Estimation of the full-field dynamic response of a floating bridge using Kalman-type filtering algorithms

•A case study of full-field response estimation of a floating bridge is presented.•Kalman filter-type algorithms are used for state and input estimation.•The methods make use of a system model and measured acceleration data.•Estimated displacements agree with measured GNSS data. Numerical prediction...

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Bibliographic Details
Published inMechanical systems and signal processing Vol. 107; pp. 12 - 28
Main Authors Petersen, Ø.W., Øiseth, O., Nord, T.S., Lourens, E.
Format Journal Article
LanguageEnglish
Published Berlin Elsevier Ltd 01.07.2018
Elsevier BV
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Summary:•A case study of full-field response estimation of a floating bridge is presented.•Kalman filter-type algorithms are used for state and input estimation.•The methods make use of a system model and measured acceleration data.•Estimated displacements agree with measured GNSS data. Numerical predictions of the dynamic response of complex structures are often uncertain due to uncertainties inherited from the assumed load effects. Inverse methods can estimate the true dynamic response of a structure through system inversion, combining measured acceleration data with a system model. This article presents a case study of full-field dynamic response estimation of a long-span floating bridge: the Bergøysund Bridge in Norway. This bridge is instrumented with a network of 14 triaxial accelerometers. The system model consists of 27 vibration modes with natural frequencies below 2 Hz, obtained from a tuned finite element model that takes the fluid-structure interaction with the surrounding water into account. Two methods, a joint input-state estimation algorithm and a dual Kalman filter, are applied to estimate the full-field response of the bridge. The results demonstrate that the displacements and the accelerations can be estimated at unmeasured locations with reasonable accuracy when the wave loads are the dominant source of excitation.
ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2018.01.022