Verification of joint input-state estimation for force identification by means of in situ measurements on a footbridge

© © 2016 Elsevier Ltd. All rights reserved. This paper presents a verification of a joint input-state estimation algorithm using data obtained from in situ experiments on a footbridge. The estimation of the input and the system states is performed in a minimum-variance unbiased way, based on a limit...

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Veröffentlicht in:Mechanical Systems and Signal Processing 2016-06, Vol.15, p.245-260
Hauptverfasser: Maes, Kristof, Van Nimmen, Katrien, Lourens, E, Rezayat, A, Guillaume, P, De Roeck, Guido, Lombaert, Geert
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Sprache:eng
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Zusammenfassung:© © 2016 Elsevier Ltd. All rights reserved. This paper presents a verification of a joint input-state estimation algorithm using data obtained from in situ experiments on a footbridge. The estimation of the input and the system states is performed in a minimum-variance unbiased way, based on a limited number of response measurements and a system model. A dynamic model of the footbridge is obtained using a detailed finite element model that is updated using a set of experimental modal characteristics. The joint input-state estimation algorithm is used for the identification of two impact, harmonic, and swept sine forces applied to the bridge deck. In addition to these forces, unknown stochastic forces, such as wind loads, are acting on the structure. These forces, as well as measurement errors, give rise to uncertainty in the estimated forces and system states. Quantification of the uncertainty requires determination of the power spectral density of the unknown stochastic excitation, which is identified from the structural response under ambient loading. The verification involves comparing the estimated forces with the actual, measured forces. Although a good overall agreement is obtained between the estimated and measured forces, modeling errors prohibit a proper distinction between multiple forces applied to the structure for the case of harmonic and swept sine excitation.
ISSN:0888-3270