Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Mode identifiability of a cable-stayed bridge under different excitation conditions assessed with an improved algorithm based on stochastic subspace identification

  • Wu, Wen-Hwa (Department of Construction Engineering, National Yunlin University of Science and Technology) ;
  • Wang, Sheng-Wei (Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology) ;
  • Chen, Chien-Chou (Department of Construction Engineering, National Yunlin University of Science and Technology) ;
  • Lai, Gwolong (Department of Construction Engineering, National Yunlin University of Science and Technology)
  • Received : 2015.05.31
  • Accepted : 2015.08.19
  • Published : 2016.03.25
⟨ Previous Next ⟩

Abstract

Deficient modes that cannot be always identified from different sets of measurement data may exist in the application of operational modal analysis such as the stochastic subspace identification techniques in large-scale civil structures. Based on a recent work using the long-term ambient vibration measurements from an instrumented cable-stayed bridge under different wind excitation conditions, a benchmark problem is launched by taking the same bridge as a test bed to further intensify the exploration of mode identifiability. For systematically assessing this benchmark problem, a recently developed SSI algorithm based on an alternative stabilization diagram and a hierarchical sifting process is extended and applied in this research to investigate several sets of known and blind monitoring data. The evaluation of delicately selected cases clearly distinguishes the effect of traffic excitation on the identifiability of the targeted deficient mode from the effect of wind excitation. An additional upper limit for the vertical acceleration amplitude at deck, mainly induced by the passing traffic, is subsequently suggested to supplement the previously determined lower limit for the wind speed. Careful inspection on the shape vector of the deficient mode under different excitation conditions leads to the postulation that this mode is actually induced by the motion of the central tower. The analysis incorporating the tower measurements solidly verifies this postulation by yielding the prevailing components at the tower locations in the extended mode shape vector. Moreover, it is also confirmed that this mode can be stably identified under all the circumstances with the addition of tower measurements. An important lesson learned from this discovery is that the problem of mode identifiability usually comes from the lack of proper measurements at the right locations.

