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A New Remedial strategy for Permanent Magnet Synchronous Motor Based on Artificial Neural Network
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| Author(s) |
Shady KHALIL, Haitham ABU-RUB, Mohamed SAAD, Essam ABOU-EL-ZAHAB, Atif IQBAL |
| Abstract |
This paper proposes an effective approach to detect, isolate, and identify fault severity and post faultoperation of permanent magnet synchronous motors (PMSM) in the presence of stator winding turn fault.The paper proposes fault tolerant operation of PMSM under post condition with stator winding turn faultby using grounded neutral point through controllable impedance using artificial neural network (ANN).The fault detection and diagnosis is achieved by using a strategy based on the analysis of the ratio of third harmonic to fundamental waveform obtained from Fast Fourier Transform (FFT) of magnitudecomponents of the stator currents. The strategy helps to detect stator turn fault, isolate the faultycomponents, and estimate different insulation failure percentages and remedial operation of PMSM in thepresence of stator winding turn fault. The model of PMSM with stator winding turn fault is simulated atdifferent load conditions using a (2-D) Finite Element Analysis (FEA). Experimental results demonstratethe validity of the proposed technique. |
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| Filename: | 0348-epe2013-full-10361489.pdf |
| Filesize: | 351.2 KB |
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| Type |
Members Only |
| Date |
Last modified 2014-02-09 by System |
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