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Modal parameter identification in civil structures via Hilbert transform ensemble with improved empirical wavelet transform

Shiqiang Qin, Jian Tang, Jiacheng Feng, Yunlai Zhou, Fei Yang and Magd Abdel Wahab (UGent)
(2024) JOURNAL OF VIBRATION AND CONTROL.
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Abstract
To overcome the inaccurate frequency band division in empirical wavelet transform (EWT) induced by high noise and modulation edge band, this study proposes an improved EWT (IEWT) and applies it to operational modal analysis (OMA) in civil structures. The IEWT segments the frequency band using spectral trend determined with removing the high-frequency components of the Fourier spectrum. The synchroextracting transform is employed to denoise the frequency components obtained from IEWT combined with the random decrement technique and Hilbert transform to identify modal parameters. The effectiveness of IEWT and the proposed modal analysis method is comprehensively verified by a full-scale cable-stayed footbridge. The results demonstrate that the proposed IEWT, random decrement technique, and Hilbert transform can accurately identify the modal parameters from multi-setup ambient vibration measurements.
Keywords
Mechanical Engineering, Mechanics of Materials, Aerospace Engineering, Automotive Engineering, General Materials Science, Operational modal analysis, empirical wavelet transform, spectrum, segmentation, synchroextracting transform, Hilbert transform

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Citation

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MLA
Qin, Shiqiang, et al. “Modal Parameter Identification in Civil Structures via Hilbert Transform Ensemble with Improved Empirical Wavelet Transform.” JOURNAL OF VIBRATION AND CONTROL, 2024, doi:10.1177/10775463231166428.
APA
Qin, S., Tang, J., Feng, J., Zhou, Y., Yang, F., & Abdel Wahab, M. (2024). Modal parameter identification in civil structures via Hilbert transform ensemble with improved empirical wavelet transform. JOURNAL OF VIBRATION AND CONTROL. https://doi.org/10.1177/10775463231166428
Chicago author-date
Qin, Shiqiang, Jian Tang, Jiacheng Feng, Yunlai Zhou, Fei Yang, and Magd Abdel Wahab. 2024. “Modal Parameter Identification in Civil Structures via Hilbert Transform Ensemble with Improved Empirical Wavelet Transform.” JOURNAL OF VIBRATION AND CONTROL. https://doi.org/10.1177/10775463231166428.
Chicago author-date (all authors)
Qin, Shiqiang, Jian Tang, Jiacheng Feng, Yunlai Zhou, Fei Yang, and Magd Abdel Wahab. 2024. “Modal Parameter Identification in Civil Structures via Hilbert Transform Ensemble with Improved Empirical Wavelet Transform.” JOURNAL OF VIBRATION AND CONTROL. doi:10.1177/10775463231166428.
Vancouver
1.
Qin S, Tang J, Feng J, Zhou Y, Yang F, Abdel Wahab M. Modal parameter identification in civil structures via Hilbert transform ensemble with improved empirical wavelet transform. JOURNAL OF VIBRATION AND CONTROL. 2024;
IEEE
[1]
S. Qin, J. Tang, J. Feng, Y. Zhou, F. Yang, and M. Abdel Wahab, “Modal parameter identification in civil structures via Hilbert transform ensemble with improved empirical wavelet transform,” JOURNAL OF VIBRATION AND CONTROL, 2024.
@article{01H5SZCDSKK4KQS52EHF7C7AS0,
  abstract     = {{To overcome the inaccurate frequency band division in empirical wavelet transform (EWT) induced by high noise and modulation edge band, this study proposes an improved EWT (IEWT) and applies it to operational modal analysis (OMA) in civil structures. The IEWT segments the frequency band using spectral trend determined with removing the high-frequency components of the Fourier spectrum. The synchroextracting transform is employed to denoise the frequency components obtained from IEWT combined with the random decrement technique and Hilbert transform to identify modal parameters. The effectiveness of IEWT and the proposed modal analysis method is comprehensively verified by a full-scale cable-stayed footbridge. The results demonstrate that the proposed IEWT, random decrement technique, and Hilbert transform can accurately identify the modal parameters from multi-setup ambient vibration measurements.}},
  author       = {{Qin, Shiqiang and Tang, Jian and Feng, Jiacheng and Zhou, Yunlai and Yang, Fei and Abdel Wahab, Magd}},
  issn         = {{1077-5463}},
  journal      = {{JOURNAL OF VIBRATION AND CONTROL}},
  keywords     = {{Mechanical Engineering,Mechanics of Materials,Aerospace Engineering,Automotive Engineering,General Materials Science,Operational modal analysis,empirical wavelet transform,spectrum,segmentation,synchroextracting transform,Hilbert transform}},
  language     = {{eng}},
  title        = {{Modal parameter identification in civil structures via Hilbert transform ensemble with improved empirical wavelet transform}},
  url          = {{http://doi.org/10.1177/10775463231166428}},
  year         = {{2024}},
}
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