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This paper presents three intelligent methods for condition monitoring of induction motors in real-time. A structured neural network has been designed to prognosis of instantaneous faults. The inputs of neural network are the standard deviation and mean of feature signal obtained by Hilbert transform of one phase current signal. The stator related faults have been diagnosed by designing fuzzy logic...
Early detection and diagnosis of incipient faults is desirable for online condition evaluation and improved operational efficiency of induction motors. A classification technique based on time series data mining is developed to detect broken rotor bar faults in induction motors. The proposed algorithm uses only stator phase currents as input without the need for any other signals. The stator phase...
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