• DocumentCode
    3532914
  • Title

    Mechanical Fault Detection Using Fuzzy Index Fusion

  • Author

    Boutros, Tony ; Liang, Ming

  • Author_Institution
    Dept. of Mech. Eng., Univ. of Ottawa Ottawa, Ottawa, ON
  • fYear
    2009
  • fDate
    28-29 April 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper reports a simple yet effective fuzzy fusion approach. With this approach, several important machine fault indices can be turned into a single comprehensive fault indicator, fuzzy fused index (FFI). The FFI has been successfully applied to different tasks: tool condition monitoring in milling operations and bearing condition monitoring for a motor, using the same fuzzy rule base. This clearly shows the effectiveness and versatility of the fuzzy fused index.
  • Keywords
    condition monitoring; fault diagnosis; fuzzy set theory; milling; milling machines; bearing condition monitoring; condition monitoring; fuzzy index fusion; machine fault indices; mechanical fault detection; milling operations; motor; Condition monitoring; Electrical capacitance tomography; Fault detection; Fuzzy sets; Mechanical engineering; Milling; Power generation; Robustness; Sensor fusion; Turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Testing and Diagnosis, 2009. ICTD 2009. IEEE Circuits and Systems International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-2587-7
  • Type

    conf

  • DOI
    10.1109/CAS-ICTD.2009.4960837
  • Filename
    4960837