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Capacitive imaging using fused amplitude and phase information for improved defect detection
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Amato, Silvio, Hutchins, David A., Yin, Xiaokang, Ricci, Marco and Laureti, Stefano (2021) Capacitive imaging using fused amplitude and phase information for improved defect detection. NDT & E International, 124 . 102547. doi:10.1016/j.ndteint.2021.102547
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WRAP-Capacitive-imaging-amplitude-phase-improved-defect-detection-2021.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only until 24 September 2022. Contact author directly, specifying your specific needs. - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (1757Kb) |
Official URL: https://doi.org/10.1016/j.ndteint.2021.102547
Abstract
This paper introduces an improved image processing method useable in capacitive imaging applications. Standard capacitive imaging tends to prefer amplitude-based images over the use of phase due to better signal-to-noise ratios. The new approach exploits the best features of both types of information by combining them to form clearer images, hence improving both defect detection and characterization in non-destructive evaluation. The methodology is demonstrated and optimized using a benchmark sample. Additional experiments on glass fibre composite sample illustrate the advantages of the technique.
| Item Type: | Journal Article | ||||||||
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| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science > Engineering | ||||||||
| SWORD Depositor: | Library Publications Router | ||||||||
| Library of Congress Subject Headings (LCSH): | Nondestructive testing, Imaging systems, Materials -- Defects | ||||||||
| Journal or Publication Title: | NDT & E International | ||||||||
| Publisher: | Elsevier | ||||||||
| ISSN: | 0963-8695 | ||||||||
| Official Date: | December 2021 | ||||||||
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| Volume: | 124 | ||||||||
| Article Number: | 102547 | ||||||||
| DOI: | 10.1016/j.ndteint.2021.102547 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| RIOXX Funder/Project Grant: |
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