• DocumentCode
    3710759
  • Title

    Recognition of series arc fault based on the Hilbert Huang Transform

  • Author

    Changken Chen;Fengyi Guo;Yanli Liu;Zhiyong Wang;Yanjun Chen;Haihong Liang

  • Author_Institution
    Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, 125105, China
  • fYear
    2015
  • Firstpage
    324
  • Lastpage
    330
  • Abstract
    Series arc fault is a common fault in a power supply system. It could affect the reliability of power supply seriously and even cause safety accidents. A low-voltage series arc fault experiment platform was developed on the basis of the GB14287.4 standard in this paper. Series arc fault experiments were conducted with different types of load. Arc fault current signals of five cycles before and after arc occurred were analyzed by using Hilbert-Huang Transform. The current was resolved into several Intrinsic Mode Functions (IMF) by using the Empirical Mode Decomposition (EMD). Then the Hilbert spectrum was obtained by calculating Hilbert transform for IMF. The results show that Hilbert spectrum amplitude increased when arc fault occurred. Therefore Hilbert Huang Transform can be used to recognize the series arc fault.
  • Keywords
    "Circuit faults","Computers","Noise reduction","Time-frequency analysis","Spectral analysis","Empirical mode decomposition"
  • Publisher
    ieee
  • Conference_Titel
    Electrical Contacts (Holm), 2015 IEEE 61st Holm Conference on
  • Type

    conf

  • DOI
    10.1109/HOLM.2015.7355116
  • Filename
    7355116