• DocumentCode
    2317743
  • Title

    A practical bearing fault diagnoser

  • Author

    Sadoughi, Alireza ; Behbahanifard, Hamidreza

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Isfahan Univ. of Technol., Isfahan
  • fYear
    2008
  • fDate
    21-24 April 2008
  • Firstpage
    151
  • Lastpage
    154
  • Abstract
    Bearing is an important part of electric machines. In order to avoid unscheduled outputs, it is important to detect an upcoming fault as soon as possible. Since fault in a great number of bearings commences from a single point defect, research on this category of faults has shared a great deal in predictive diagnosis literature. Single point defects will cause certain characteristic frequencies to appear in machine vibration spectrum. Because of impulsive nature of fault strikes, and complex modulations present in vibration signal, a simple spectrum analysis may result in erroneous conclusions.
  • Keywords
    electric machines; fault diagnosis; machine bearings; vibrations; auto-correlated vibration power signals; bearing fault diagnoser; electric machines; machine vibration spectrum; Autocorrelation; Circuit faults; Condition monitoring; Costs; Fault diagnosis; Frequency; Neural networks; Shafts; Signal processing; Vibration measurement; Apparatus; Autocorrelation; Bearing; Diagnosis; Fault; Intelligent; Vibration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Condition Monitoring and Diagnosis, 2008. CMD 2008. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-1621-9
  • Electronic_ISBN
    978-1-4244-1622-6
  • Type

    conf

  • DOI
    10.1109/CMD.2008.4580251
  • Filename
    4580251