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  5. Experimental verification of optimal sensor placement for multi-setup modal testing

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Article
English
2017

Experimental verification of optimal sensor placement for multi-setup modal testing

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English
2017
Procedia Engineering
Vol 199
DOI: 10.1016/j.proeng.2017.09.063

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Guido De Roeck
Guido De Roeck

University Of Leuven

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Jie Zhang
Kristof Maes
Guido De Roeck
+2 more

Abstract

Modal testing of large structures is usually performed in multiple setups in order to obtain sufficiently detailed information on the mode shapes with a limited number of sensors. Several reference sensors are kept fixed during the entire measurement, while the other so-called roving sensors are moved in different setups. A careful choice of the reference and roving sensor positions is necessary for a successful modal analysis. An optimal sensor placement strategy which was developed for multi-setup modal identification is applied to the modal testing of a nearly repetitive office building. Based on the strategy the optimal reference sensor locations are designed for the building. As a comparison, badly chosen reference sensor locations are also studied. The optimal sensor placement strategy is verified by comparing the modal identification results obtained from the optimally selected reference sensor locations to those obtained from the badly chosen reference sensor locations. The experimental results show that the optimal sensor placement strategy for multi-setup modal testing allows extracting more information from the measurement. Two roving sensor strategies, i.e. a cluster and a uniform distribution of roving sensors, are also investigated. It is found that a uniform distribution of roving sensors is preferred over a cluster of roving sensors.

How to cite this publication

Jie Zhang, Kristof Maes, Guido De Roeck, Edwin Reynders, Geert Lombaert (2017). Experimental verification of optimal sensor placement for multi-setup modal testing. Procedia Engineering, 199, pp. 1068-1073, DOI: 10.1016/j.proeng.2017.09.063.

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Publication Details

Type

Article

Year

2017

Authors

5

Datasets

0

Total Files

0

Language

English

Journal

Procedia Engineering

DOI

10.1016/j.proeng.2017.09.063

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