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Structural Stiffness Identification Based on the Extended Kalman Filter Research

Author

Listed:
  • Fenggang Wang
  • Xianzhang Ling
  • Xun Xu
  • Feng Zhang

Abstract

For the response acquisition of the structure section measuring points, the method of identifying the structural stiffness parameters is developed by using the extended Kalman filter. The state equation of structural system parameter is a nonlinear equation. Dispersing the structural dynamic equation by using Newmark‐β method, the state transition matrix of discrete state equation is deduced and the solution of discrete state equation is simplified. The numerical simulation shows that the error of structural recognition doesnot exceed 5% when the noise level is 3%. It meets the requirements of the error limit of the engineering structure, which indicates that the derivation described in this paper has the robustness for the structural stiffness recognition. Shear structure parameter identification examples illustrate its applicability, and the method can also be used to identify physical parameters of large structure.

Suggested Citation

  • Fenggang Wang & Xianzhang Ling & Xun Xu & Feng Zhang, 2014. "Structural Stiffness Identification Based on the Extended Kalman Filter Research," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:103102
    DOI: 10.1155/2014/103102
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    References listed on IDEAS

    as
    1. Shuping He, 2013. "Resilient - Filtering of Uncertain Markovian Jumping Systems within the Finite-Time Interval," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-7, April.
    2. Shuping He & Fei Liu, 2012. "Adaptive Observer‐Based Fault Estimation for Stochastic Markovian Jumping Systems," Abstract and Applied Analysis, John Wiley & Sons, vol. 2012(1).
    3. Shuping He & Fei Liu, 2012. "Adaptive Observer-Based Fault Estimation for Stochastic Markovian Jumping Systems," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-11, July.
    4. Shuping He, 2013. "Resilient L2‐L∞ Filtering of Uncertain Markovian Jumping Systems within the Finite‐Time Interval," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    Full references (including those not matched with items on IDEAS)

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