Fault Diagnosis and Condition Monitoring of Electrical Machines and Drives
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Automation Control Systems".
Deadline for manuscript submissions: 20 December 2025 | Viewed by 5
Special Issue Editors
Interests: integrated starter generator; multi-phase synchronous generator; fault diagnosis; motor drive
Interests: integrated starter-generator; PMSM; fault diagnosis; position-sensorless control; motor drive
Special Issues, Collections and Topics in MDPI journals
Interests: permanent magnet synchronous machines; brushless wound-rotor synchronous starter-generator; motor control; fault diagnosis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the rapid development of electric transportation, intelligent manufacturing, and energy technologies, the demand for high-reliability electrical machine systems in critical application scenarios has become increasingly prominent. Reducing maintenance costs and preventing unscheduled downtimes, which cause production and economic losses, are a priority for manufacturers and operators. The correct diagnosis and early detection of incipient faults lead to reduced maintenance costs and downtime for the process under consideration, and, in many cases, also prevent harmful and sometimes disruptive failures. Moreover, the comprehension of the fault occurrence conditions and the fault detection and location are the foundation for the study of effective fault-tolerant techniques, since the latter must always include fault detection, the isolation of failed component, and component reconfiguration.
This Special Issue aims to provide an opportunity for scientists, researchers, and practicing engineers to share and disseminate their latest discoveries and results in the fields, indicating the future trends for the fault diagnosis and condition monitoring of electrical machines and drives. Topics include, but are not limited to, the following research areas:
(1) Simulation techniques, algorithms, or other tools for modeling and simulation;
(2) Innovative sensors and their applications in motor systems;
(3) Intelligent sensing technologies and multi-source information fusion for electrical machine systems;
(4) Advanced fault diagnosis and condition monitoring methods.
Dr. Chenghao Sun
Dr. Ningfei Jiao
Dr. Ji Pang
Guest Editors
Manuscript Submission Information
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Keywords
- electrical machines
- fault diagnosis
- condition monitoring
- feature extraction
- innovative sensors
- interturn short circuit
- faults of power devices
- demagnetization
- faults of bearings
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