Bridge Frequency Identification Using a Multi-DOF Test Vehicle by Nodal Distribution Method and Enhanced Integration Algorithm

  • Yang, Yeong-Bin (Chongqing University)
  • Mo, Xiangqian (Chongqing University)
  • Shi, Kang (Chongqing University)

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It was demonstrated that the bridge dynamic properties can be detected by a test vehicle moving over the bridge [1]. To reflect the real vehicles mostly used in railways, this lecture presents a general procedure for calculating the multi contact responses and for identifying bridge frequencies from an instrumented multi-DOF vehicle. The vehicle contains a car body, two bogies and four wheelsets, connecting by the two-layer dashpots. Two key steps are involved. First, the nodal distribution method was devised for distributing the vehicle’s responses to those of the four wheelsets. Then by treating the wheelset as a single-DOF system, the contact response is calculated exactly by the enhanced integration algorithm for each time step. Two scenarios are studied. In Scenario 1, the vehicle is kept stationary on the rails, but excited differently via the contact points, by which the transmission of vibration from the wheelsets up to the vehicle components and down again by the present method is validated. In Scenario 2, the vehicle is set to move over a simple bridge, by which the contact responses are shown to outperform the vehicle’s responses in extracting the bridge frequencies, due to the fact that the vehicle’s frequencies were totally eliminated. In addition, the present method has been demonstrated to be of excellent accuracy, efficiency and robustness in each application [2]. REFERENCES [1] Y.B. Yang, C.W. Lin, and J.D. Yau. Extracting bridge frequencies from the dynamic response of a passing vehicle. Journal of Sound and Vibration, 272(3-5), 471-493, 2004. [2] Y.B. Yang, X.Q. Mo, K. Shi, S.Y. Gao and S.K. Tian. Bridge frequency identification using multi-contact responses computed from multi-DOF moving vehicle by nodal distribution method and enhanced integration algorithm. Computers and Structures, 299, 107397, 2024.