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Video analysis of nonlinear systems with extended Kalman filtering for modal identification

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Abstract

This study proposes to carry out the experimental modal analysis of nonlinear systems under the assumption of almost invariant modal shapes by coupling video analysis from a high speed/resolution camera and extended Kalman filtering. A clamped-clamped beam with a local nonlinearity is considered, and its vibrations are measured by detecting and tracking a large set of (virtual) sensors bonded to the beam outer surface. Specific image processing and video tracking techniques are employed and detailed herein. Then, the instantaneous natural frequencies and modal amplitudes are identified by means of a data assimilation method based on extended Kalman and modal filters. Finally, the proposed method of identification is assessed using a numerical example possessing 3 degrees of freedom and a strong nonlinearity. The performance and limits of the identification process are discussed.

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Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank Tilàn Dossogne (University of Liège) and Reza Babajanivalashedi (ISAE-Supméca) for their time and help during the experimental campaign.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. QUARTZ Laboratory (EA7393), Vibrations, Acoustics, Mechanical Structures and Shapes, ISAE-Supméca, Saint-Ouen-sur-Seine, France

    Stefania Lo Feudo, Jean-Luc Dion & Franck Renaud

  2. Space Structures and Systems Laboratory (S3L), Aerospace and Mechanical Engineering Department, University of Liège, Liège, Belgium

    Gaëtan Kerschen

  3. Mechanical Engineering Department, KU Leuven, Leuven, Belgium

    Jean-Philippe Noël

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  1. Stefania Lo Feudo
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Correspondence to Stefania Lo Feudo.

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Lo Feudo, S., Dion, JL., Renaud, F. et al. Video analysis of nonlinear systems with extended Kalman filtering for modal identification. Nonlinear Dyn 111, 13263–13277 (2023). https://doi.org/10.1007/s11071-023-08560-1

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