IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-40636-9.html
   My bibliography  Save this article

Non-destructive erosive wear monitoring of multi-layer coatings using AI-enabled differential split ring resonator based system

Author

Listed:
  • Vishal Balasubramanian

    (University of British Columbia)

  • Omid Niksan

    (University of British Columbia)

  • Mandeep C. Jain

    (University of British Columbia)

  • Kevin Golovin

    (University of Toronto)

  • Mohammad H. Zarifi

    (University of British Columbia)

Abstract

Unprotected surfaces where a coating has been removed due to erosive wear can catastrophically fail from corrosion, mechanical impingement, or chemical degradation, leading to major safety hazards, financial losses, and even fatalities. As a preventive measure, industries including aviation, marine and renewable energy are actively seeking solutions for the real-time and autonomous monitoring of coating health. This work presents a real-time, non-destructive inspection system for the erosive wear detection of coatings, by leveraging artificial intelligence enabled microwave differential split ring resonator sensors, integrated to a smart, embedded monitoring circuitry. The differential microwave system detects the erosion of coatings through the variations of resonant characteristics of the split ring resonators, located underneath the coating layer while compensating for the external noises. The system’s response and performance are validated through erosive wear tests on single- and multi-layer polymeric coatings up to a thickness of 2.5 mm. The system is capable of distinguishing which layer is being eroded (for multi-layer coatings) and estimating the wear depth and rate through its integration with a recurrent neural network-based predictive analytics model. The synergistic combination of artificial intelligence enabled microwave resonators and a smart monitoring system further demonstrates its practicality for real-world coating erosion applications.

Suggested Citation

  • Vishal Balasubramanian & Omid Niksan & Mandeep C. Jain & Kevin Golovin & Mohammad H. Zarifi, 2023. "Non-destructive erosive wear monitoring of multi-layer coatings using AI-enabled differential split ring resonator based system," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40636-9
    DOI: 10.1038/s41467-023-40636-9
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-40636-9
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-40636-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Stephane Rioual & Benoit Lescop & Julien Pellé & Gerusa De Alkmim Radicchi & Gilles Chaumat & Marie Dominique Bruni & Johan Becker & Dominique Thierry, 2021. "Monitoring of the Environmental Corrosivity in Museums by RFID Sensors: Application to Pollution Emitted by Archeological Woods," Sustainability, MDPI, vol. 13(11), pages 1-10, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Charlotte Holzer & Benoît Lescop & Gilles Nguyen-Vien & Stéphane Rioual, 2023. "The Deutsches Museum Spacesuit Display: Long-Term Preservation and Atmospheric Monitoring," Sustainability, MDPI, vol. 15(12), pages 1-15, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40636-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.