• DocumentCode
    3480385
  • Title

    Vibration Fault Diagnosis for Hydraulic Generator Units with Pattern Recognition and Cluster Analysis

  • Author

    An, X.L. ; Zhou, J.Z. ; Liu, L. ; Yang, J.J. ; Li, C.S. ; Xiang, X.Q.

  • Author_Institution
    Coll. of Hydroelectr. & Digitization Eng., Huazhong Univ. of Sci. & Technol., Wuhan
  • fYear
    2008
  • fDate
    12-14 Oct. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    For reducing the economic losses of hydraulic generator units, fault detection and diagnosis is fundamental. A technique is presented that uses pattern recognition and cluster analysis. Faults of hydraulic generator units are classified from the characteristic parameters using statistical analysis methods. A characteristic parameter matrix of standard faults has been developed for identifying the vibration faults. The cluster technique is carried out in a real case. Results demonstrated that the proposed method is a good candidate to be used as an online diagnosis tool for hydraulic generator units.
  • Keywords
    fault diagnosis; hydroelectric generators; matrix algebra; pattern clustering; power engineering computing; power generation economics; power generation faults; statistical analysis; vibrations; characteristic parameter matrix; cluster analysis; economic loss reducion; fault detection; hydraulic generator unit; pattern recognition; statistical analysis; vibration fault diagnosis; Clustering algorithms; Clustering methods; Condition monitoring; Environmental economics; Fault detection; Fault diagnosis; Hydroelectric power generation; Pattern analysis; Pattern recognition; Power generation economics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-2107-7
  • Electronic_ISBN
    978-1-4244-2108-4
  • Type

    conf

  • DOI
    10.1109/WiCom.2008.3037
  • Filename
    4681226