In recent years, nondestructive testing and evaluation techniques have been successfully used to evaluate the integrity on different kinds of materials. These methods have been exploited in a lot of interesting industrial applications, since they have the advantage to keep the inspected specimens intact. In particular, within the framework of ageing aircrafts’ inspection, magnetooptic imaging (MOI) is increasing in importance and popularity. Usually, the open problem with MOI is the identification of bad rivets starting from experimental measurements. For this purpose, the Karhunen–Loeve transform, an eigenvector singular value decomposition based technique, has been exploited by authors. In this paper, the implemented method and very interesting preliminary results are described.

Singular Value Decomposition Processing of Magneto-Optic Images for Flawed Rivet Identification in Agin Aircrafts

VERSACI, Mario;MORABITO, Francesco Carlo
2009

Abstract

In recent years, nondestructive testing and evaluation techniques have been successfully used to evaluate the integrity on different kinds of materials. These methods have been exploited in a lot of interesting industrial applications, since they have the advantage to keep the inspected specimens intact. In particular, within the framework of ageing aircrafts’ inspection, magnetooptic imaging (MOI) is increasing in importance and popularity. Usually, the open problem with MOI is the identification of bad rivets starting from experimental measurements. For this purpose, the Karhunen–Loeve transform, an eigenvector singular value decomposition based technique, has been exploited by authors. In this paper, the implemented method and very interesting preliminary results are described.
flawed rivet detection ; Magneto-optic imaging; Singular value decomposition; Karhunen-Loeve transform
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/1780
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