• DocumentCode
    1871155
  • Title

    Research of low-voltage arc fault classification based on support vector machine

  • Author

    Shuirong Liao ; Rencheng Zhang ; Yijian Huang ; He Xia

  • Author_Institution
    College of Mechanical Engineering and Automation, Huaqiao University, Xiamen, Fujian, China
  • fYear
    2012
  • fDate
    3-5 March 2012
  • Firstpage
    1690
  • Lastpage
    1693
  • Abstract
    Support vector machine is introduced into low-voltage arc fault research, carrying out arc fault classification analysis for different loads. Referring to U.S. UL1699 standard, current data is collected by doing experiment. Then support vector machine is used to classify and compare the recognition results for different kernels. Light bulbs, switching power and cleaner are selected as typical loads to analyze arc fault. The differences between normal arc and arc fault are compared. Finally, it is concluded that arc fault current is usually short-time zero, has big differences between positive and negative half-cycle, and has large variation of amplitude and other characteristics. This provides reference for further arc fault research.
  • Keywords
    Matlab; Support vector machine; arc fault; electrical fire; low-voltage;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Automatic Control and Artificial Intelligence (ACAI 2012), International Conference on
  • Conference_Location
    Xiamen
  • Electronic_ISBN
    978-1-84919-537-9
  • Type

    conf

  • DOI
    10.1049/cp.2012.1311
  • Filename
    6492918