• DocumentCode
    2199724
  • Title

    A comparison between RNN and RBF NN techniques for the detection of stator inter-turn fault of an induction motor

  • Author

    Dash, Rudra Narayan ; Panigrahy, Chinmoy ; Subudhi, Bidyadhar

  • Author_Institution
    School of Electrical Engineering, KIIT University, Bhubaneswar, Odisha, India
  • fYear
    2015
  • fDate
    24-25 Jan. 2015
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    With a view to detecting the inter-turn short circuit fault in stator winding of an Induction motor, an attempt has been made to compare RNN (Recurrent Neural Network) with RBF NN (Radial basis feed-forward neural network). Monitoring the three phase shifts between the current (Line) and voltage (Phase) of the Induction Motor is the basis of the fault location process.
  • Keywords
    Artificial neural networks; Circuit faults; Induction motors; Recurrent neural networks; Stator windings; Fault Diagnosis; Induction Motor; Interturn short circuit fault; Radial Basis Function Neural Network; Recurrent Neural Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical, Electronics, Signals, Communication and Optimization (EESCO), 2015 International Conference on
  • Conference_Location
    Visakhapatnam, India
  • Print_ISBN
    978-1-4799-7676-8
  • Type

    conf

  • DOI
    10.1109/EESCO.2015.7254022
  • Filename
    7254022
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2199724