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Damping and frequency changes induced by increasing levels of inelastic seismic demand

  • Aguirre, Diego A. (Department of Civil Engineering and Surveying, University of Puerto Rico at Mayaguez) ;
  • Montejo, Luis A. (Department of Engineering Science and Materials, University of Puerto Rico at Mayaguez)
  • Received : 2013.03.05
  • Accepted : 2014.04.29
  • Published : 2014.09.25

Abstract

The objective in this research is to determine the feasibility of using changes on the dynamic properties of a reinforced concrete (RC) structure to identify different levels of seismic induced damage. Damping ratio and natural frequency changes in a RC bridge column are analyzed using different signal processing techniques like Hilbert Transforms, Random Decrement and Wavelet Transforms. The data used in the analysis was recorded during a full-scale RC bridge column shake table test. The structure was subjected to ten earthquake excitations that induced different levels of inelastic demand on the column. In addition, low-intensity white noises were applied to the column in-between earthquakes. The results obtained show that the use of the damping ratio and natural frequency of vibration as damage indicators is arguable.

Keywords

References

  1. Aguirre, D.A., Gaviria, C.A. and Montejo, L.A. (2013), "Wavelet based damage detection in reinforced concrete structures subjected to seismic excitations", J. Earthq. Eng., 17(8), 1103-1125. https://doi.org/10.1080/13632469.2013.804467
  2. Al Sanad, H., Aggour, M.S. and Yang, J.C.S. (1983), "Dynamic shear modulus and damping ratio from random loading tests", Geotech. Test. J., 6(3), 120-127. https://doi.org/10.1520/GTJ10840J
  3. Banks, H.T., Inman, D.J., Leo, D.J. and Wang, Y. (1996), "An experimentally validated damage detection theory in smart structures", J. Sound Vib., 191(5), 859-880. https://doi.org/10.1006/jsvi.1996.0160
  4. Brincker, R., Krenk, S. and Jensen, J.L. (1991), "Estimation of correlation functions by the random decrement technique", Proceedings of the Florence Modal Analysis Conference, Florence, Italy.
  5. Celebi, M., Okawa, I. and Kashima, T. (2012), "March 11, 2011 m=9.0 great east japan earth-quake: the story of a retrofitted building damaged and repaired", Proceedings of the 15th WCEE, Lisbon, Portugal, September.
  6. Chen, S.L., Liu, J.J. and Lai, H.C. (2009), "Wavelet analysis for identification of damping ratios and natural frequencies", J. Sound Vib., 323(1-2), 130-147. https://doi.org/10.1016/j.jsv.2009.01.029
  7. Curadelli, R.O., Riera, J.D., Ambrosini, D. and Amani, M.G. (2008), "Damage detection by means of structural damping identification", Eng. Struct., 30(12), 3497-3504. https://doi.org/10.1016/j.engstruct.2008.05.024
  8. Daubuchies, I., Lu, J., Wu, H.T. (2011), "Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool", Appl. Comput. Harmon. A., 30(2), 243-261. https://doi.org/10.1016/j.acha.2010.08.002
  9. Feldman, M. (2006), "Time varying vibration decomposition and analysis based on the Hilbert transform", J. Sound Vib., 295(3-5), 518-530. https://doi.org/10.1016/j.jsv.2005.12.058
  10. Feldman, M. (2011), "Hilbert transform in vibration analysis", Mech. Syst. Signal. Pr., 25(3), 735-802. https://doi.org/10.1016/j.ymssp.2010.07.018
  11. Feldman, M. (2011), Hilbert Transform Applications in Mechanical Vibration, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom.
  12. Gabor, D. (1946), "Theory of communication", Proceedings of the IEEE 93(III), 429-457.
  13. Grossman, A. and Morlet, J. (1990), Decompositions of functions into wavelets of constant shape and related transforms, Mathematics and Physics - Lecture on Recent Results, World Scientific, Singapore, 135-65.
  14. Hahn, S.L. (1996), Hilbert Transforms in Signal Processing, Artech House (print-on-demand).
  15. Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.C., Tung, C.C. and Liu, H.H. (1998), "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis", Philos. T. R. Soc. London A, 454, 903-995. https://doi.org/10.1098/rspa.1998.0193
  16. Kareem, A. and Gurley, K. (1996), "Damping in structures: its evaluation and treatment of uncertainty", J. Wind Eng. Ind. Aerod., 59(2-3), 131-157. https://doi.org/10.1016/0167-6105(96)00004-9
  17. Kawiecki, G. (2001), "Modal damping measurement for damage detection", Smart Mater. Struct., 10(3), 466-471. https://doi.org/10.1088/0964-1726/10/3/307
  18. Kijewski-Correa, T.L. (2003), Full-scale measurements and system identification: a time-frequency perspective, Ph.D. Dissertation, University of Notre Dame, Notre Dame, Indiana.
  19. Kijewski, T. and Kareem, A. (2003), "Wavelet transforms for system identification in civil engineering", Comput.-Aided Civil. Infrastruct. Eng., 18(5), 339-355. https://doi.org/10.1111/1467-8667.t01-1-00312
