• DocumentCode
    2851787
  • Title

    OBTS-oriented research on warship main power system hybrid model

  • Author

    Xie, Kuan ; Wu, Liechang ; Guo, Chaoyou

  • Author_Institution
    Dept. of Mech. Eng., Naval Univ. of Eng., Wuhan, China
  • fYear
    2012
  • fDate
    24-27 June 2012
  • Firstpage
    435
  • Lastpage
    437
  • Abstract
    This paper puts forward a warship main power on board training system hybrid modeling method based on neural network and integrates the method of mechanism modeling and Identification Modeling, uses neural network to compensate the error from the mechanism model. It improves the model precision, and suit the behavior changing of main power system. Taking warship diesel as an example, the developing method of hybrid model of diesel rotating speed was studied, and the feasibility of hybrid modeling method proposed was testified.
  • Keywords
    computer based training; marine power systems; neural nets; power engineering computing; ships; OBTS-oriented research; diesel rotating speed was; identification modeling; mechanism modeling; model precision; neural network; warship diesel; warship main power on board training system hybrid modeling method; warship main power system hybrid model; Accuracy; Analytical models; Predictive models; hybrid modeling; main power system; neural network; on board training system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4673-2363-5
  • Type

    conf

  • DOI
    10.1109/EEESym.2012.6258685
  • Filename
    6258685