• Medientyp: E-Artikel
  • Titel: Case-based reasoning user support for industrial x-ray computed tomography
  • Beteiligte: Schild, Leonard; Höger, Katja; Zanini, Filippo; Lanza, Gisela; Carmignato, Simone
  • Erschienen: IOP Publishing, 2023
  • Erschienen in: Measurement Science and Technology, 34 (2023) 4, Seite 045403
  • Sprache: Nicht zu entscheiden
  • DOI: 10.1088/1361-6501/acacba
  • ISSN: 0957-0233; 1361-6501
  • Schlagwörter: Applied Mathematics ; Instrumentation ; Engineering (miscellaneous)
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  • Beschreibung: <jats:title>Abstract</jats:title> <jats:p>Industrial x-ray computed tomography is increasingly used in the field of dimensional metrology. However, the measurement accuracy is influenced by many factors for which comprehensive expert’s knowledge is still not available. This work presents an approach to establish a user support system that allows a user to achieve highly accurate measurements. The approach generates knowledge from experimental investigations deploying specifically designed test parts and uses the knowledge in a case-based reasoning user support system. Validation experiments showed that the user support system was successful at providing a user with instructions that led to highly accurate measurements of three previously unknown industrial workpieces.</jats:p>