• DocumentCode
    2319350
  • Title

    Application of fault diagnosis expert system in grinding process

  • Author

    Qin, Wei ; Yan, Wenjun ; Xu, Jing

  • Author_Institution
    Coll. of Electr. Eng., Zhejiang Univ., Hangzhou, China
  • fYear
    2010
  • fDate
    16-20 Aug. 2010
  • Firstpage
    290
  • Lastpage
    295
  • Abstract
    Directing at the complex structure, cockamamie production technology and great operation difficulty of vertical roller mill, this paper constructs the fault expert system to guide and optimize the grinding process. First, the expert database is established with fuzzy cluster analysis, principal component analysis (PCA) and tendency analysis. With support vector machine (SVM) regression, the multiple regression equations of main operation loops are fitted. In online, by looking up expert database and corresponding equations, the system gives out adjustment suggestions according to the variation tendency. Making use of OPC and VC++ techniques, this system has been applied in the practical field. The practical running conditions indicate that this system is effective and credible.
  • Keywords
    condition monitoring; expert systems; fault diagnosis; fuzzy set theory; grinding; pattern clustering; powder technology; principal component analysis; production engineering computing; regression analysis; rolling mills; support vector machines; OPC techniques; VC++ techniques; cockamamie production technology; fault diagnosis expert system; fuzzy cluster analysis; grinding process; multiple regression equations; principal component analysis; support vector machine; tendency analysis; vertical roller mill; Databases; Employee welfare; Equations; Expert systems; Mathematical model; Monitoring; Principal component analysis; Expert System; Fuzzy Cluster Analysis; PCA; SVM; Vertical Roller Mill;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics (ICAL), 2010 IEEE International Conference on
  • Conference_Location
    Hong Kong and Macau
  • Print_ISBN
    978-1-4244-8375-4
  • Electronic_ISBN
    978-1-4244-8374-7
  • Type

    conf

  • DOI
    10.1109/ICAL.2010.5585295
  • Filename
    5585295