Identification of modal parameters based on moving load excitation

Yi Liu*, John Macdonald, Dario Di Maio

*Corresponding author for this work

Research output: Contribution to journalConference articleAcademicpeer-review

5 Citations (Scopus)
79 Downloads (Pure)

Abstract

It is often desired to measure the model parameters of bridges, but normally the forcing function cannot be measured so it is necessary to use output-only system identification methods. A moving vehicle provides a force on a bridge that could be used for input-output analysis, which could be superior, but the force varies in space as well as time, so existing system identification methods are not directly applicable. To address this issue, this paper proposes a new strategy to use the moving load response to identify the modal parameters. A numerically simulated simply supported Euler-Bernoulli beam of known parameters is used as an example case to test the validity of the approach. Frequency Domain Decomposition is first implemented to extract the mode shapes from the simulated acceleration responses. Then, by applying the mode superposition method, the simulated force and acceleration responses are transformed into modal space. The accelerances of five modes are then processed using the Levenberg-Marquardt method such that the three unknown parameters, namely natural frequency, damping ratio, and modal mass, of each mode are determined simultaneously. The effectiveness of the proposed method is validated by the low percentage errors (less than 1.7%) for all three identified modal parameters compared to their actual values for four of the five modes.

Original languageEnglish
Pages (from-to)960-965
Number of pages6
JournalProcedia engineering
Volume199
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event10th International Conference on Structural Dynamics, EURODYN 2017 - Rome, Italy
Duration: 10 Sep 201713 Sep 2017
Conference number: 10

Keywords

  • Inout-output
  • Modal mass
  • Mode superpositon
  • Moving vehicle
  • System identification

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