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A Fuzzy Similarity-Based Approach to Classify Numerically Simulated and Experimentally Detected Carbon Fiber-Reinforced Polymer Plate Defects

Articolo
Data di Pubblicazione:
2022
Citazione:
A Fuzzy Similarity-Based Approach to Classify Numerically Simulated and Experimentally Detected Carbon Fiber-Reinforced Polymer Plate Defects / Versaci, Mario; Angiulli, Giovanni; Crucitti, Paolo; De Carlo, Domenico; Laganà, Filippo; Pellicanò, Diego; Palumbo, Annunziata. - In: SENSORS. - ISSN 1424-8220. - 22:11(2022), p. 4232. [10.3390/s22114232]
Abstract:
: This paper presents an eddy current approach for testing, estimating, and classifying CFRP plate sub-surface defects, mainly due to delamination, through specific 2D magnetic induction field amplitude maps. These maps, showing marked fuzziness content, require the development of a procedure based on a fuzzy approach being efficiently classified. Since similar defects produce similar maps, we propose a method based on innovative fuzzy similarity formulations. This procedure can collect maps similar to each other in particular defect classes. In addition, a low-cost analysis system, including the probe, has been implemented in hardware. The developed tool can detect and evaluate the extent of surface defects with the same performance as a hardware tool of higher specifications, and it could be fruitfully employed by airline companies to maintain aircraft in compliance with safety standards
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Versaci, Mario; Angiulli, Giovanni; Crucitti, Paolo; De Carlo, Domenico; Laganà, Filippo; Pellicanò, Diego; Palumbo, Annunziata
Autori di Ateneo:
ANGIULLI Giovanni
VERSACI Mario
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/126346
Link al Full Text:
https://iris.unirc.it//retrieve/handle/20.500.12318/126346/260495/Versaci_2022_Sensors_Fuzzy_Editor.pdf
Pubblicato in:
SENSORS
Journal
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URL

https://www.mdpi.com/1424-8220/22/11/4232
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