Intelligent System Design for Stator Windings Faults Diagnosis: Suitable for Maintenance Work

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ISSN Print: 1945-3116
ISSN Online: 1945-3124
www.scirp.org/journal/jsea
E-mail: jsea@scirp.org

"Intelligent System Design for Stator Windings Faults Diagnosis: Suitable for Maintenance Work"
written by Lane M. Rabelo Baccarini, Vinícius S. Avelar, Valceres Vieira R. E. Silva, Gleison F. V. Amaral,
published by Journal of Software Engineering and Applications, Vol.6 No.10, 2013

has been cited by the following article(s):

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[5]	The design of multiple linear regression models using a genetic algorithm to diagnose initial short-circuit faults in 3-phase induction motors
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[6]	Fault Analysis and Predictive Maintenance of Induction Motor Using Machine Learning
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[7]	Application of intelligent tools to detect and classify broken rotor bars in three-phase induction motors fed by an inverter
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[8]	An application of artificial neural networks and PCA for stator fault diagnosis in inverter-fed induction motors
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[9]	Application of intelligent tools to detect and classify broken rotor bars in three‐phase induction motors fed by an inverter
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[10]	Evaluation of stator winding faults severity in inverter-fed induction motors
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[1]	An integrated machine learning: Utility theory framework for real-time predictive maintenance in pumping systems Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2021 DOI:10.1177/0954405420970517

[2]	The design of multiple linear regression models using a genetic algorithm to diagnose initial short-circuit faults in 3-phase induction motors Applied Soft Computing, 2018 DOI:10.1016/j.asoc.2017.11.015

[3]	Fault Analysis and Predictive Maintenance of Induction Motor Using Machine Learning 2018 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), 2018 DOI:10.1109/ICEECCOT43722.2018.9001543

[4]	Application of intelligent tools to detect and classify broken rotor bars in three-phase induction motors fed by an inverter IET Electric Power Applications, 2016 DOI:10.1049/iet-epa.2015.0469

[5]	An application of artificial neural networks and PCA for stator fault diagnosis in inverter-fed induction motors 2016 XXII International Conference on Electrical Machines (ICEM), 2016 DOI:10.1109/ICELMACH.2016.7732822

[6]	Evaluation of stator winding faults severity in inverter-fed induction motors Applied Soft Computing, 2015 DOI:10.1016/j.asoc.2015.03.053

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