model can be determined. The proposed generalized total least-squares (GTLS) algorithm provides an accurate modal parameter estimation by the integration of this noise model in the parametric identification process. Modal-based design and comfort improvement, damage assessment and structural health monitoring, and finite element model updating are important applications that strongly rely on a high accuracy of the modal model. In this paper it is shown how frequency-domain TLS and GTLS estimators can be numerically optimized to handle large amounts of modal data. In order to use an errors-in-variables noise model, a linear approximation is necessary in order to obtain a fast implementation of the GTLS algorithm. The validity of this approximation is a function of the signal-to-noise ratio of the input Fourier data and is evaluated by means of Monte Carlo simulations and experimental data. (C) 2003 Elsevier Ltd. All rights reserved. |
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Language
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English
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Source (journal)
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Journal of sound and vibration / University of Southampton. Institute of Sound and Vibration Research. - London
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Publication
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London
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2004
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ISSN
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0022-460X
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DOI
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10.1016/J.JSV.2003.09.058
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Volume/pages
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278
:1-2
(2004)
, p. 21-38
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ISI
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000224594200002
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Full text (Publisher's DOI)
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