NEURAL NETWORK-BASED APPROACH FOR DETECTION AND MAGNITUDE DETERMINATION OF TURN FAULTS IN INDUCTION MOTORS | ||||
| ERJ. Engineering Research Journal | ||||
| Article 3, Volume 31, Issue 4, October 2008, Page 331-336 PDF (246.68 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erjm.2008.69820 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| M. Alaam; M. Abdelkariem; M. A. Ekhazendar | ||||
| Department of Electrical Power and Machine Engineering Faculty of Engineering, Tanta University, Tanta, Egypt | ||||
| Abstract | ||||
| This paper presents a novel scbeme for the detection and magnitude determination of turn faults. Arlificial neural network (ANN) plays a role as fault detector and fault location estimator. This study is based on simulating the faulty motor on phase (abc) frame. Insensitivity of the technique to load variation, supply voltage variation and unbalance in supply voltage is Illustrated in this paper. The results from this study suggests that the proposed method provides a powerful and a general approach to the ANN based fault detection. | ||||
| Keywords | ||||
| Induction motor; Neural network; Turn fault detection | ||||
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