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  4. Dynamics of Geometrically-Nonlinear Beam Structures, Part 2: Experimental Analysis
 
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2019
Conference Paper
Title

Dynamics of Geometrically-Nonlinear Beam Structures, Part 2: Experimental Analysis

Abstract
System identification is a key tool to gather information about dynamical structures. In the last decades, important steps have been made to perform this task in the presence of localized nonlinearities. However, the continual interest in improving structural performance has created the need of designing light and flexible elements in several engineering fields. These elements are usually characterized by moderate and large deformations, exhibiting distributed nonlinearities. System identification of structures with distributed nonlinear features remains particularly challenging, especially when dealing with experimental data. This work proposes a method to perform such a task, relying on a convenient basis reduction of the measured signals. The identification is then performed using the nonlinear subspace identification method (NSI) in the reduced domain together with a closed-form nonlinear description. This methodology is validated on an experimental structure, consisting of a very thin steel beam that is clamped at both ends. Excited with a multisine, the beam undergoes large amplitude oscillations. A final objective of the identification is to exploit its response through the correct identification of the parameters that define the nonlinearity. Results show a high level of accuracy, which validates the effectiveness of the methodology and paves the way toward the identification of more complex real-life structures exhibiting large deformations.
Author(s)
Anastasio, D.
Dietrich, J.
Noël, J.P.
Kerschen, G.
Marchesiello, S.
Häfele, J.
Gebhardt, C.G.
Rolfes, R.
Mainwork
37th IMAC, a Conference and Exposition on Structural Dynamics 2019. Proceedings. Vol.1: Nonlinear structures and systems  
Conference
Conference and Exposition on Structural Dynamics 2019  
DOI
10.1007/978-3-030-12391-8_29
Language
English
Fraunhofer-Institut für Windenergiesysteme IWES  
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