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13 May 2013 A computational tool to highlight anomalies on shearographic images in optical flaw detection
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Shearography is an optical and nondestructive technique that has been largely used for damage detection in layered composite materials where delaminations and debondings are found among the most common flaws. Shearography is a relative measurement on which two images are recorded for different loading conditions of the sample. The applied loading induces some deformations into the sample generating a displacement field on its surface. The absolute difference between two phase maps recorded at two different loading instances produces an interference fringe pattern which is directly correlated to the displacements produced on the material surface. In some cases, depending on the loading level and mainly on the sample geometry, interference patterns will contain fringes resulting from geometry changes. This will mask those fringes correlated to flaws presented into the material, resulting in an image misinterpretation. This phenomenon takes place mainly when the sample has curved geometries, as for example pipe or vessel surfaces. This paper presents an algorithm which uses a mathematical processing to improve the visualization of flaws in shearographic images. The mathematical processing is based on divergent calculation. This algorithm highlights defected regions and eliminates fringes caused by geometry changes, providing an easier interpretation for complex shearographic images. This paper also shows the principle and the algorithm used for the processing. Results, advantages and difficulties of the method are presented and discussed by using simulated fringe maps as well as real ones.
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A. V. Fantin, D. P. Willemann, M. Viotti, and A. Albertazzi "A computational tool to highlight anomalies on shearographic images in optical flaw detection", Proc. SPIE 8788, Optical Measurement Systems for Industrial Inspection VIII, 87880L (13 May 2013);

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