Application of radial basis neural networks for the rotor fault detection of the induction motor

Application of radial basis neural networks for the rotor fault detection of the induction motor

The main stages of the design methodology of the radial basis neural detectors are described. Furthermore, influence of neural networks complexity and parameters of RBF activation function on quality of data classification is shown. Presented neural detectors are tested with data obtained in laborat...

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Bibliographische Detailangaben
Hauptverfasser: Kaminski, M., Kowalski, C. T., Orlowska-Kowalska, T.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial neural networks
Bars
diagnostic symptoms
Fault detection
fault detector
induction motor
Induction motors
Neurons
RBF neural networks
rotor fault
Rotors
Stators
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Beschreibung
Zusammenfassung:The main stages of the design methodology of the radial basis neural detectors are described. Furthermore, influence of neural networks complexity and parameters of RBF activation function on quality of data classification is shown. Presented neural detectors are tested with data obtained in laboratory setup contained of converter-fed induction motor and changeable rotors with different degree of damages.
DOI:10.1109/EUROCON.2011.5929405