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Techniques for Nonlinear Identification and Maximizing Modal Response

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Abstract

Recent research has shown that weakly nonlinear structures can be modeled as a combination of nonlinear pseudo-modal models. These modal models consist of a linear spring, mass, and damper with the addition of a nonlinear element often identified using a restoring force surface technique. This approach is limited by force level achieved when exciting the system for identification. Extrapolation leads to poor results when predicting the nonlinear response; thus, there is a need to maximize the modal amplitude excited in these weakly nonlinear structures. Previous works have compared hammer testing to shaker testing using windowed sinusoidal input forces. This appeared to be a promising technique to increasing the excited modal amplitude. In this work the windowed sinusoidal technique is further investigated to understand how window parameters (such as window width) can be optimized to maximize the modal amplitude obtained during the identification process.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525.

This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

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Correspondence to D. Roettgen .

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Roettgen, D., Pacini, B.R., Mayes, R. (2020). Techniques for Nonlinear Identification and Maximizing Modal Response. In: Kerschen, G., Brake, M., Renson, L. (eds) Nonlinear Structures and Systems, Volume 1. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-030-12391-8_24

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  • DOI: https://doi.org/10.1007/978-3-030-12391-8_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12390-1

  • Online ISBN: 978-3-030-12391-8

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