The paper presents a work developed in the framework of the two years COPERNICUS technological research project CRASH (CRack and SHape defect detection in ferrite cores) CIPA-CT94 0153, in progress since 1995. The CRASH project concerns automated quality inspection of ferrite cores. CRASH studies the development of optical and electromagnetic systems that may be integrated in a working module to increase the recognition of imperfections on ferrite materials. Analysis and processing of acquired images and signals, as well as specification of ad-hoc algorithms for classification purposes constitute the technical approach to the problem. The achieved results show the capability of the system to detect different kind of imperfections in ferrite cores (shape defects, surface defects and subsurface imperfections) and classify them with low error rates. After an introduction to the problem in Section 1, different techniques of defect detection with different sensors are shown in Section 2, and Section 3 describes the achieved classification results.
CITATION STYLE
Mari, M., Dambra, C., Chetverikov, D., Verestoy, J., Jozwik, A., Nieniewski, M., … Lugg, M. (1997). The CRASH project: Defect detection and classification in ferrite cores. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1311, pp. 781–787). Springer Verlag. https://doi.org/10.1007/3-540-63508-4_196
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