• DocumentCode
    1075715
  • Title

    Motor bearing damage detection using stator current monitoring

  • Author

    Schoen, Randy R. ; Habetler, Thomas G. ; Kamran, Farrukh ; Bartfield, R.G.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    31
  • Issue
    6
  • fYear
    1995
  • Firstpage
    1274
  • Lastpage
    1279
  • Abstract
    This paper addresses the application of motor current spectral analysis for the detection of rolling-element bearing damage in induction machines. Vibration monitoring of mechanical bearing frequencies is currently used to detect the presence of a fault condition. Since these mechanical vibrations are associated with variations in the physical air gap of the machine, the air gap flux density is modulated and stator currents are generated at predictable frequencies related to the electrical supply and vibrational frequencies. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by correlating the relationship between vibration and current frequencies caused by incipient bearing failures. The bearing failure modes are reviewed and the characteristic bearing frequencies associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and the related frequencies determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. Experimental results which show the vibration and current spectra of an induction machine with different bearing faults are used to verify the relationship between the vibrational and current frequencies. The test results clearly illustrate that the stator current signature can be used to identify the presence of a bearing fault
  • Keywords
    electric current measurement; failure analysis; induction motors; machine bearings; machine testing; monitoring; spectral analysis; stators; vibration measurement; current monitoring; current signature; current spectra analysis; failure modes; fault condition; flux density; induction machines; mechanical bearing frequencies; motor bearing damage detection; physical air gap; rolling-element bearing damage; stator current monitoring; stator currents; vibration monitoring; vibrational frequencies; Condition monitoring; Electrical fault detection; Frequency; Induction generators; Induction machines; Induction motors; Mechanical bearings; Spectral analysis; Stators; Vibrations;
  • fLanguage
    English
  • Journal_Title
    Industry Applications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0093-9994
  • Type

    jour

  • DOI
    10.1109/28.475697
  • Filename
    475697