Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Modal identification of Canton Tower under uncertain environmental conditions

  • Ye, Xijun (School of Civil Engineering and Transportation, South China University of Technology) ;
  • Yan, Quansheng (School of Civil Engineering and Transportation, South China University of Technology) ;
  • Wang, Weifeng (School of Civil Engineering and Transportation, South China University of Technology) ;
  • Yu, Xiaolin (School of Civil Engineering and Transportation, South China University of Technology)
  • Received : 2011.11.08
  • Accepted : 2012.04.10
  • Published : 2012.10.25
⟨ Previous Next ⟩

Abstract

The instrumented Canton Tower is a 610 m high-rise structure, which has been considered as a benchmark problem for structural health monitoring (SHM) research. In this paper, an improved automatic modal identification method is presented based on a natural excitation technique in conjunction with the eigensystem realization algorithm (NExT/ERA). In the proposed modal identification method, damping ratio, consistent mode indicator from observability matrices (CMI_O) and modal amplitude coherence (MAC) are used as criteria to distinguish the physically true modes from spurious modes. Enhanced frequency domain decomposition (EFDD), the data-driven stochastic subspace identification method (SSI-DATA) and the proposed method are respectively applied to extract the modal parameters of the Canton Tower under different environmental conditions. Results of modal parameter identification based on output-only measurements are presented and discussed. User-selected parameters used in those methods are suggested and discussed. Furthermore, the effect of environmental conditions on the dynamic characteristics of Canton tower is investigated.