Keywords

Acknowledgement

Supported by : Ministry of Science and Technology of Republic of China

References

  1. Alicioglu, B. and Lus, H. (2008), "Ambient vibration analysis with subspace methods and automated mode selection: case studies", J. Struct. Eng.-ASCE, 134(6), 1016-1029. https://doi.org/10.1061/(ASCE)0733-9445(2008)134:6(1016)
  2. Bakir, P.G. (2011), "Automation of the stabilization diagram for subspace based system identification", Expert Syst. Appl., 38(12), 14390-14397. https://doi.org/10.1016/j.eswa.2011.04.021
  3. Bendat, J.S. and Piersol, A.G. (1986), Random Data: Analysis and Measurement Procedures, John Wiley & Sons, New York, USA.
  4. Brinker, R., Zhang, L. and Andersen, P. (2001), "Modal identification of output-only systems using frequency domain decomposition", Smart Mater. Struct., 10(3), 441-445. https://doi.org/10.1088/0964-1726/10/3/303
  5. Carden, E.P. and Brownjohn J.M. (2008), "Fuzzy clustering of stability diagrams for vibration-based structural health monitoring", Comput.-Aided Civil Infrastruct. Eng., 23(5), 360-372. https://doi.org/10.1111/j.1467-8667.2008.00543.x
  6. Faravelli, L., Ubertini, F. and Fuggini, C. (2011), "System identification of a super high-rise building via a stochastic subspace approach", Smart Struct. Syst., 7(2), 133-152. https://doi.org/10.12989/sss.2011.7.2.133
  7. Jacobsen, N.J., Andersen, P. and Brincker, R. (2006), "Using enhanced frequency domain decomposition as a robust technique to harmonic excitation in operational modal analysis", Proceedings of the ISMA Conference on Advanced Acoustics and Vibration Engineering, Leuven, Belgium, September.
  8. 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
  9. 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
  10. Ljung, L. (1987), System Identification: Theory for the User, Prentice-Hall, Englewood Cliffs, New Jersey, USA.
  11. Ni, Y.Q., Wong, K.Y. and Xia, Y.X. (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
  12. 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
  13. Parloo, E., Guillaume, P., Cauberghe, B. (2003), "Maximum likelihood identification of non-stationary operational data", J. Sound Vib., 268(5), 971-991. https://doi.org/10.1016/S0022-460X(03)00377-8
  14. Peeters, B. (2000), "System identification and damage detection in civil engineering", Ph.D. Dissertation, Katholieke Universiteit Leuven, Leuven.
  15. 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
  16. Reynders, E., Houbrects, J. and De Roeck, G. (2012), "Fully automated (operational) modal analysis", Mech. Syst. Signal Pr., 29, 228-250. https://doi.org/10.1016/j.ymssp.2012.01.007
  17. Scionti, M. and Lanslots, J.P. (2005), "Stabilisation diagrams: pole identification using fuzzy clustering techniques", Adv. Eng. Softw., 36(11), 768-779. https://doi.org/10.1016/j.advengsoft.2005.03.029
  18. Ubertini, F., Gentile, C. and Materazzi, A.L. (2013), "Automated modal identification in operational conditions and its application to bridges", Eng. Struct., 46, 264-278. https://doi.org/10.1016/j.engstruct.2012.07.031
  19. Van Overschee, P. and De Moor, B. (1991), "Subspace algorithm for the stochastic identification problem", Proceedings of the 30th IEEE Conference on Decision and Control, Brighton, England, December.
  20. Van Overschee, P. and De Moor, B. (1993), "Subspace algorithms for the stochastic identification problem", Automatica, 29(3), 649-660. https://doi.org/10.1016/0005-1098(93)90061-W
  21. Van Overschee, P. and De Moor, B. (1996), Subspace Identification for Linear Systems: Theory-Implementation-Applications, Kluwer Academic Publishers, Dordecht, Netherlands.
  22. Wong, K.Y. (2004), "Instrumentation and health monitoring of cable-supported bridges", Struct. Control Health Monit., 11(2), 91-124. https://doi.org/10.1002/stc.33
  23. Wong, K.Y. (2007), "Design of a structural health monitoring system for long-span bridges", Struct. Infrastruct. E., 3(2), 169-185. https://doi.org/10.1080/15732470600591117
  24. Wu, W.H., Chen, C.C., Wang, S.W. and Lai, G. (2014), "Modal parameter determination of stay cable with an improved algorithm based on stochastic subspace identification", Proceedings of 7th European Workshop on Structural Health Monitoring, Nantes, France, July.
  25. Wu, W.H., Wang. S.W., Chen, C.C. and Lai, G. (2016), "Application of stochastic subspace identification for stay cables with an alternative stabilization diagram and hierarchical sifting process", Struct. Control Health Monit., in press (DOI: 10.1002/stc.1836).

Cited by

  1. Assessment of environmental and nondestructive earthquake effects on modal parameters of an office building based on long-term vibration measurements vol.26, pp.5, 2017, https://doi.org/10.1088/1361-665X/aa6ae6
  2. Dynamic Property Evaluation of a Long-Span Cable-Stayed Bridge (Sutong Bridge) by a Bayesian Method pp.1793-6764, 2018, https://doi.org/10.1142/S0219455419400108
  3. Mode identifiability of a cable-stayed bridge using modal contribution index vol.20, pp.2, 2017, https://doi.org/10.12989/sss.2017.20.2.115
  4. Stable modal identification for civil structures based on a stochastic subspace algorithm with appropriate selection of time lag parameter vol.4, pp.4, 2016, https://doi.org/10.12989/smm.2017.4.4.331
  5. Modal flexibility based damage detection for suspension bridge hangers: A numerical and experimental investigation vol.23, pp.1, 2016, https://doi.org/10.12989/sss.2019.23.1.015
  6. Modal parameter identification for closely spaced modes of civil structures based on an upgraded stochastic subspace methodology vol.15, pp.3, 2019, https://doi.org/10.1080/15732479.2018.1547770
  7. A novel recursive stochastic subspace identification algorithm with its application in long-term structural health monitoring of office buildings vol.24, pp.4, 2016, https://doi.org/10.12989/sss.2019.24.4.459
  8. Investigation of modal damping ratios for stay cables based on stochastic subspace identification with ambient vibration measurements vol.22, pp.16, 2016, https://doi.org/10.1177/1369433219855900