• DocumentCode
    2753067
  • Title

    Linguistic model for axle fatigue

  • Author

    Grantner, Janos ; Bazuin, Bradley ; Liang Dong ; Al-shawawreh, Jumana ; Hathaway, Richard ; Fajardo, Claudia ; Castanier, Matthew P. ; Hussain, Shiraz

  • Author_Institution
    Dept. of Electr. & Comput. Eng., WMU, Kalamazoo, MI, USA
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Army ground vehicles often operate in extremely severe environmental and battlefield conditions. Condition Based Maintenance (CBM) allows maintenance to be performed based on evidence of need provided by reliability modeling and/or other enabling technologies, thus reducing maintenance costs and increasing vehicle availability. A fuzzy model is developed to diagnose the axle fatigue of light trucks. The extraction of the fuzzy rules is based upon expert knowledge and a linear damage model. Training data will be used to modify the membership functions and the fuzzy If-Then rules to improve the quality of the fuzzy model for fault diagnostics. The improvement of the fuzzy model will be carried out using re-clustering operation and membership function optimization.
  • Keywords
    axles; condition monitoring; fault diagnosis; fuzzy set theory; knowledge based systems; maintenance engineering; mechanical engineering computing; military computing; military vehicles; optimisation; CBM; army ground vehicles; axle fatigue; condition based maintenance; fault diagnostics; fuzzy If-Then rules; fuzzy model; fuzzy rule extraction; linear damage model; linguistic model; maintenance costs reduction; membership function optimization; reclustering operation; reliability modeling; Axles; Computational modeling; Fatigue; Maintenance engineering; Stress; Training data; Vehicles; Condition Based Maintenance; Rainflow algorithm; axle fatigue; fuzzy model; intelligent diagnostics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4673-1507-4
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2012.6251197
  • Filename
    6251197