Keywords

References

  1. Abdel Wahab, M. and De Roeck, G. (1997), "Effect of temperature on dynamic system parameters of a highway bridge", J. Struct. Eng. - ASCE, 7(4), 266-270.
  2. Allemang, R.J. (1999), Vibrations: experimental modal analysis, Course Notes (UC-SDRL-CN-20-263-663/664), Structural Dynamics Research Laboratory, Univ. of Cincinnati, Cincinnati, (http://www.sdrl.uc.edu/academiccourse-info/).
  3. Brincker, R., Ventura, C. and Andersen, P. (2001), "Damping estimation by frequency domain decomposition", Proceedings of the 19th Int. Modal Analysis Conf. (IMAC), Kissimmee, Fla., Soc. Experimental Mechanics, Inc., Bethel, Conn.
  4. Brincker, R., Zhang, L. and Andersen, P. (2000), "Modal identification from ambient responses using frequency domain decomposition", Proceedings of the 18th Int. Modal Analysis Conf. (IMAC), San Antonio, Tex., Soc. Experimental Mechanics, Inc., Bethel, Conn.
  5. Brown, D.L., Allemang, R.J., Zimmerman, R. and Mergeay, M. (1979), Parameters Estimation Techniques for Modal Analysis, Society of Automotive Engineers Technical Paper Series, 88, 828-846.
  6. Caicedo, J.M., Dyke, S.J. and Johnson, E.A. (2004), "Natural excitation technique and eigensystem realization algorithm for phase I of the IASC-ASCE benchmark problem: Simulated data", J. Eng. Mech -ASCE, 130(1), 49-60. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(49)
  7. Chen, W.H, Lu, Z.R., Lin, W., Chen, S.H., Ni, Y.Q., Xia, Y. and Liao, W.Y. (2011), "Theoretical and experimental modal analysis of the Guangzhou New TV Tower", J. Eng. Mech -ASCE, 33(12), 3628-3646.
  8. Corrêa, M.R. and Costa, A.C. (1992), Dynamic Tests of the Bridge over the Arade River, Cable-stayed bridges of Guadiana and Arade.
  9. Faravelli, L., Ubertini, F. and Fuggini, C. (2010), "Subspace identification of the Guangzhou New TV Tower", Proceedings of the 5th World Conference on Structural Control and Monitoring, Tokyo, Japan.
  10. He, X., Fraser, M., Conte J.P. and Elgamal, A. (2007), "Investigation of environmental effects on identified modal parameters of the Voigt Bridge", Proceedings of the18th Engineering Mechanics Division Conference of the ASCE, Blacksburg, VA.
  11. He, X., Moaveni, B., Conte, J.P. and Elgamal, A. (2006), "Comparative study of system identification techniques applied to New Carquinez Bridge", Proceedings of the 3rd Conf. on Bridge Maintenance, Safety and Management, IABMAS, Porto, Portugal.
  12. He, X., Moaveni, B., Conte, J.P., Elgamal, A. and Masri, S.F. (2009), "System identification of Alfred Zampa Memorial Bridge using dynamic field test data", J. Struct. Eng. - ASCE, 135(1), 54-66. https://doi.org/10.1061/(ASCE)0733-9445(2009)135:1(54)
  13. Hua, X.G., Ni, Y.Q., Ko, J.M. and Wong, K.Y. (2007), "Modeling of temperature-frequency correlation using combined principal component analysis and support vector regression technique", J. Comput. Civil Eng. - ASCE, 21(2), 122-135. https://doi.org/10.1061/(ASCE)0887-3801(2007)21:2(122)
  14. Ibrahim, S.R. and Mikulcik, E.C. (1977), "A method for the direct identification of vibration parameters from the free response", Shock Vib., 47(4), 183-198.
  15. James, G.H., Carne, T.G. and Lauffer, J.P. (1993), The Natural Excitation Technique for Modal Parameter Extraction from Operating Wind Turbines, SANDIA REPORT, SAND92-1666. UC-261, Sandia National Laboratories.
  16. Juang, J.N. and Pappa, R.S. (1985), "An eigensystem realization algorithm for modal parameters identification and model reduction", J. Guid. Control Dynam., 8(5), 620-627. https://doi.org/10.2514/3.20031
  17. Magalhaes, F., Caetano, E. and Cunha, A.(2007), "Challenges in the application of stochastic modal identification methods to a cable-stayed bridge", J. Bridge Eng., 12(6), 746-754. https://doi.org/10.1061/(ASCE)1084-0702(2007)12:6(746)
  18. Nayeri, R.D., Tasbihgoo, F., Wahbeh, M., Caffrey, J., Masri, S., Conte, J. and Elgamal, A. (2009), "Study of timedomain techniques for modal parameter identification of a long suspension bridgewith dense sensor arrays", J. Eng. Mech. -ASCE, 135(7), 669-683. https://doi.org/10.1061/(ASCE)0733-9399(2009)135:7(669)
  19. Ni, Y.Q., Xia, Y., Liao, W.Y. and Ko, J.M. (2009a), "Technology innovation in developing the structural health monitoring system for Guangzhou New TV Tower", Struct. Control Health Monit., 16(1), 73-98. https://doi.org/10.1002/stc.303
  20. Ni, Y.Q., Zhou, H.F. and Ko, J.M. (2009b), "Generalization capability of neural network models for temperaturefrequency correlation using monitoring data", J. Struct. Eng. - ASCE, 135(10), 1290-1300. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000050
  21. Ni, Y.Q., Xia, Y., Lin, W., Chen, W.H. and Ko, J.M. (2012), "SHM benchmark for high-rise structures: a reducedorder finite element model and field measurement data", Smart Struct. Syst., in this issue.
  22. Niu, Y., Kraemer, P. and Fritzen, C.P. (2011), "Operational Modal Analysis for the Guangzhou New TV Tower", Proceedings of the 29th Int. Modal Analysis Conf. (IMAC), Jacksonville, Florida, USA.
  23. Pappa, R.S. (1999), "Independent analysis of the space station node modal test data", J. Guid. Control Dynam., 22(1), 22-27. https://doi.org/10.2514/2.4366
  24. Pappa, R.S. and Elliott, K.B. (1993), "Consistent-mode indicator for the eigensystem realization algorithm", J. Guid. Control Dynam., 16(5), 852-858. https://doi.org/10.2514/3.21092
  25. Pappa, R.S., James, G.H. and Zimmerman, D.C. (1998), "Autonomous modal identification of the space shuttle tail rudder", J. Spacecraft Rockets, 35(2),163-169. https://doi.org/10.2514/2.3324
  26. Peeters, B. and De Roeck, G. (2001), "One-year monitoring of the Z24-Bridge: environmental effects versus damage events", Earthq. Eng. Struct. D., 30(2), 149-171. https://doi.org/10.1002/1096-9845(200102)30:2<149::AID-EQE1>3.0.CO;2-Z
  27. Prevosto, M. (1982), Algorithmes d'Identification des Caractéristiques Vibratoires de Structures Mecaniques Complexes, Ph.D. Thesis, Univ.de Rennes 1, France.
  28. Sohn, H. (2007), "Effects of environmental and operational variability on structural health monitoring", Philos. T. R. Soc. A., 365(1851), 539-560. https://doi.org/10.1098/rsta.2006.1935
  29. Van Overschee, P. and De Moor, B. (1996), Subspace Identification for Linear Systems: Theory Implementation-Applications, Kluwer Academic, Norwell, Mass.
  30. Vold, H., Kundrat, J., Rocklin, G.T. and Russel, R. (1982), A Multiinput Modal Estimation Algorithm for Minicomputers, Society of Automotive Engineers Technical Paper Series, 91, 815-821.
  31. Xia, Y., Hao, H., Zanardo, G. and Deeks, A. (2006), "Long term vibration monitoring of an RC slab: Temperature and humidity effect", Eng. Struct., 28(3), 441-452. https://doi.org/10.1016/j.engstruct.2005.09.001
  32. Xia, Y., Xu, Y.L., Wei, Z.L., Zhu, H.P. and Zhou, X.Q. (2011), "Variation of structural vibration characteristics versus non-uniform temperature distribution", Eng. Struct., 33(1), 146-153. https://doi.org/10.1016/j.engstruct.2010.09.027
  33. Yun, G. J. (2009), Modal Identification and Damage Detection for Structural Health Monitoring Under Ambient Vibration Environment, 2009 Structures Congress, Austin, Texas.
  34. Zhou, H.F., Ni, Y.Q. and Ko, J.M. (2011a), "Eliminating temperature effect in vibration-based structural damage detection", J. Eng. Mech. - ASCE, 137(12), 785-796. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000273
  35. Zhou, H.F., Ni, Y.Q. and Ko, J.M. (2011b), "Structural damage alarming using auto-associative neural network technique: exploration of environment-tolerant capacity and setup of alarming threshold", Mech. Syst. Signal Pr., 25(5), 1508-1526. https://doi.org/10.1016/j.ymssp.2011.01.005
  36. Zhou, H.F., Ni, Y.Q., Ko, J.M. and Wong, K.Y. (2008), "Modeling of wind and temperature effects on modal frequencies and analysis of relative strength of effect", Wind Struct., 11(1), 35-50. https://doi.org/10.12989/was.2008.11.1.035

