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Lookup NU author(s): Adi Marindra, Professor Gui Yun TianORCiD
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© 2001-2012 IEEE.One of the challenges in structural health monitoring (SHM) is that defects, such as metal cracks and corrosions, can occur with multiple material properties and multilayer structure, entangled with influences from the reader system and the environment. This paper presents a multiresonance chipless radio frequency identification (RFID) sensor tag and the chipless RFID sensor reader applying principal component analysis (PCA) for multiparameter estimation in metal defect characterization. The proposed sensor tag is composed of the crossed diagonal dipole patches and the L-shaped patches generating six resonance peaks within 2-6-GHz band. The frequency signature of the sensor tag is acquired and processed by a chipless RFID reader implemented using an ultra-wideband impulse radar (UWB-IR) transceiver module. We demonstrate that the multiresonance chipless RFID sensor tag in conjunction with PCA-based feature extraction and selection can be applied for the characterization of metal crack with different widths and orientations. Furthermore, the proposed technique can find a robust feature indicating corrosion stages under a coating layer regardless of the sample orientation. This paper paves the way for multiparameter defect sensing and monitoring using a chipless RFID sensor system.
Author(s): Marindra AMJ, Tian GY
Publication type: Article
Publication status: Published
Journal: IEEE Sensors Journal
Year: 2019
Volume: 19
Issue: 18
Pages: 8037-8046
Print publication date: 15/09/2019
Online publication date: 20/05/2019
Acceptance date: 06/05/2019
ISSN (print): 1530-437X
ISSN (electronic): 1558-1748
Publisher: IEEE
URL: https://doi.org/10.1109/JSEN.2019.2917840
DOI: 10.1109/JSEN.2019.2917840
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