<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This article constitutes an introductory part of the special section on Intelligent Fault Monitoring and Fault-Tolerant Control in Power Electronics, Drives and Renewable Energy Systems. In the current issue of the journal, the first part of this section is published. Accepted articles are focussed mainly on the sensor-fault diagnosis methods for T-type inverter-fed dual-three phase PMSM drives, partial demagnetization, faults of the permanent magnet synchronous generator (PMSG) and online open phase fault detection (FD) in the sensorless five-phase induction motor drive implemented with an inverter output LC filter and third harmonic injection. Also, neural networks (NN) application in the detection of stator and rotor electrical faults of induction motors has been proposed in one of the papers, and the observer-based FD concept for unknown systems using input–output measurements was applied to a brushless direct current motor drive with unknown parameters.</p></abstract>

This article constitutes an introductory part of the special section on Intelligent Fault Monitoring and Fault-Tolerant Control in Power Electronics, Drives and Renewable Energy Systems. In the current issue of the journal, the first part of this section is published. Accepted articles are focussed mainly on the sensor-fault diagnosis methods for T-type inverter-fed dual-three phase PMSM drives, partial demagnetization, faults of the permanent magnet synchronous generator (PMSG) and online open phase fault detection (FD) in the sensorless five-phase induction motor drive implemented with an inverter output LC filter and third harmonic injection. Also, neural networks (NN) application in the detection of stator and rotor electrical faults of induction motors has been proposed in one of the papers, and the observer-based FD concept for unknown systems using input–output measurements was applied to a brushless direct current motor drive with unknown parameters.

Introduction to the Special Section on Intelligent Fault Monitoring and Fault–Tolerant Control in Power Electronics, Drives and Renewable Energy Systems

Institute of Control and Industrial Electronics

Department of Electronics and Electrical Engineering

Department of Electrical Machines, Drives and Measurements

Wroclaw University of Science and Technology

Power Electronics and Drives

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

This article constitutes an introductory part of the special section on Intelligent Fault Monitoring and Fault-Tolerant Control in Power Electronics, Drives...

Introduction to the Special Section on Intelligent Fault Monitoring and Fault–Tolerant Control in Power Electronics, Drives and Renewable Energy Systems

Online veröffentlicht: 26. Nov. 2019

Seitenbereich: 163 - 165

Eingereicht: 06. Okt. 2019

Akzeptiert: 06. Okt. 2019

DOI: https://doi.org/10.2478/pead-2019-0016

Schlüsselwörter
electrical drives, permanent-magnet machines, induction motors, sensor faults, winding faults, demagnetization faults, neural networks, observers

© 2019 Mariusz Malinowski et al., published by Sciendo

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

Introduction to the Special Section on Intelligent Fault Monitoring and Fault–Tolerant Control in Power Electronics, Drives and Renewable Energy Systems

Online veröffentlicht: 26. Nov. 2019

Seitenbereich: 163 - 165

Eingereicht: 06. Okt. 2019

Akzeptiert: 06. Okt. 2019

DOI: https://doi.org/10.2478/pead-2019-0016

Schlüsselwörterelectrical drives, permanent-magnet machines, induction motors, sensor faults, winding faults, demagnetization faults, neural networks, observers

© 2019 Mariusz Malinowski et al., published by Sciendo

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

Schlüsselwörter
electrical drives, permanent-magnet machines, induction motors, sensor faults, winding faults, demagnetization faults, neural networks, observers