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NONLINEAR VIBRATION SIGNAL TRACKING OF LARGE OFFSHORE BRIDGE STAYED CABLE BASED ON PARTICLE FILTER

Abstract

The stayed cables are key stress components of large offshore bridge. The fault detection of stayed cable is very important for safe of large offshore bridge. A particle filter model and algorithm of nonlinear vibration signal are used in this paper. Firstly, the particle filter model of stayed cable of large offshore bridge is created. Nonlinear dynamic model of the stayed-cable and beam coupling system is dispersed in temporal dimension by using the finite difference method. The discrete nonlinear vibration equations of any cable element are worked out. Secondly, a state equation of particle filter is fitted by least square algorithm from the discrete nonlinear vibration equations. So the particle filter algorithm can use the accurate state equations. Finally, the particle filter algorithm is used to filter the vibration signal of bridge stayed cable. According to the particle filter, the de-noised vibration signal can be tracked and be predicted for a short time accurately. Many experiments are done at some actual bridges. The simulation experiments and the actual experiments on the bridge stayed cables are all indicating that the particle filter algorithm in this paper has good performance and works stably.

Keywords:

nonlinear vibration of stayed cables, large offshore bridge, particle filter, signal tracking

Details

Issue
Vol. 22 No. 4(88) (2015)
Section
Latest Articles
Published
30-12-2015
DOI:
https://doi.org/10.1515/pomr-2015-0074
Licencja:
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Open Access License

This journal provides immediate open access to its content under the Creative Commons BY 4.0 license. Authors who publish with this journal retain all copyrights and agree to the terms of the CC BY 4.0 license.

 

Authors

  • Qingwei Ye

    Ningbo University
  • Zhimin Feng

    Ningbo University
  • Debin Yuan

    Ningbo University

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