Smart Structures and Systems

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Automated identification of the modal parameters of a cable-stayed bridge: Influence of the wind conditions

  • Magalhaes, Filipe (CONSTRUCT - ViBest, Faculty of Engineering, University of Porto (FEUP)) ;
  • Cunha, Alvaro (CONSTRUCT - ViBest, Faculty of Engineering, University of Porto (FEUP))
  • Received : 2015.08.05
  • Accepted : 2015.12.12
  • Published : 2016.03.25
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Abstract

This paper was written in the context of a benchmark study promoted by The Hong Kong Polytechnic University using data samples collected in an instrumented cable-stayed bridge. The main goal of the benchmark test was to study the identification of the bridge modes of vibration under different wind conditions. In this contribution, the tools developed at ViBest/FEUP for automated data processing of setups collected by dynamic monitoring systems are presented and applied to the data made available in the context of the benchmark study. The applied tools are based on parametric output only modal identification methods combined with clustering algorithms. The obtained results demonstrate that the proposed algorithms succeeded to automatically identify the modes with relevant contribution for the bridge response under different wind conditions.

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References

  1. Allemang, R.J. and Brown, D.L. (1982), "A Correlation coefficient for modal vector analysis", Proceedings of the IMAC 1, International Modal Analysis Conference, Orlando, Florida, USA.
  2. Bergermann, R. and Schlaich, M. (1996), "Ting Kau Bridge, Hong Kong", Struct. Eng. Int., 6(3), 152-154. https://doi.org/10.2749/101686696780495563
  3. Hair, J., Anderson, R., Tatham, R. and Black, W. (1998), Multivariate Data Analysis, Prentice Hall.
  4. Johnson, R.A. and Wichern, D.W. (1992), Applied Multivariate Statistical Analysis, Prentice Hall.
  5. Ko, J.M. and Ni, Y.Q. (2005), "Technology developments in structural health monitoring of large-scale bridges", Eng. Struct.., 27(12), 1715-1725. https://doi.org/10.1016/j.engstruct.2005.02.021
  6. Magalhaes, F., Cunha, A. and Caetano, E. (2009) "Online automatic identification of the modal parameters of a long span arch bridge", Mech. Syst. Signal Pr., 23(2), 316-329. https://doi.org/10.1016/j.ymssp.2008.05.003
  7. Magalhaes, F. (2010), Operational Modal Analysis for Testing and Monitoring of Bridges and Special Structures, Ph.D. Dissertation, Faculty of Engineering, University of Porto, Porto, Portugal.
  8. Magalhaes, F., Amador, S., Cunha, A. and Caetano, E. (2012), "Dynamo-software for vibration based structural health monitoring", Proceedings of the 6th Int. Conf. on Bridge Maintenance, Safety and Management, IABMAS 2012, Stresa, Lake Maggiore, Italy.
  9. Ni, Y.Q., Xia, Y., Lin, W., Chen, W.H. and Ko, J.M. (2012), "SHM benchmark for high-rise structures: a reduced-order finite element model and field measurement data", Smart Struct. Syst., 10(4), 411-426. https://doi.org/10.12989/sss.2012.10.4_5.411
  10. Ni, Y.Q., Wang, Y.W. and Xia, Y.X. (2015), "Investigation of mode identifiability of a cable-stayed bridge: comparison from ambient vibration responses and from typhoon-induced dynamic responses", Smart Struct. Syst., 15(2), 447-468. https://doi.org/10.12989/sss.2015.15.2.447
  11. Peeters, B. and De Roeck, G. (1999), "Reference-based stochastic subspace identification for output-only modal analysis", Mech. Syst. Signal Pr., 13(6), 855-878. https://doi.org/10.1006/mssp.1999.1249
  12. Yuen, K.V. and Mu, H.Q. (2012), "A novel probabilistic method for robust parametric identification and outlier detection", Probabilist. Eng. Mech., 30, 48-59 https://doi.org/10.1016/j.probengmech.2012.06.002

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