Cited by

  1. Structural health monitoring of Shanghai Tower during different stages using a Bayesian approach vol.23, pp.11, 2016, https://doi.org/10.1002/stc.1840
  2. Dynamic displacements-based model updating with motion capture system vol.24, pp.4, 2017, https://doi.org/10.1002/stc.1904
  3. A model updating method with strain measurement from impact test for the safety of steel frame structures vol.102, 2017, https://doi.org/10.1016/j.measurement.2017.02.013
  4. Vision-based system identification technique for building structures using a motion capture system vol.356, 2015, https://doi.org/10.1016/j.jsv.2015.07.011
  5. Online Simultaneous Reconstruction of Wind Load and Structural Responses-Theory and Application to Canton Tower vol.30, pp.8, 2015, https://doi.org/10.1111/mice.12134
  6. Model updating and variability analysis of modal parameters for super high-rise structure pp.15320626, 2018, https://doi.org/10.1002/cpe.4712
  7. Identification of plastic deformations and parameters of nonlinear single-bay frames vol.22, pp.3, 2018, https://doi.org/10.12989/sss.2018.22.3.315
  8. Mono-Component Feature Extraction for Condition Assessment in Civil Structures Using Empirical Wavelet Transform vol.19, pp.19, 2012, https://doi.org/10.3390/s19194280
  9. Ambient Effect Filtering Using NLPCA-SVR in High-Rise Buildings vol.20, pp.4, 2020, https://doi.org/10.3390/s20041143
  10. Improved Automatic Operational Modal Analysis Method and Application to Large-Scale Bridges vol.26, pp.8, 2021, https://doi.org/10.1061/(asce)be.1943-5592.0001756