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Improved Bayesian Model Updating Method for Frequency Response Function with Metrics Utilizing NHBFT-PCA

Author

Listed:
  • Jinhui Li

    (School of Aerospace Engineering, Xiamen University, Xiamen 361000, China)

  • Zhenhong Deng

    (School of Aerospace Engineering, Xiamen University, Xiamen 361000, China)

  • Yong Tang

    (AECC Hunan Aviation Powerplant Research Institute, Zhuzhou 412002, China
    AECC Key Laboratory of Aero-Engine Vibration Technology, Zhuzhou 412002, China)

  • Siqi Wang

    (School of Aerospace Engineering, Xiamen University, Xiamen 361000, China)

  • Zhe Yang

    (School of Aerospace Engineering, Xiamen University, Xiamen 361000, China)

  • Huageng Luo

    (School of Aerospace Engineering, Xiamen University, Xiamen 361000, China)

  • Wujun Feng

    (School of Aerospace Engineering, Xiamen University, Xiamen 361000, China)

  • Baoqiang Zhang

    (School of Aerospace Engineering, Xiamen University, Xiamen 361000, China)

Abstract

To establish a high-fidelity model of engineering structures, this paper introduces an improved Bayesian model updating method for stochastic dynamic models based on frequency response functions (FRFs). A novel validation metric is proposed first within the Bayesian theory by using the normalized half-power bandwidth frequency transformation (NHBFT) and the principal component analysis (PCA) method to process the analytical and experimental frequency response functions. Subsequently, traditional Bayesian and approximate Bayesian computation (ABC) are improved by integrating NHBFT-PCA metrics for different application scenarios. The efficacy of the improved Bayesian model updating method is demonstrated through a numerical case involving a three-degrees-of-freedom system and the experimental case of a bolted joint lap plate structure. Comparative analysis shows that the improved method outperforms conventional methods. The efforts of this study provide an effective and efficient updating method for dynamic model updating based on the FRFs, addressing some of the existing challenges associated with FRF-based model updating.

Suggested Citation

  • Jinhui Li & Zhenhong Deng & Yong Tang & Siqi Wang & Zhe Yang & Huageng Luo & Wujun Feng & Baoqiang Zhang, 2024. "Improved Bayesian Model Updating Method for Frequency Response Function with Metrics Utilizing NHBFT-PCA," Mathematics, MDPI, vol. 12(13), pages 1-20, July.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:2076-:d:1427791
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    References listed on IDEAS

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    1. Anirban Mondal & Jia Wei, 2021. "Bayesian Uncertainty Quantification for Channelized Reservoirs via Reduced Dimensional Parameterization," Mathematics, MDPI, vol. 9(9), pages 1-25, May.
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