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Sensors 2015, 15(5), 11402-11416; doi:10.3390/s150511402

Intelligent Detection of Cracks in Metallic Surfaces Using a Waveguide Sensor Loaded with Metamaterial Elements

1
Department of Electrical and Computer Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
2
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 28 January 2015 / Revised: 5 May 2015 / Accepted: 6 May 2015 / Published: 15 May 2015
(This article belongs to the Special Issue Metamaterial-Inspired Sensors)
View Full-Text   |   Download PDF [468 KB, uploaded 26 May 2015]   |  

Abstract

This work presents a real life experiment of implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor’s signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impact in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks and the obtained experimental results showed good crack classification accuracy rates. View Full-Text
Keywords: artificial intelligence; split-ring resonators; metamaterial; crack detection; waveguide sensors artificial intelligence; split-ring resonators; metamaterial; crack detection; waveguide sensors
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ali, A.; Hu, B.; Ramahi, O. Intelligent Detection of Cracks in Metallic Surfaces Using a Waveguide Sensor Loaded with Metamaterial Elements. Sensors 2015, 15, 11402-11416.

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