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ANN Based System for the Detection of Winding Insulation Condition and Bearing Wear in Single Phase Induction Motor
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 Title & Authors
ANN Based System for the Detection of Winding Insulation Condition and Bearing Wear in Single Phase Induction Motor
Ballal, M.S.; Suryawanshi, H.M.; Mishra, Mahesh K.;
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 Abstract
This paper deals with the problem of detection of induction motor incipient faults. Artificial Neural Network (ANN) approach is applied to detect two types of incipient faults (1). Interturn insulation and (2) Bearing wear faults in single-phase induction motor. The experimental data for five measurable parameters (motor intake current, rotor speed, winding temperature, bearing temperature and the noise) is generated in the laboratory on specially designed single-phase induction motor. Initially, the performance is tested with two inputs i.e. motor intake current and rotor speed, later the remaining three input parameters (winding temperature, bearing temperature and the noise) were added sequentially. Depending upon input parameters, the four ANN based fault detectors are developed. The training and testing results of these detectors are illustrated. It is found that the fault detection accuracy is improved with the addition of input parameters.
 Keywords
Induction motor;ANN;Winding insulation;Bearing wear;
 Language
English
 Cited by
1.
Detection of Incipient Faults in Induction Motors using FIS, ANN and ANFIS Techniques,;;;

Journal of Power Electronics, 2008. vol.8. 2, pp.181-191
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