• DocumentCode
    3124779
  • Title

    Fault detection and prognosis methods for a monitoring system of rotating electrical machines

  • Author

    Ciandrini, Chiara ; Gallieri, Marco ; Giantomassi, Andrea ; Ippoliti, Gianluca ; Longhi, Sauro

  • Author_Institution
    Dipt. di Ing. Inf. Gestionale e dell´´Autom., Univ. Politec. delle Marche, Ancona, Italy
  • fYear
    2010
  • fDate
    4-7 July 2010
  • Firstpage
    2085
  • Lastpage
    2090
  • Abstract
    Companies are involved in a high competition for reducing the cost of production in order to maintain their market shares. Since the costs of maintenance contribute a substantial portion of the production costs, companies must budget maintenance effectively. Machine deterioration prognosis can decrease the costs of maintenance by minimizing the loss of production due to machine breakdown and avoiding the overstocking of spare parts. This paper gives a review of some fault detection and prognosis methods to diagnose faults and failure on rotating electrical machines. To develop the monitoring system accelerometers have been used to acquire vibration measurements. Performance are studied on a laboratory-scale experimental system.
  • Keywords
    electric machines; fault diagnosis; fault detection; machine deterioration prognosis; monitoring system; prognosis method; rotating electrical machine; Artificial neural networks; Circuit faults; Fault detection; Indexes; Monitoring; Principal component analysis; Vibrations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics (ISIE), 2010 IEEE International Symposium on
  • Conference_Location
    Bari
  • Print_ISBN
    978-1-4244-6390-9
  • Type

    conf

  • DOI
    10.1109/ISIE.2010.5637762
  • Filename
    5637762