• DocumentCode
    2740730
  • Title

    Three-phase Induction Motor Operation Trend Prediction Using Support Vector Regression for Condition-based Maintenance

  • Author

    Li, Yanfeng ; Yu, Haibin

  • Author_Institution
    Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    7878
  • Lastpage
    7881
  • Abstract
    Due to the broad employment and large amount of electricity consumption of induction motor, their efficient operation has been a focus for engineering research. The paper proposes a new integrated approach performing the motor condition prediction for the maintenance of low cost and high quality. Studies were done on nonlinear data analysis techniques, including particle filters for state estimates and support vector regression for condition prediction. Laboratory studies support the condition-based maintenance for motor systems
  • Keywords
    data analysis; induction motors; maintenance engineering; regression analysis; state estimation; support vector machines; condition prediction; condition-based maintenance; nonlinear data analysis; particle filters; state estimation; support vector regression; three-phase induction motor operation trend prediction; AC motors; Costs; Data analysis; Electrical equipment industry; Electrical products industry; Employment; Energy consumption; Induction motors; Maintenance; Power system reliability; kernel method; maintenance; motor systems; prediction; regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1713504
  • Filename
    1713504