The authors present a signal processing method dedicated to the detection of defects buried next to rivets in aeronautical lap joints. The method is based on a multi-frequency principal component analysis and is applied to the images provided by an original eddy current imager. The optimization of the method is carried out thanks to an experimental approach, and validated with the detection of buried defects, ranging from 2mm to 8mm long and 2mm to 8mm deep. An extension of the method to a classification scheme is also considered.
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