DOI QR코드

DOI QR Code

Modal parameters identification of heavy-haul railway RC bridges - experience acquired

  • Sampaio, Regina (Faculty of Civil Engineering, Federal University of Para - UFPA) ;
  • Chan, Tommy H.T. (Faculty of Science and Engineering, Queensland University of Technology - QUT)
  • 투고 : 2015.01.09
  • 심사 : 2015.03.05
  • 발행 : 2015.03.25

초록

Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Caraj$\acute{a}$s railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

키워드

참고문헌

  1. Brincker, R. (2000), "Modal identification from ambient responses using frequency domain decomposition", Proceedings of the IMAC-XVIII: Conference on Structural Dynamics, San Antonio, Texas, USA, February.
  2. Brinker, R., Zhang, L. and Anderson, P. (2001), "Modal identification of output-only systems using frequency domain decomposition", Smart Mater. Struct., 10, 441-445. https://doi.org/10.1088/0964-1726/10/3/303
  3. Herlufsen, H., Andersen, P., Gade, S. and Moller, N. (2006), "Identification techniques for operational modal analysis - an overview and practical experiences", Proceedings of the IMAC-XXIV: Conference on Structural Dynamics, St Louis, Missouri, USA, January.
  4. Jacobsen, N.J., Andersen, P. and Brincker, R. (2007), "Eliminating the influence of harmonic components in operational modal analysis", Proceedings of the IMAC-XXV: Conference and exposition on Structural Dynamics, Orlando, Florida, USA, February.
  5. Lee, C.H., Kawatanib, M., Kim, C.W., Nishimura, N. and Kobayashi, Y. (2006), "Dynamic response of a monorail steel bridge under a moving train", J. Sound Vib., 294, 562-579. https://doi.org/10.1016/j.jsv.2005.12.028
  6. 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
  7. Nguyen, T., Chan, T.H.T. and Thambiratnam, D.P. (2014a), "Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests", In PLSE special issue - Adv. Struct. Eng., 17(3), (in press).
  8. Nguyen, T., Chan, T.H.T. and Thambiratnam, D.P. (2014b), "Effects of wireless sensor network uncertainties on output-only modal-based damage identification", Aus. J. Struct. Eng., 15(1), 15-25.
  9. Peeters, B. (2000), System Identification an Damage detection in Civil Engineering, Ph.D. Thesis, Katholieke Universiteit Leuven, Leuven, Belgium.
  10. Pfeil, W. (1989), Pontes em Concreto Armado, LPC Editora, Rio de Janeiro, RJ, Brazil (in Portuguese).
  11. 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
  12. Shih W.W., Thambiratnam D.P. and Chan T.H.T. (2011), "Damage detection in truss bridges using vibration based multi-criteria approach", Struct. Eng. Mech., 39(2), 187-206. https://doi.org/10.12989/sem.2011.39.2.187
  13. SVS (2011), ARTeMIS Extractor release 5.3, User's manual. Structural Vibration Solutions A/S.
  14. 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
  15. 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

피인용 문헌

  1. Numerical and experimental investigation for damage detection in FRP composite plates using support vector machine algorithm vol.5, pp.2, 2015, https://doi.org/10.12989/smm.2018.5.2.243
  2. Research on Mechanical Performance of Improved Low Vibration Track and Its Feasibility Analysis for Heavy-Haul Railway Applications vol.11, pp.21, 2015, https://doi.org/10.3390/app112110232