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EnglishIn the field of nondestructive testing on defect identification in metallic plates, the shape reconstruction is still an open question. State-of-the-art technologies indeed enable the operator to locate the position of a defect but not its shape. The aim of this paper is to make a contribution to the solution of this side of the problem suggesting a novel methodology based on a neurofuzzy approach. Sugeno's neurofuzzy inferences have been carried out for this purpose, as a first step in this direction. Fuzzy entropy was then exploited to measure how far is a given defect from a well-known depth. A sort of classification based on the depth of a defect has been performed this way.
| Titolo: | A Novel Approach for Detecting and Classifying Defects in Metallic Plates | |
| Autori: | ||
| Data di pubblicazione: | 2003 | |
| Rivista: | ||
| Handle: | http://hdl.handle.net/20.500.12318/533 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
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http://hdl.handle.net/20.500.12318/533
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