• DocumentCode
    3662161
  • Title

    Induction machine bearing faults detection based on Hilbert-Huang transform

  • Author

    Elhoussin Elbouchikhi;Vincent Choqueuse;Youness Trachi;Mohamed Benbouzid

  • Author_Institution
    ISEN Brest, EA 4325 LBMS, France
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    843
  • Lastpage
    848
  • Abstract
    This paper focuses on rolling elements bearing faults detection in induction machine based on stator currents monitoring. Specifically, it proposes to process the stator currents using Hilbert-Huang transform. This approach is composed of two steps. First, the empirical mode decomposition is used in order to estimate the intrinsic mode functions (IMFs), then the Hilbert transform is employed to compute the instantaneous amplitude (IA) and instantaneous frequency (IF). The energy of the instantaneous amplitude of the IMFs is used as fault indicator. The proposed approach is used for bearing fault detection in induction machine at several fault degrees. The effectiveness of the proposed Hilbert-Huang Transform technique is verified by a series of experimental tests corresponding to different bearing fault conditions.
  • Keywords
    "Transforms","Stators","Induction machines","Fault detection","Frequency modulation","Time-frequency analysis","Circuit faults"
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics (ISIE), 2015 IEEE 24th International Symposium on
  • Electronic_ISBN
    2163-5145
  • Type

    conf

  • DOI
    10.1109/ISIE.2015.7281580
  • Filename
    7281580