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Self-reference broadband local wavenumber estimation (SRB-LWE) for defect assessment in composites

Joost Segers (UGent) , Saeid Hedayatrasa (UGent) , Gaétan Poelman (UGent) , Wim Van Paepegem (UGent) and Mathias Kersemans (UGent)
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Abstract
Local wavenumber estimation (LWE) applied to a full wavefield response is a powerful approach for detecting and characterizing defects in a composite structure. However, the narrowband nature of the traditional LWE techniques brings several challenges for application on actual test cases. This study proposes a self-reference broadband version of the LWE technique. The broadband vibrations are injected using low-power piezoelectric actuators (sine sweep signal) or using pulsed laser excitation in the thermoelastic regime. The out-of-plane velocity response of the surface is recorded using an infrared scanning laser Doppler vibrometer. The dispersive Lamb wave behavior, corresponding to the damage-free base material, is identified from the broadband vibrational response. Using the identified dispersion curves (i.e. self-reference approach), a Lamb mode passband filter bank in the wavenumber-frequency domain is constructed. Searching for the maximum bandpower density in function of the assumed material thickness provides a robust estimate of the effective local thickness of the tested component, and as such yields a detection and evaluation of damage. The performance of the self-reference broadband LWE algorithm is demonstrated on aluminum plates with various flat bottom holes, as well as on cross-ply CFRP aircraft components with a stiffener disbond and barely visible impact damage. Compared to the traditional narrowband LWE approaches, the proposed self-reference broadband LWE method allows a higher level of automation, removes the need for a priori knowledge on the material and/or defect properties, and results in an improved characterization of defects.
Keywords
Composites, Non-destructive testing (NDT), Self-reference broadband local wavenumber estimation, Depth quantification, Scanning laser Doppler vibrometry, Guided waves, EXCITATION, DAMAGE, IDENTIFICATION

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MLA
Segers, Joost, et al. “Self-Reference Broadband Local Wavenumber Estimation (SRB-LWE) for Defect Assessment in Composites.” MECHANICAL SYSTEMS AND SIGNAL PROCESSING, vol. 163, 2022, doi:10.1016/j.ymssp.2021.108142.
APA
Segers, J., Hedayatrasa, S., Poelman, G., Van Paepegem, W., & Kersemans, M. (2022). Self-reference broadband local wavenumber estimation (SRB-LWE) for defect assessment in composites. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 163. https://doi.org/10.1016/j.ymssp.2021.108142
Chicago author-date
Segers, Joost, Saeid Hedayatrasa, Gaétan Poelman, Wim Van Paepegem, and Mathias Kersemans. 2022. “Self-Reference Broadband Local Wavenumber Estimation (SRB-LWE) for Defect Assessment in Composites.” MECHANICAL SYSTEMS AND SIGNAL PROCESSING 163. https://doi.org/10.1016/j.ymssp.2021.108142.
Chicago author-date (all authors)
Segers, Joost, Saeid Hedayatrasa, Gaétan Poelman, Wim Van Paepegem, and Mathias Kersemans. 2022. “Self-Reference Broadband Local Wavenumber Estimation (SRB-LWE) for Defect Assessment in Composites.” MECHANICAL SYSTEMS AND SIGNAL PROCESSING 163. doi:10.1016/j.ymssp.2021.108142.
Vancouver
1.
Segers J, Hedayatrasa S, Poelman G, Van Paepegem W, Kersemans M. Self-reference broadband local wavenumber estimation (SRB-LWE) for defect assessment in composites. MECHANICAL SYSTEMS AND SIGNAL PROCESSING. 2022;163.
IEEE
[1]
J. Segers, S. Hedayatrasa, G. Poelman, W. Van Paepegem, and M. Kersemans, “Self-reference broadband local wavenumber estimation (SRB-LWE) for defect assessment in composites,” MECHANICAL SYSTEMS AND SIGNAL PROCESSING, vol. 163, 2022.
@article{8714075,
  abstract     = {{Local wavenumber estimation (LWE) applied to a full wavefield response is a powerful approach for detecting and characterizing defects in a composite structure. However, the narrowband nature of the traditional LWE techniques brings several challenges for application on actual test cases. This study proposes a self-reference broadband version of the LWE technique. The broadband vibrations are injected using low-power piezoelectric actuators (sine sweep signal) or using pulsed laser excitation in the thermoelastic regime. The out-of-plane velocity response of the surface is recorded using an infrared scanning laser Doppler vibrometer. The dispersive Lamb wave behavior, corresponding to the damage-free base material, is identified from the broadband vibrational response. Using the identified dispersion curves (i.e. self-reference approach), a Lamb mode passband filter bank in the wavenumber-frequency domain is constructed. Searching for the maximum bandpower density in function of the assumed material thickness provides a robust estimate of the effective local thickness of the tested component, and as such yields a detection and evaluation of damage. The performance of the self-reference broadband LWE algorithm is demonstrated on aluminum plates with various flat bottom holes, as well as on cross-ply CFRP aircraft components with a stiffener disbond and barely visible impact damage. Compared to the traditional narrowband LWE approaches, the proposed self-reference broadband LWE method allows a higher level of automation, removes the need for a priori knowledge on the material and/or defect properties, and results in an improved characterization of defects.}},
  articleno    = {{108142}},
  author       = {{Segers, Joost and Hedayatrasa, Saeid and Poelman, Gaétan and Van Paepegem, Wim and Kersemans, Mathias}},
  issn         = {{0888-3270}},
  journal      = {{MECHANICAL SYSTEMS AND SIGNAL PROCESSING}},
  keywords     = {{Composites,Non-destructive testing (NDT),Self-reference broadband local wavenumber estimation,Depth quantification,Scanning laser Doppler vibrometry,Guided waves,EXCITATION,DAMAGE,IDENTIFICATION}},
  language     = {{eng}},
  pages        = {{19}},
  title        = {{Self-reference broadband local wavenumber estimation (SRB-LWE) for defect assessment in composites}},
  url          = {{http://doi.org/10.1016/j.ymssp.2021.108142}},
  volume       = {{163}},
  year         = {{2022}},
}

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