An Embedded System for Stator Short-Circuit Diagnosis in Three-Phase Induction Motors Using Information Theory and Artificial Neural Networks-Reference-Cited by-同舟云学术

An Embedded System for Stator Short-Circuit Diagnosis in Three-Phase Induction Motors Using Information Theory and Artificial Neural Networks

Published:2022-10 Issue:10 Volume:52 Page:6582-6592
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Bazan Gustavo Henrique¹^ORCID,Goedtel Alessandro²^ORCID,Scalassara Paulo Rogerio²^ORCID,Endo Wagner²^ORCID,Nunes Erick Araujo³^ORCID,Takase Victor Takeo Ferreira²,Guedes Jacqueline Jordan²,Gentil Murillo Garcia²

Affiliation:

1. Department of Control and Industrial Process, Federal Institute of Paraná, Jacarezinho, Brazil

2. Department of Electrical Engineering, Federal University of Technology—Paraná, Cornélio Procópio, Brazil

3. Department of Telecommunication and Control Engineering, University of São Paulo, São Paulo, Brazil

Funder

National Council for Technological and Scientific Development

Coordination for the Improvement of Higher Level Personnel

Araucària Foundation for the Support of the Scientific and Technological Development of the State of Paranà

Federal University of Technology—Paranà

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221021/9893286/09714201.pdf?arnumber=9714201

Reference33 articles.

1. Stator End-Winding Thermal and Magnetic Sensor Arrays for Online Stator Inter-Turn Fault Detection

2. The Measurement of Observer Agreement for Categorical Data

3. Artificial Neural Networks

4. Comprehensive Diagnostics of Induction Motor Faults Based on Measurement of Space and Time Dependencies of Air Gap Flux

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