Artificial neural networks broken rotor bars induction motor fault detection

@article{Matic2010ArtificialNN,
  title={Artificial neural networks broken rotor bars induction motor fault detection},
  author={Dragan Z. Matic and Filip Kulic and Vincente Climente-Alarcon and Ruben Puche-Panadero},
  journal={10th Symposium on Neural Network Applications in Electrical Engineering},
  year={2010},
  pages={49-53}
}
Paper deals with application of online rotor broken bar fault detection via artificial neural networks. Fault can be detected by monitoring abnormalities of the spectrum amplitudes at certain frequencies in the motor current spectrum. These discriminative features are used for training of feed-forward backpropagation artificial neural network. Trained network is capable to successfully classify induction motor rotor condition. Results are presented in tables and figures. 

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