DOI QR코드

DOI QR Code

Mode identifiability of a cable-stayed bridge using modal contribution index

  • Huang, Tian-Li (School of Civil Engineering, Central South University) ;
  • Chen, Hua-Peng (Department of Engineering Science, University of Greenwich)
  • Received : 2017.01.16
  • Accepted : 2017.04.10
  • Published : 2017.08.25

Abstract

The modal identification of large civil structures such as bridges under the ambient vibrational conditions has been widely investigated during the past decade. Many operational modal analysis methods have been proposed and successfully used for identifying the dynamic characteristics of the constructed bridges in service. However, there is very limited research available on reliable criteria for the robustness of these identified modal parameters of the bridge structures. In this study, two time-domain operational modal analysis methods, the data-driven stochastic subspace identification (SSI-DATA) method and the covariance-driven stochastic subspace identification (SSI-COV) method, are employed to identify the modal parameters from field recorded ambient acceleration data. On the basis of the SSI-DATA method, the modal contribution indexes of all identified modes to the measured acceleration data are computed by using the Kalman filter, and their applicability to evaluate the robustness of identified modes is also investigated. Here, the benchmark problem, developed by Hong Kong Polytechnic University with field acceleration measurements under different excitation conditions of a cable-stayed bridge, is adopted to show the effectiveness of the proposed method. The results from the benchmark study show that the robustness of identified modes can be judged by using their modal contributions to the measured vibration data. A critical value of modal contribution index of 2% for a reliable identifiability of modal parameters is roughly suggested for the benchmark problem.

