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Pulsed Eddy Current Data Analysis for the Characterization of the Second-Layer Discontinuities

  • Yihao Liu
  • Shuo Liu
  • Huan Liu
  • Catalin Mandache
  • Zheng LiuEmail author
Article

Abstract

Pulsed eddy current (PEC) technique has been applied as a viable method to detect hidden discontinuities in metallic structures. Conventionally, selected time-domain features are employed to characterize the PEC data, such as peak value, lift-off point of intersection, rising point, crossing time, and differential time to peak. The research presented in this paper continues the effort in a previous study on detecting the radial cracks starting from the fastener hole in second layer of a two-layer mock-up aircraft structure. A large diameter excitation coil with ferrite core is used to induce a strong pulse, and the magnetic field generated by eddy current is detected by Hall sensors. Instead of analyzing the limited time-domain features, we propose using machine learning methods to interpret the raw data without feature extraction. Thus, the second-layer discontinuities can be characterized presumably with all the information contained in a waveform. An automated detection framework is proposed in this paper and the experimental results demonstrate the effectiveness of the proposed method.

Keywords

Pulse eddy current Lift-off intersection Second-layer crack Machine learning Classification 

Notes

Acknowledgements

Mr. Marc Genest at National Research Council of Canada is acknowledged for his valuable comments and feedback, which help improve the quality of this paper.

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of British Columbia (Okanagan)KelownaCanada
  2. 2.School of AutomationChina University of GeosciencesWuhanChina
  3. 3.National Research Council of CanadaOttawaCanada

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