Identification of the beam vibration parameters by Rayleigh method
Email:
nhhunggttp@utc.edu.vn
Keywords:
Natural vibration frequency, modal participating stiffness, modal participating mass, mode shape function, Reyleigh method.
Abstract
The current test and load-carrying test of bridge mainly receives the natural vibration frequency, deflection and strain of the bridge structure. This result immediately used to assess the current state of the bridge structure or stored to assess the bridge condition in the future. Of the above three results, only the natural vibration frequency of bridge is the parameter independent of external loads, so it is convenient to assess the bridge condition. The natural vibration frequency is made up of two main parameters which are the modal participating stiffness of the structure and the modal participating mass in that frequency. In order to better understand the behavior of beams, the paper proceeds to determine the actual modal participating stiffness, the modal participating mass of the beam and the mode shape function corresponding to this vibration case. The paper using Rayleigh method analyzed for simply supported beam case, the results modal participating mass and stiffness obtained by the proposed method are compared with the original assumptions and received high reliability results.References
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[2] T. Kijewski, A. Kareem, Wavelet transform for system identification in Civil Engineering, Computer-Aided Civil and Infrastructure Engineering, 18 (2003) 339-355. https://doi.org/10.1111/1467-8667.t01-1-00312
[3] J. Chen, Y.L. Xu, R.C. Zhang, Modal parameter identification of Tsing Ma suspension bridge under Typhoon Victor: EMD-HT method, Journal of Wind Engineering and Industrial Aerodynamics, 92 (2004) 805–827. https://doi.org/10.1016/j.jweia.2004.04.003
[4] Joo Sung Kang, Seung-Keun Park, Soobong Shin, Hae Sung Lee, Structural system identification in time domain using measured acceleration, Journal of Sound and Vibration, 288 (2005) 215–234. https://doi.org/10.1016/j.jsv.2005.01.041
[5] B.F. Yan, A. Miyamoto, E. Bruhwiler, Wavelet transform-based modal parameter identification considering uncertainty, Journal of Sound and Vibration, 291 (2006) 285–301. https://doi.org/10.1016/j.jsv.2005.06.005
[6] Banfu Yan, Ayaho Miyamoto, A Comparative Study of Modal Parameter Identification Based on Wavelet and Hilbert–Huang Transforms, Computer-Aided Civil and Infrastructure Engineering, 21 (2006) 9–23. https://doi.org/10.1111/j.1467-8667.2005.00413.x.
[7] Michael Feldman, Identification of weakly nonlinearities in multiple coupled oscillators, Journal of Sound and Vibration, 303 (2007) 357–370. https://doi.org/10.1016/j.jsv.2007.01.028
[8] P. Frank Pai, Anthony N. Palazotto, HHT-based nonlinear signal processing method for parametric and non-parametric identification of dynamical systems, International Journal of Mechanical Sciences, 50 (2008) 1619–1635. https://doi.org/10.1016/j.ijmecsci.2008.10.001
[9] Michael Feldman, Izhak Bucher, Joseph Rotberg, Experimental Identification of Nonlinearities under Free and Forced Vibration using the Hilbert Transform, Journal of Vibration and Control, 15 (2009) 1563-1579. https://doi.org/10.1177/1077546308097270
[10] H.A. Nasrellah, C.S. Manohar, A particle filtering approach for structural system identification in vehicle–structure interaction problems, Journal of Sound and Vibration 329 (2010) 1289–1309. https://doi.org/10.1016/j.jsv.2009.10.041
[11] Te-Yu Liu, Wei-Ling Chiang, Cheng-Wu Chen, Wen-Ko Hsu, Chi-Wei Lin, Dong-Jiang Chiou and Pei-Chun Huang, Structural system identification for vibration bridges using the Hilbert–Huang transform, Journal of Vibration and Control, 18 (2011) 1939-1956. https://doi.org/10.1177/1077546311428347
[12] R. W. Clough, J. Penzien, Dynamics of structures, Computers & Structures, Inc. , Berkeley, CA 94704, 2003.
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Received
01/10/2019
Revised
14/11/2019
Accepted
18/11/2019
Published
16/12/2019
Type
Research Article
How to Cite
Nguyễn Hữu, H., & Đàm Minh, H. (1576429200). Identification of the beam vibration parameters by Rayleigh method. Transport and Communications Science Journal, 70(4), 320-329. https://doi.org/10.25073/tcsj.70.4.19
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