Optimal Simulated Design of RBF Neural Network Classifier Block for Assessment of State of Degradation in Stator Insulation of Induction Motor
Amit J. Modak1, H. P. Inamdar2
1Prof. Amit J. Modak, Ph. D. Research Student, Department of Electrical Engineering, Walchand College of Engineering, Sangli (Maharashtra), India.
2Dr. H. P. Inamdar, Ex-Professor & Head, Department of Electrical Engineering, Walchand College of Engineering, Sangli (Maharashtra), India.
Manuscript received on 15 October 2015 | Revised Manuscript received on 25 October 2015 | Manuscript Published on 30 October 2015 | PP: 17-26 | Volume-5 Issue-1, October 2015 | Retrieval Number: A4267105115/15©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the present work the design of discrete ‘ANN’ simulation model is done for the classification and qualitative assessment of the state of degradation of insulation in the respective phases of three-phase ac induction motor. The extraction of mathematical parameters of stator current data pattern, which are simulating the specific state of degradation of insulation based on Park’s current transformation model, are presented in the previous research papers. The methodology adopted towards the optimal design process of the discrete neural network classifier blocks of discrete ‘ANN’ simulation model , which are designed on the basis of ‘radial basis function’ (RBF) type of neural network architecture for the qualitative assessment of the state of degradation of stator insulation is described in the present research paper.
Keywords: Induction Motor, Stator Insulation, Radial Basis Function, Artificial Neural Network, Park’s Current Transformation
Scope of the Article: Artificial Neural Network