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ISSN: 1999-8716

Volume1, Issue1

PRUNED ANN MODEL FOR THREE PHASE INDUCTION MOTOR OPERATING CONDITIONS CLASSIFICATION

    Ali Khudhair Mutlag

DIYALA JOURNAL OF ENGINEERING SCIENCES, 2008, Volume 1, Issue 1, Pages 32-45

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Abstract

The Artificial Neural Networks (ANN) have become a very useful tool in a wide range of engineering applications. In this paper, feed forward neural network Optimal Brain Surgeon (OBS) pruned model is proposed to classify the operating conditions of three phase induction motor. The proposed model had been trained with error back propagation training algorithm using frequency and voltage as input signals with nine possible operating conditions (faulty and healthy) acting as output neurons of the neural network model. The simulation results show that the pruned ANN model can perform perfect classification for the operating conditions of three phase induction motor.
Keywords:
    neural networks Optimal Brain Surgeon Induction Motor
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(2008). PRUNED ANN MODEL FOR THREE PHASE INDUCTION MOTOR OPERATING CONDITIONS CLASSIFICATION. DIYALA JOURNAL OF ENGINEERING SCIENCES, 1(1), 32-45.
Ali Khudhair Mutlag. "PRUNED ANN MODEL FOR THREE PHASE INDUCTION MOTOR OPERATING CONDITIONS CLASSIFICATION". DIYALA JOURNAL OF ENGINEERING SCIENCES, 1, 1, 2008, 32-45.
(2008). 'PRUNED ANN MODEL FOR THREE PHASE INDUCTION MOTOR OPERATING CONDITIONS CLASSIFICATION', DIYALA JOURNAL OF ENGINEERING SCIENCES, 1(1), pp. 32-45.
PRUNED ANN MODEL FOR THREE PHASE INDUCTION MOTOR OPERATING CONDITIONS CLASSIFICATION. DIYALA JOURNAL OF ENGINEERING SCIENCES, 2008; 1(1): 32-45.
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Journal Information

Publisher: Diyala University

Email:  engineering_college@diyengineering.net

Editor-in-chief: Dr. Amer Mohammed Ibrahim

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