Keywords

Acknowledgement

Supported by : Natural Science Foundation of China

References

  1. Au, S.K. and Zhang, F.L. (2016), "Fundamental two-stage formulation for Bayesian system identification, Part I: general theory", Mech. Syst. Signal Pr., 66-67, 31-42. https://doi.org/10.1016/j.ymssp.2015.04.025
  2. Bendat, J.S. and Piersol, A.G. (1993), Engineering applications of correlation and spectral analysis, New York, NY, Wiley-Interscience.
  3. Brincker, R., Zhang, L. and Andersen, P. (2000), "Modal identification from ambient responses using frequency domain decomposition", Proceedings of the 18th International Modal Analysis Conference (IMAC), San Antonio, Texas, USA.
  4. Brownjohn, J.M.W., Magalhaes, F., Caetano, E. and Cunha, A. (2010), "Ambient vibration re-testing and operational modal analysis of the Humber Bridge", Eng. Struct., 32(8), 2003-2018. https://doi.org/10.1016/j.engstruct.2010.02.034
  5. Cara, F.J., Juan, J., Alarcon, E., Reynders, E. and De Roeck, G. (2013), "Modal contribution and state space order selection in operational modal analysis", Mech. Syst. Signal Pr., 38(2), 276-298. https://doi.org/10.1016/j.ymssp.2013.03.001
  6. Cunha, A., Caetano, E. and Delgado, R. (2001), "Dynamic tests on large cable-stayed bridge", J. Bridge Eng., 6(1), 54-62. https://doi.org/10.1061/(ASCE)1084-0702(2001)6:1(54)
  7. Chen H.P. (2006), "Efficient methods for determining modal parameters of dynamic structures with large modifications", J. Sound Vib., 298(1-2), 462-470. https://doi.org/10.1016/j.jsv.2006.06.002
  8. Chen, H.P. and Huang, T.L. (2012), "Updating finite element model using dynamic perturbation method and regularization algorithm", Smart Struct. Syst., 10(4-5), 427-442. https://doi.org/10.12989/sss.2012.10.4_5.427
  9. Chen, H.P. and Maung, T.S. (2014a), "Regularised finite element model updating using measured incomplete modal data", J. Sound Vib., 333(21), 5566-5582. https://doi.org/10.1016/j.jsv.2014.05.051
  10. Chen, H.P. and Maung, T.S. (2014b), "Structural damage evolution assessment using regularised time step integration method", J. Sound Vib., 333(18), 4104-4122. https://doi.org/10.1016/j.jsv.2014.04.044
  11. Chopra, A.K. (2005), Dynamics of structures: theory and applications to earthquake engineering (3rd edition), Prentice Hall.
  12. Ewins, D.J. (2000), Modal Testing: Theory, Practice and Application (2nd edition), Research Studies Press Ltd, Hertfordshire.
  13. Goi, Y. and Kim, C.W. (2016), "Mode identifiability of a multi-span cable-stayed bridge utilizing stabilization diagram and singular values", Smart Struct. Syst., 17(3), 391-411. https://doi.org/10.12989/sss.2016.17.3.391
  14. Guillaume, P., Verboven, P., Vanlanduit, S., Van Der Auweraer, H. and Peeters, B. (2003), "A poly-reference implementation of the least-squares complex frequency-domain estimator", Proceedings of the 21st International Modal Analysis Conference (IMAC), Kissimmee, FL, USA.
  15. Juang, J.N. and Pappa, R.S. (1985), "An eigensystem realization algorithm for modal parameter identification and model reduction", J. Guid. Control. Dynam., 8(5), 620-627. https://doi.org/10.2514/3.20031
  16. 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
  17. Le, T.H. and Caracoglia, L. (2015), "High-order, closely-spaced modal parameter estimation using wavelet analysis", Struct. Eng. Mech., 56(3), 423-442. https://doi.org/10.12989/sem.2015.56.3.423
  18. Li, M. and Ni, Y.Q. (2016), "Modal identifiability of a cable-stayed bridge using proper orthogonal decomposition", Smart Struct. Syst., 17(3), 413-429. https://doi.org/10.12989/sss.2016.17.3.413
  19. Magalhaes, F., Cunha, A. and Caetano, E. (2008), "Dynamic monitoring of a long span arch bridge", Eng. Struct., 30(11), 3034-3044. https://doi.org/10.1016/j.engstruct.2008.04.020
  20. Moradipour, P., Chan, T.H.T. and Gallage, C. (2015), "An improved modal strain energy method for structural damage detection, 2D simulation", Struct. Eng. Mech., 54(1), 105-119. https://doi.org/10.12989/sem.2015.54.1.105
  21. 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
  22. Ni, Y.Q., Wong, K.Y. and Xia, Y. (2011), "Health checks through landmark bridges to sky-high structures", Adv. Struct. Eng., 14(1), 103-119. https://doi.org/10.1260/1369-4332.14.1.103
  23. Overschee, V.P. and De Moor, B. (1996), Subspace Identification for Linear Systems, Kluwer Academic Publisher, Dordrecht, The Netherlands.
  24. Papadimitriou, C. and Papadioti, D.C. (2013), "Component mode synthesis techniques for finite element model updating", Comput. Struct., 126(1), 15-28. https://doi.org/10.1016/j.compstruc.2012.10.018
  25. 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
  26. Reynders, E. (2012), "System identification methods for (operational) modal analysis: review and comparison", Arch. Comput. Methods Eng., 19(1), 51-124. https://doi.org/10.1007/s11831-012-9069-x
  27. Reynders, E., Schevenels, M. and De Roeck, G. (2011), "User's manual: MACEC 3.2 - A Matlab toolbox for experimental and operational modal analysis", Department of Civil Engineering, Catholic University of Leuven, Belgium.
  28. Ren, W.X., Peng, X.L. and Lin, Y.Q. (2005), "Experimental and analytical studies on dynamic characteristics of a large span cable-stayed bridge", Eng. Struct., 27(4), 535-548. https://doi.org/10.1016/j.engstruct.2004.11.013
  29. Wu, W.H., Wang, S.W., Chen, C.C. and Lai, G. (2016a), "Mode identifiability of a cable-stayed bridge under different excitation conditions assessed with an improved algorithm based on stochastic subspace identification", Smart Struct. Syst., 17(3), 363-389. https://doi.org/10.12989/sss.2016.17.3.363
  30. Wu, W.H., Wang, S.W., Chen, C.C. and Lai, G. (2016b), "Application of stochastic subspace identification for stay cables with an alternative stabilization diagram and hierarchical sifting process", Struct. Control Health Monit., 23(9), 1194-1213. https://doi.org/10.1002/stc.1836
  31. Zhang, F.L. and Au, S.K. (2016), "Fundamental two-stage formulation for Bayesian system identification, Part II: application to ambient vibration data", Mech. Syst. Signal Pr., 66-67, 43-61. https://doi.org/10.1016/j.ymssp.2015.04.024
  32. Zhang, F.L., Ni, Y.Q. and Ni, Y.C. (2016), "Mode identifiability of a cable-stayed bridge based on a Bayesian method", Smart Struct. Syst., 17(3), 471-489. https://doi.org/10.12989/sss.2016.17.3.471