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Comparison of Two (Geometric) Algorithms for Auto OMA

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Abstract

In this paper we compare two geometric algorithms for automatic Operational Modal Analysis(OMA). The compared algorithms are the Shortest Path Algorithm (SPA) that considers shortest paths in the set of poles and the Smallest Sphere Algorithm (SSA) that operates on the set of identified poles to find the set of smallest spheres, containing physical poles. Both algorithm are based on sliding filter stability diagrams recently introduced by Olsen et al. We show how the two algorithms identify system parameters of a simulated system, and illustrate the difference between the identified parameters. The two algorithms are compared and illustrated on simulated data. Different choices of distance measures are discussed and evaluated. It is illustrated how a simple distance measure outperforms traditional distance measures from other Auto OMA algorithms. Traditional measures are unable to discriminate between modes and noise.

Keywords

  • System identification
  • Automated operational modal analysis
  • Sliding filter stability
  • Distance measure
  • Smallest sphere algorithm
  • Shortest path algorithm

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References

  1. Brincker, R., Ventura, C.: Introduction to Operational Modal Analysis. Wiley, New York (2015). ISBN:9781118535158

    CrossRef  Google Scholar 

  2. Allemang, R.J., Brown, D.L.: Operational modal analysis on wind turbine hub. In: Proceedings of the 36st International Modal Analysis Conference (IMAC). SEM, Orlando (2018)

    Google Scholar 

  3. Cormen, T.H., Leiserson, C.E., Rivest, R.L.: Introduction to Algorithms. MIT Electrical Engineering and Computer Science. The MIT Press (1990). ISBN:0262530910

    MATH  Google Scholar 

  4. Allemang, R.J., Brown, D.L.: A correlation coefficient for modal vector analysis. In: Proceedings of the 1st International Modal Analysis Conference (IMAC), vol. 1, pp. 110–116. SEM, Orlando (1982)

    Google Scholar 

  5. Neu, E., Janser, F., Khatibi, A.A., Orifici, A.C.: Fully automated operational modal analysis using multi-stage clustering. Mech. Syst. Signal Process. 84, 308–323 (2017)

    CrossRef  Google Scholar 

  6. Reynders, E., Houbrechts, J., De Roeck, G.: Fully automated (operational) modal analysis. Mech. Syst. Signal Process. 29, 228–250 (2012)

    CrossRef  Google Scholar 

  7. Raschka, S.: Python Machine Learning. Packt Publishing Ltd, Birmingham (2015)

    Google Scholar 

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Acknowledgements

This contribution is partly based upon work done in the INNOMILL project supported by the Innovation Fund Denmark, contract number 54-2014-3.

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Correspondence to Martin Juul .

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Juul, M., Olsen, P., Balling, O., Amador, S., Brincker, R. (2019). Comparison of Two (Geometric) Algorithms for Auto OMA. In: Mains, M., Dilworth, B. (eds) Topics in Modal Analysis & Testing, Volume 9. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-74700-2_7

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  • DOI: https://doi.org/10.1007/978-3-319-74700-2_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74699-9

  • Online ISBN: 978-3-319-74700-2

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