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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    Titel :

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


    Beteiligte:
    Mair, A.J. (Autor:in) / Davidson, E.M. (Autor:in) / McArthur, S.D.J. (Autor:in) / Srivastava, S.K. (Autor:in) / Schoder, K. (Autor:in) / Cartes, D.A. (Autor:in)


    Erscheinungsdatum :

    01.04.2009


    Format / Umfang :

    320106 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch