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A Comparative Study of Enhanced Infrared Image Processing for Foreign Object Detection in Lightweight Composite Honeycomb Structures

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Abstract

The interest toward lightweight composites in the aeronautical industry grows year by year. The challenge is the identification and characterization of defects by using an integration of different techniques. The use of the infrared thermography (IRT) method for the inspection of lightweight composites is poorly documented in the open literature, due to the low heat diffusion through the honeycomb cores. In this study, IRT was used to retrieve the unknown positions of internal inserted objects in three different lightweight composite structures, by using three new thermal image processing integration methods. The corresponding post-processed results were compared against the traditional principal component thermography and pulsed phase thermography image processing techniques. The comparison showed that the integrated signal smoothing processing enhanced the image quality compared to the established techniques. Then, a thermal-physical analysis corresponding to the experimental results was conducted, in order to explain the experimental results. Finally, the advantages and disadvantages of the different presented methods when applied on the different lightweight composite structures were summarized.

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Acknowledgements

The authors would like to thank Michael Brothers from the National Research Council (NRC) Canada for his assistance. The authors are also indebted to Eng. E. Valentini (Mecaer Aviation Group—Monteprandone—Italy) for the fabrication of the samples used in this work.

Author information

Authors and Affiliations

  1. Computer Vision and Systems Laboratory (CVSL), Department of Electrical and Computer Engineering, Laval University, 1065 av. de la Médecine, Quebec City, G1V 0A6, Canada

    Hai Zhang, Clemente Ibarra-Castanedo, Nicolas P. Avdelidis & Xavier P. V. Maldague

  2. Department of Industrial and Information Engineering and Economics, University of L’Aquila, Piazzale E. Pontieri No. 1, 67100, Roio Poggio, Italy

    Stefano Sfarra

  3. Tomsk Polytechnic University, Savinykh St., 7, Tomsk, Russia, 634028

    Stefano Sfarra

  4. Aerospace Research Centre, Structures, Materials and Manufacturing, National Research Council Canada, 1200 Montreal Road, Ottawa, K1A 0R6, Canada

    Marc Genest

  5. School of Physics and Electronics, Central South University, Changsha, 410083, China

    Yuxia Duan

  6. Department of Computer Science, Federal University of Uberlandia, 2121 Avenida Joao Naves de Avila, Uberlandia, 38400-902, Brazil

    Henrique Fernandes

  7. Aerospace Integration Research Centre (AIRC), College Road, Cranfield, MK43 0AL, UK

    Nicolas P. Avdelidis

Authors
  1. Hai Zhang
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  2. Stefano Sfarra
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  3. Marc Genest
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  4. Clemente Ibarra-Castanedo
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  5. Yuxia Duan
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  6. Henrique Fernandes
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  7. Nicolas P. Avdelidis
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  8. Xavier P. V. Maldague
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Corresponding author

Correspondence to Hai Zhang.

Additional information

This research is supported by the Canada Research Chair in Multipolar Infrared Vision (MiViM) and the Natural Sciences and Engineering Research Council Canada (NSERC) through a Discovery Grant.

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Zhang, H., Sfarra, S., Genest, M. et al. A Comparative Study of Enhanced Infrared Image Processing for Foreign Object Detection in Lightweight Composite Honeycomb Structures. Int J Thermophys 39, 140 (2018). https://doi.org/10.1007/s10765-018-2460-6

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  • DOI: https://doi.org/10.1007/s10765-018-2460-6

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