• DocumentCode
    2764237
  • Title

    Detection and Severity Classification of Rotor Imbalance Faults in Induction Machines

  • Author

    Jain, Himanshu ; Korkua, Suratsavadee ; Lee, Wei-Jen ; Kwan, Chiman

  • Author_Institution
    Energy Syst. Res. Center, Univ. of Texas at Arlington, Arlington, TX, USA
  • fYear
    2010
  • fDate
    3-7 Oct. 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Rotor imbalance in induction machines has been widely studied. The signatures to look for in the stator current for detecting rotor imbalance are well established. However, an accurate explanation for the appearance of these signatures is lacking. Moreover, in most studies only a single phase of stator current has been used for detecting rotor imbalance and determining its severity. Combing imbalance features from the three phases through sensor fusion can yield more accurate and reliable results. Therefore, this paper focuses on, (i) accurate modeling of rotor imbalance to explain the genesis of its signatures in the stator current and, (ii) determining imbalance severity by sensor fusion. A test bed is established to verify the proposed approach.
  • Keywords
    asynchronous machines; fault diagnosis; sensor fusion; induction machines; rotor imbalance detection; rotor imbalance faults; sensor fusion; severity classification; stator current; Inductance; Mathematical model; Rotors; Sensor fusion; Stator windings; Torque;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industry Applications Society Annual Meeting (IAS), 2010 IEEE
  • Conference_Location
    Houston, TX
  • ISSN
    0197-2618
  • Print_ISBN
    978-1-4244-6393-0
  • Type

    conf

  • DOI
    10.1109/IAS.2010.5615966
  • Filename
    5615966