Non Destructive Testing and Evaluation (NDT/NDE) assumes a very important role in many fields of industrial and civil interest, particularly when the quality control of manufacturing is associated to the maintenance of complex equipment without compromising its integrity and functionality. In addition, requiring the detection of the integrity of a specimen in real time contexts, it is necessary to exploit algorithms with a low computational complexity. In this context, the production of Carbon Fiber Reinforced Polymer (CFRP) is a very complex procedure in which defects take place during the process of manufacturing compromising the integrity of the specimen. In the NDT/NDE domain, Ultrasonic Tests (UTs) give an efficient contribution in identifying the presence of a defect. In this paper, Fuzzy Subsethood approach is exploited to localize and classify defects in CFRP following a geometrical point of view in which the problem is translated into the computation of a fuzzy distance among signals (measure of ultrasonic echoes). Results of classification are analyzed and compared with other heuristic techniques with a higher computational load.
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