• DocumentCode
    2717056
  • Title

    Artificial neural network for detection of asynchronous state

  • Author

    Kostyla, Pawel

  • Author_Institution
    Dept. of Electr. Eng., Wroclaw Univ. of Technol., Wroclaw, Poland
  • fYear
    2010
  • fDate
    16-19 May 2010
  • Firstpage
    171
  • Lastpage
    174
  • Abstract
    An asynchronous state of a synchronic machine may be identified through determining the amplitudes of particular components of stator´s current provided that a constant slip value is assumed. Following a synchronism loss, this adopted value is assumed to be achieved and, for sure, exceeded. New parallel algorithms for detection of asynchronous state of synchronic machines, are proposed. The algorithms can be implemented by analogue adaptive circuits employing some neural networks principles. This chapter provides a description of artificial neural networks realising this task, whose operation algorithm is based on minimum square error criteria and maximum loss method.
  • Keywords
    Artificial neural networks; Circuits; DC generators; Machine windings; Magnetic flux; Parallel algorithms; Power generation; Rotors; Signal processing algorithms; Stator windings; neural network; optimization problem; parallel algorithms; signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2010 9th International Conference on
  • Conference_Location
    Prague, Czech Republic
  • Print_ISBN
    978-1-4244-5370-2
  • Electronic_ISBN
    978-1-4244-5371-9
  • Type

    conf

  • DOI
    10.1109/EEEIC.2010.5489953
  • Filename
    5489953