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Automated extraction of local defect resonance for efficient non-destructive testing of composites

Joost Segers (UGent) , Erik Verboven (UGent) , Saeid Hedayatrasa (UGent) , Gaétan Poelman (UGent) , Wim Van Paepegem (UGent) and Mathias Kersemans (UGent)
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Abstract
Local defect resonance (LDR) makes use of high frequency vibrations to get a localized resonant activation of the defect. One of the major difficulties with respect to the use of LDR for non-destructive testing is the actual identification of the LDR frequency. In this study, different post-processing methods are applied to broadband vibration data, obtained for a carbon fiber reinforced plastic with a flat bottom hole, in view of automated extraction of LDR features. Results are shown and discussed in the frequency domain. In order to reduce the computational effort for large datasets, principle component analysis (PCA) and frequency band data (FBD) calculation are investigated. The effect on the calculation time and the data size is investigated. Moreover, a signal-to-noise ratio is introduced to investigate the performance of both techniques with respect to the automated LDR detection algorithm. Finally, the effect of a reduced sampling is investigated with respect to the performance of the automated LDR extraction procedure.
Keywords
Non-destructive testing, local defect resonance, laser Doppler vibrometry

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Chicago
Segers, Joost, Erik Verboven, Saeid Hedayatrasa, Gaétan Poelman, Wim Van Paepegem, and Mathias Kersemans. 2018. “Automated Extraction of Local Defect Resonance for Efficient Non-destructive Testing of Composites.” In 9th European Workshop on Structural Health Monitoring. Manchester: NDT.net.
APA
Segers, Joost, Verboven, E., Hedayatrasa, S., Poelman, G., Van Paepegem, W., & Kersemans, M. (2018). Automated extraction of local defect resonance for efficient non-destructive testing of composites. 9th European Workshop on Structural Health Monitoring. Presented at the 9th European Workshop on Structural Health Monitoring, Manchester: NDT.net.
Vancouver
1.
Segers J, Verboven E, Hedayatrasa S, Poelman G, Van Paepegem W, Kersemans M. Automated extraction of local defect resonance for efficient non-destructive testing of composites. 9th European Workshop on Structural Health Monitoring. Manchester: NDT.net; 2018.
MLA
Segers, Joost, Erik Verboven, Saeid Hedayatrasa, et al. “Automated Extraction of Local Defect Resonance for Efficient Non-destructive Testing of Composites.” 9th European Workshop on Structural Health Monitoring. Manchester: NDT.net, 2018. Print.
@inproceedings{8571536,
  abstract     = {Local defect resonance (LDR) makes use of high frequency vibrations to get a localized resonant activation of the defect. One of the major difficulties with respect to the use of LDR for non-destructive testing is the actual identification of the LDR frequency. In this study, different post-processing methods are applied to broadband vibration data, obtained for a carbon fiber reinforced plastic with a flat bottom hole, in view of automated extraction of LDR features. Results are shown and discussed in the frequency domain. In order to reduce the computational effort for large datasets, principle component analysis (PCA) and frequency band data (FBD) calculation are investigated. The effect on the calculation time and the data size is investigated. Moreover, a signal-to-noise ratio is introduced to investigate the performance of both techniques with respect to the automated LDR detection algorithm. Finally, the effect of a reduced sampling is investigated with respect to the performance of the automated LDR extraction procedure.},
  author       = {Segers, Joost and Verboven, Erik and Hedayatrasa, Saeid and Poelman, Ga{\'e}tan and Van Paepegem, Wim and Kersemans, Mathias},
  booktitle    = {9th European Workshop on Structural Health Monitoring},
  language     = {eng},
  location     = {Manchester, United Kingdom},
  publisher    = {NDT.net},
  title        = {Automated extraction of local defect resonance for efficient non-destructive testing of composites},
  url          = {https://www.ndt.net/search/docs.php3?showForm=off\&id=23233},
  year         = {2018},
}