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Several studies have demonstrated that induction machine faults introduce phase and/or amplitude modulation of the stator currents. Hence, demodulation of the stator currents is of high interest for induction machines faults detection and diagnosis. The demodulation techniques can be classified into mono-dimensional and multi-dimensional approaches. The mono-dimensional techniques include the synchronous...
In this paper, we have developed a feedforward neural networks to detect and to diagnosis rotor fault on induction motors using stator currents. In the first step, causes and effects of rotor fault have been studied, particularly, the number of broken bars has been considered. Then, in the second step, the number of broken rotor bars has been localized by Artificial Neural Networks (ANN), using the...
Nowadays, the induction motors became the key element in all industrial plants. Early detection of abnormalities during motor operation would reduce the repair cost and the motor outage time. It was observed that most methods which are presented in literature for diagnosing motor faults are belonged to signal approach. Their philosophy supposes that each fault is characterized by specific spectral...
Through the increasing use of electric actuators, the induction motor is now major in industrial applications and takes a particular interest for applications requiring high power and variable speed robustness and for its simplicity and its low cost. The early detection for motor deterioration can increase plant availability and safety in an economical way. To improve the reliability as a whole, a...
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