The management and control of shipboard Medium Voltage AC (MVAC) and Medium Voltage DC (MVDC) power system architectures under fault conditions present a number of challenges. The use and resulting interaction of multiple power electronic components in mesh-like power distribution architectures possibly result in the effects of faults being detectable throughout the system, for example, line-to-hull faults on DC systems with high resistive grounding.


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    Title :

    Machine learning techniques for diagnosing and locating faults through the automated monitoring of power electronic components in shipboard power systems


    Contributors:


    Publication date :

    2009-04-01


    Size :

    320106 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English