Fault Diagnosis for Electrical Machines, Power Electronics, and Drives

Dear Colleagues,

Electrical machines are key elements in power systems since they allow the transformation of electric power into useful mechanical action, and vice versa. As a consequence, a correct fault diagnosis is required to reduce the maintenance time of these devices.

With the increasing demand of smart processes and in the search of sustainability, more efficient power systems are required. Nowadays, electrical machines are connected to power electronics creating electrical drives. The pulsed voltage waves provided from power electronics produce a faster aging of the insulation materials of the electrical machines, increasing the fault probability, not only of electrical faults but also mechanical and magnetic faults. Furthermore, additional faults can be found in the power electronics involved.

With the implementation of this type of technology, most of the actual protections produce unwanted tripping because of high-frequency converter noises, leakage currents, non-sinusoidal waveforms, or variable operation frequency, among others. In this field, new diagnosis techniques must be developed in order to satisfy the problem.

This Special Issue is focused in searching for new and efficient trends in fault diagnosis for electrical machines, power electronics or its ensemble, electrical drives. The Issue is focused but not limited to the following topics:

• Electrical machines fault diagnosis (Induction, synchronous or DC machines);
• Especial electrical machines diagnosis (linear, axial flux machines or other non-standard machines);
• Power electronics fault diagnosis ;
• Fault diagnosis in power applications involving power electronics (batteries, supercapacitors, …);
• New power converter topologies (For example: modular multilevel converters, partial power converters, exciter and rotor placed power electronics);
• Electric drives fault diagnosis;
• Electric transportation systems fault diagnosis (aircrafts, ships or electric locomotives among others);
• New fault detection, classification and fault location methods;
• Industrial and laboratory experiments, studies about fault parameters behavior and/or features extraction for fault diagnosis;
• Smart diagnosis (data driven techniques, cloud computing, digital twins diagnosis, etc.);
• The use of AI in fault diagnosis for electrical machines, power electronics and drives;
• Literature reviews involving the previous scopes.

Dr. Jose M. Guerrero
Dr. Araitz Iturregi
Dr. Sergio Toscani
Guest Editors

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• fault diagnosis
• electrical machines
• power converters
• power electronics
• fault detection
• fault location
• fault classification
• electric drives
• power converters