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Uncertainties in an Application of Operational Modal Analysis

  • Lorenzo Banfi
  • Luigi CarassaleEmail author
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

Operational modal analysis is widely used to estimate the mechanical properties of vibrating systems. The several available mathematical techniques, based upon different mathematical formulations, have the common feature that the unmeasured excitation is modeled as a random process specified by some probabilistic model. In practical applications, the length of the measurement is necessarily limited and the probabilistic model adopted to represent the excitation does not necessarily apply. This, together with measurement errors, leads to uncertainties of different nature that affect the estimation of the modal parameters. We discuss the effect of these uncertainty through the assistance of a wide numerical simulation in which a realistic identification process is reproduced isolating different sources of uncertainty. Besides, the identification activity of the experimentalist (e.g. rejection of clearly unphysical results) is mimed by an automated software. The conclusions derived from the simulations are verified by applying the same procedures to a real case study for which a large measurement database is available.

Keywords

Operational modal analysis Uncertainty quantification Monte Carlo simulations Frequency domain decomposition Stochastic subspace identification 

References

  1. 1.
    Brincker, L., Zhang, L., Andersem, P.: Modal identification from ambient responses using frequency domain decomposition. In: Proceedings of the 18th International Modal Analysis Conference, pp. 625–630 (2000)Google Scholar
  2. 2.
    Peeters, B., De Roeck, G.: Reference-based stochastic subspace identification for output-only modal analysis. Int. J. Mech. Syst. Signal Process. 13, 855–878 (1999)CrossRefGoogle Scholar
  3. 3.
    Overschee, P.V.: Subspace Identification for the Linear Systems: Theory Implementation. Kluwer Academic Publishers, Boston (1996)CrossRefzbMATHGoogle Scholar
  4. 4.
    Bajric, A., Georgakis, C.T., Brincker, R.: Evaluation of damping using frequency domain operational modal analysis techniques. In: Proceedings of the XXXIII IMAC Conference, Orlando, FL (2015)Google Scholar
  5. 5.
    Reynders, E.: System identification methods for (operational) modal analysis: review and comparison. Arch. Comput. Meth. Eng. 19, 51–124 (2012)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Reynders, E., Pintelon, R., De Roeck, G.: Uncertainty bounds on modal parameters obtained from stochastic subspace identification. Mech. Syst. Signal Process. 22, 948–969 (2008)CrossRefGoogle Scholar
  7. 7.
    Banfi, L.: Modal identification in frequency and time domains: assessment of uncertainties. Master Thesis (2013)Google Scholar
  8. 8.
    Carassale, L., Solari, G.: Monte Carlo simulation ofwind velocity fields on complex structures. J. Wind Eng. Ind. Aerodyn. 94, 323–339 (2006)CrossRefGoogle Scholar
  9. 9.
    Carassale, L., Percivale, F.: POD-based modal identification of wind-excited structures. In: Proceedings of the 12th International Conference of Wind Engineering, Cairns, 1–6 July 2007Google Scholar

Copyright information

© The Society for Experimental Mechanics, Inc. 2016

Authors and Affiliations

  1. 1.Department of Civil, Chemical and Environmental EngineeringUniversity of GenovaGenovaItaly

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