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In this paper, a fault classification method based on grey clustering is proposed for fault detection of induction motors. The amplitudes of rotor frequency related sideband components obtained through Fourier transform of one phase stator current are used for broken rotor bar faults. Park's vector components are extracted from three phase motor currents and then new feature is obtained using principal...
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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