Army ground vehicles often operate in extremely severe environmental and battlefield conditions. There are challenges for the reliability of the military ground vehicle fleet, which need to be addressed. 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. The architecture of the Intelligent Vehicle Health Management System (IVHMS) for light trucks is presented. A fuzzy model is developed to diagnose the axle fatigue of the vehicle. 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.


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    Titel :

    Condition Based Maintenance for Light Trucks


    Beteiligte:
    J. Grantner (Autor:in) / B. Bazuin (Autor:in) / S. Hussain (Autor:in) / M. P. Castanier (Autor:in) / L. Dong (Autor:in)

    Erscheinungsdatum :

    2010


    Format / Umfang :

    9 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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