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  1. Journal of Applied Sciences
  2. Vol 6 (13), 2006
  3. 2817-2820
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Journal of Applied Sciences

Year: 2006 | Volume: 6 | Issue: 13 | Page No.: 2817-2820
DOI: 10.3923/jas.2006.2817.2820
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Research Article

Three Phase Induction Motor Faults Detection by Using Radial Basis Function Neural Network

Ahmed N. Abd Alla

ABSTRACT


In the present study the Artificial Neural Network (ANN) technique for the detection of (bearing and stator inter turn faults) incipient faults in an induction motor bas been explored. Radial basis function approach has been used for ANN Training and test. Three phase instantaneous currents and angular velocity depending on rotor speed are utilized in proposed approach. An experimental setup is used to implement an online fault defector
PDF References Citation

How to cite this article

Ahmed N. Abd Alla, 2006. Three Phase Induction Motor Faults Detection by Using Radial Basis Function Neural Network. Journal of Applied Sciences, 6: 2817-2820.

DOI: 10.3923/jas.2006.2817.2820

URL: https://scialert.net/abstract/?doi=jas.2006.2817.2820

REFERENCES


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  8. Schoen, R.R., B.K. Lin, T.G. Habetler, J.H. Schlag and S. Farag, 1995. An unsupervised, on-line system for induction motor fault detection using stator current monitoring. IEEE Trans. Industry Appl., 31: 1280-1286.
    CrossRefDirect Link

  9. Siddique, A., G.X.Y. Adava and B. Sin, 2003. Applications of artificial intelligence techniques for induction machines stator fault diagnostics. Proceedings of the 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, Aug. 24-26, Atlanta, pp: 29-34.
    Direct Link

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