  20. Kullaa, J. (2003), "Damage detection of the z24 bridge using control charts", Mech. Syst. Signal. Pr., 17(1), 163-170. https://doi.org/10.1006/mssp.2002.1555
  21. Lardies, J. and Gouttebroze, S. (2002), "Identification of modal parameters using the Wavelet transform", Int. J. Mech. Sci., 44(11), 2263-2283. https://doi.org/10.1016/S0020-7403(02)00175-3
  22. Le, T.P. and Argoul, P. (2004), "Continuous Wavelet Transform for modal identification using free decay response", J. Sound Vib., 277, 73-100. https://doi.org/10.1016/j.jsv.2003.08.049
  23. Le, T.P. and Paultre, P. (2012), "Modal identification based on continuous wavelet transform and ambient excitation tests", J. Sound Vib., 331(9), 2023-2037. https://doi.org/10.1016/j.jsv.2012.01.018
  24. Lin, C.S. and Chiang, D.Y. (2012), "A modified random decrement technique for modal identification from nonstationary ambient response data only", J. Mech. Sci. Technol., 26(6), 1687-1696. https://doi.org/10.1007/s12206-012-0414-7
  25. Loh, C.H., Mao C.H., Huang, J.R. and Pan, T.C. (2011), "System identification and damage evaluation of degrading hysteresis of reinforced concrete frames", Earthq. Eng. Struct. D., 40(6), 623-640. https://doi.org/10.1002/eqe.1051
  26. McKenna, F., Fenves, G.L., Scott, M.H. and Jeremic, B. (2000), "Open system for earthquake engineering simulation - opensees", http://opensees.berkeley.edu
  27. Michel, C. and Gueguen, P. (2010), "Time-frequency analysis of small frequency variations in civil engineering structures under weak and strong motions using a reassignment method", Struct. Health Monit., 9(2), 159-171. https://doi.org/10.1177/1475921709352146
  28. Montejo, L.A. (2011), "Signal processing based damage detection in structures subjected to random excitations", Struct. Eng. Mech., 40(6), 745-762. https://doi.org/10.12989/sem.2011.40.6.745
  29. Montejo, L.A., Velazquez, L.R., Ramirez, R.I., Jiang, Z. and Christenson, R.E. (2012), "Frequency content effect on the efficiency of wavelet and hilbert-huang transforms for health monitoring", Proceedings of the 15th WCEE, Lisbon, Portugal, September.
  30. Montejo, L.A. and Vidot, A.L. (2012), "Synchrosqueezed wavelet transform for frequency and damping identification from noisy signals", Smart Struct. Syst., 9(5), 441-459. https://doi.org/10.12989/sss.2012.9.5.441
  31. Park, Y. J. and Ang, A. H. S. (1985), "Mechanistic seismic damage model for reinforced concrete", J. Struct. Eng. - ASCE, 111(4), 722-739. https://doi.org/10.1061/(ASCE)0733-9445(1985)111:4(722)
  32. Ramirez-Castro, R.I. and Montejo, L.A. (2011), "Hilbert Transform, empirical mode decomposition and its applications to free vibration analysis (in spanish)", RevistaInternacional de DesastresNaturales, Accidentes e Infraestructura Civil, 11 (2), 123-134.
  33. Ruzzene, M. Fasana, A., Garibaldi, L. and Piombo, B. (1997), "Natural frequencies and dampings identification using Wavelet Transform: application to real data", Mech. Syst. Signal. Pr., 11(2), 207-218. https://doi.org/10.1006/mssp.1996.0078
  34. Salawu, O.S. (1997), "Detection of structural damage through changes in frequency: a review", Eng. Struct., 19(9), 718-723. https://doi.org/10.1016/S0141-0296(96)00149-6
  35. Schoettler, M.J., Restrepo, J.I., Guerrini, G., Duck, D.E. and Carrea, F. (2012), A full-scale, single-column bridge bent tested by shake-table excitation, Center for Civil Engineering Earthquake Research, Department of Civil Engineering, University of Nevada.
  36. Shi, W., Shan, J. and Lu, X. (2012), "Modal identification of Shanghai World Financial Center both from free and ambient vibration response", Eng. Struct., 36, 14-26. https://doi.org/10.1016/j.engstruct.2011.11.025
  37. Staszewski, W.J. (1997), "Identification of damping in mdof systems using time-scale decomposition", J. Sound Vib., 203(2), 283-305. https://doi.org/10.1006/jsvi.1996.0864
  38. Todorovska, M.I. and Trifunac, M.D. (2007), "Earthquake damage detection in the imperial county services building I: the data and time frequency analysis", Soil Dyn. Earthq. Eng., 27(6), 564-576. https://doi.org/10.1016/j.soildyn.2006.10.005
  39. Ulker-Kaustell, M. and Karoumi, R. (2011), "Application of the continuous wavelet transform on the free vibrations of a steel-concrete composite Railway Bridge", Eng. Struct., 33(3), 911-919. https://doi.org/10.1016/j.engstruct.2010.12.012
  40. Ville, J. (1948), "Theorie et application de la notion de signal analytical (in French)", Cables et Transmissions, 2(1), 61-74.
  41. Yan, B. and Miyamoto, A. (2006), "A comparative study of modal parameter identification based on Wavelet and Hilbert-Huang transforms", Comput.-Aided Civil. Infrastruct. Eng., 21(1), 9-23.
  42. Zembaty, Z., Kowalski, M. and Pospisil, S. (2006), "Dynamic identification of a reinforced concrete frame in progressive states of damage", Eng.Struct., 28(5), 668-681. https://doi.org/10.1016/j.engstruct.2005.09.025

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