• DocumentCode
    277527
  • Title

    Expert system for tool wear monitoring in blanking

  • Author

    Mardapittas, A.S. ; Au, Y.H.J.

  • Author_Institution
    Dept. of Manuf. & Eng. Syst., Brunel Univ., Uxbridge, UK
  • fYear
    1992
  • fDate
    33659
  • Firstpage
    42401
  • Lastpage
    42404
  • Abstract
    A description is given of a simple yet powerful expert system created using the CRYSTAL shell which is able to monitor the potential and functional failures of the tool and the monitoring equipment. The techniques of feature extraction, selection and classification using the Bayesian rule are presented. Finally supervised learning, necessary when new situations are encountered, is also discussed
  • Keywords
    computerised monitoring; computerised pattern recognition; expert systems; learning systems; machine tools; manufacturing data processing; mechanical engineering computing; Bayesian rule; CRYSTAL shell; blanking; classification; feature extraction; functional failures; monitoring equipment; powerful expert system; supervised learning; tool wear monitoring;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Intelligent Fault Diagnosis - Part 1: Classification-Based Techniques, IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • Filename
    170064