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Comparison of Automated Operational Modal Analysis Algorithms for Long-Span Bridge Applications

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Topics in Modal Analysis & Parameter Identification, Volume 8

Abstract

Automated operational modal analysis allows operational modal analysis to be used without the need of a human operator to identify structural modes from a stabilisation diagram. Multiple algorithms for automating this procedure have been proposed, and this paper selects four (Magalhaes 2008, Reynders 2012, Yang 2019, and Kvåle 2020) and benchmarks them using experimental data from the monitored, and previously studied, Hardanger Bridge. It is shown that the Magalhaes 2008 and Kvåle 2020 algorithms have the highest detection rates of all the algorithms but that the Reynders 2012 and Yang 2019 algorithms have higher automation and lowest error rates, respectively.

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Acknowledgements

The authors would like to acknowledge the financial support to this research granted by the Norwegian Public Roads Authority (NPRA).

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Authors and Affiliations

  1. Department of Structural Engineering, Structural Mechanics Group, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

    Anno C. Dederichs, Ole Øiseth, Øyvind W. Petersen & Knut A. Kvåle

Authors
  1. Anno C. Dederichs
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  2. Ole Øiseth
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  3. Øyvind W. Petersen
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  4. Knut A. Kvåle
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Correspondence to Anno C. Dederichs .

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Editors and Affiliations

  1. Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA

    Brandon J. Dilworth

  2. ATA Engineering (United States), San Diego, CA, USA

    Timothy Marinone

  3. University of Cincinnati, Cincinnati, OH, USA

    Michael Mains

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Dederichs, A.C., Øiseth, O., Petersen, Ø.W., Kvåle, K.A. (2023). Comparison of Automated Operational Modal Analysis Algorithms for Long-Span Bridge Applications. In: Dilworth, B.J., Marinone, T., Mains, M. (eds) Topics in Modal Analysis & Parameter Identification, Volume 8. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-031-05445-7_4

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  • DOI: https://doi.org/10.1007/978-3-031-05445-7_4

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  • Online ISBN: 978-3-031-05445-7

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