Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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An Artificial Neural Networks Application for the Automatic Detection of Severity of Stator Inter Coil Fault in Three Phase Induction Motor

  • Rajamany, Gayatridevi (Dept. of Electrical and Electronic Engineering, Asan Memorial College of Engineering and Technology, Affiliated to Anna University) ;
  • Srinivasan, Sekar (Dept. of Electrical and Electronic Engineering, Hindustan Institute of Technology and Science)
  • Received : 2017.04.09
  • Accepted : 2017.07.11
  • Published : 2017.11.01
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Abstract

This paper deals with artificial neural network approach for automatic detection of severity level of stator winding fault in induction motor. The problem is faced through modelling and simulation of induction motor with inter coil shorting in stator winding. The sum of the absolute values of difference in the peak values of phase currents from each half cycle has been chosen as the main input to the classifier. Sample values from workspace of Simulink model, which are verified with experiment setup practically, have been imported to neural network architecture. Consideration of a single input extracted from time domain simplifies and advances the fault detection technique. The output of the feed forward back propagation neural network classifies the short circuit fault level of the stator winding.

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References

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