<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The possibility of using neural networks to detect eccentricity of induction motors has been presented. A field-circuit model, which was used to generate a diagnostic pattern has been discussed. The formulas describing characteristic fault frequencies for static, dynamic and mixed eccentricity, occurring in the stator current spectrum, have been presented. Teaching and testing data for neural networks based on a preliminary analysis of diagnostic signals (phase currents) have been prepared. Two types of neural networks were discussed: general regression neural network (GRNN) and multilayer perceptron (MLP) neural network. This paper presents the results obtained for each type of the neural network. Developed neural detectors are characterized by high detection effectiveness of induction motor eccentricity.</p></abstract>

The possibility of using neural networks to detect eccentricity of induction motors has been presented. A field-circuit model, which was used to generate a diagnostic pattern has been discussed. The formulas describing characteristic fault frequencies for static, dynamic and mixed eccentricity, occurring in the stator current spectrum, have been presented. Teaching and testing data for neural networks based on a preliminary analysis of diagnostic signals (phase currents) have been prepared. Two types of neural networks were discussed: general regression neural network (GRNN) and multilayer perceptron (MLP) neural network. This paper presents the results obtained for each type of the neural network. Developed neural detectors are characterized by high detection effectiveness of induction motor eccentricity.

Application of Neural Networks to Detect Eccentricity of Induction Motors

Wrocław University of Science and Technology

Power Electronics and Drives

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Application of Neural Networks to Detect Eccentricity of Induction Motors"}

The possibility of using neural networks to detect eccentricity of induction motors has been presented. A field-circuit model, which was used to generate a...

Application of Neural Networks to Detect Eccentricity of Induction Motors

Online veröffentlicht: 29. Dez. 2017

Seitenbereich: 151 - 165

Eingereicht: 18. Okt. 2017

Akzeptiert: 22. Nov. 2017

DOI: https://doi.org/10.5277/ped170209

Schlüsselwörter
neural network, general regression neural network, multilayer perceptron, eccentricity, induction motor

© 2017 Paweł Ewert, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Application of Neural Networks to Detect Eccentricity of Induction Motors

Online veröffentlicht: 29. Dez. 2017

Seitenbereich: 151 - 165

Eingereicht: 18. Okt. 2017

Akzeptiert: 22. Nov. 2017

DOI: https://doi.org/10.5277/ped170209

Schlüsselwörterneural network, general regression neural network, multilayer perceptron, eccentricity, induction motor

© 2017 Paweł Ewert, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
neural network, general regression neural network, multilayer perceptron, eccentricity, induction motor