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  5. Joint input-response estimation for structural systems based on reduced-order models and vibration data from a limited number of sensors

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Article
English
2012

Joint input-response estimation for structural systems based on reduced-order models and vibration data from a limited number of sensors

0 Datasets

0 Files

English
2012
Mechanical Systems and Signal Processing
Vol 29
DOI: 10.1016/j.ymssp.2012.01.011

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Edwin Reynders
Edwin Reynders

University Of Leuven

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Eliz‐Mari Lourens
Costas Papadimitriou
Steven Gillijns
+3 more

Abstract

An algorithm is presented for jointly estimating the input and state of a structure from a limited number of acceleration measurements. The algorithm extends an existing joint input-state estimation filter, derived using linear minimum-variance unbiased estimation, to applications in structural dynamics. The filter has the structure of a Kalman filter, except that the true value of the input is replaced by an optimal estimate. No prior information on the dynamic evolution of the input forces is assumed and no regularization is required, permitting online application. The effectiveness and accuracy of the proposed algorithm are demonstrated using data from a numerical cantilever beam example as well as a laboratory experiment on an instrumented steel beam and an in situ experiment on a footbridge.

How to cite this publication

Eliz‐Mari Lourens, Costas Papadimitriou, Steven Gillijns, Edwin Reynders, Guido De Roeck, Geert Lombaert (2012). Joint input-response estimation for structural systems based on reduced-order models and vibration data from a limited number of sensors. Mechanical Systems and Signal Processing, 29, pp. 310-327, DOI: 10.1016/j.ymssp.2012.01.011.

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Publication Details

Type

Article

Year

2012

Authors

6

Datasets

0

Total Files

0

Language

English

Journal

Mechanical Systems and Signal Processing

DOI

10.1016/j.ymssp.2012.01.011

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