• DocumentCode
    478129
  • Title

    Machine Performance Degradation Assessment Based on PCA-FCMAC

  • Author

    Lei, Zhang ; Qixin, Cao

  • Author_Institution
    Res. Inst. of Robot., Shanghai Jiao Tong Univ., Shanghai
  • Volume
    2
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    443
  • Lastpage
    447
  • Abstract
    A PCA-FCMAC (Principal Component Analysis-Fuzzy Cerebellar Model Articulation Controller) model is proposed for machine performance degradation assessment. In the model, the selected features from the sensor signals are first processed by PCA to eliminate the redundant information and then inputted into FCMAC. FCMAC is used to assess degradation states quantitatively based on its local generalization ability. The implementation of the model is presented. Then the application in a drilling machine to assess the states of the cutting tool shows the effectiveness of the model. The comparative analyses of the assessing results prove FCMAC work better than CMAC.
  • Keywords
    fuzzy control; principal component analysis; fuzzy cerebellar model articulation controller; machine performance degradation assessment; principal component analysis; Cutting tools; Degradation; Drilling machines; Feature extraction; Machine intelligence; Performance analysis; Principal component analysis; Sensor phenomena and characterization; Spline; Temperature sensors; Degradation prediction; FCMAC; PCA;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.741
  • Filename
    4667034