Advances in Fault Diagnosis Methods of Power Systems and Key Components
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".
Deadline for manuscript submissions: 15 August 2026 | Viewed by 12
Special Issue Editors
Interests: pulsed power technology and its application; condition monitoring; fault diagnosing
Special Issues, Collections and Topics in MDPI journals
2. State Key Laboratory of Intelligent Power Distribution Equipment and System, Hebei University of Technology, Tianjing 300401, China
Interests: electrical equipment intelligent diagnosis and health management; high-reliability pulsed power technology; power equipment life-cycle management; advanced detection technology development
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the continuous expansion of the scale of power systems and the large-scale integration of renewable energy, the safe and stable operation of power systems and equipment faces increasingly severe challenges. Power systems and key components are prone to various faults, such as short circuits, discharges, overheating, mechanical failures, insulation faults, and moisture damage, which seriously affect the stability of the system. Therefore, it is crucial to detect and evaluate those faults. As a key technology to ensure the reliability of power systems and enhance the efficiency of the operation and maintenance of key components, fault diagnosis has made significant progress in terms of its theoretical methods, data-driven technologies, and intelligent applications in recent years.
This Special Issue aims to showcase the latest research and state-of-the-art contributions in fault diagnosis, condition monitoring, and health assessment for power systems and key components. It will aim to provide solutions for the difficulties faced in safety assurance, and also aims to yield insights related to the efficiency, security, reliability, and sustainability of power systems and equipment.
In this Special Issue, original research articles and reviews are welcome. Research areas may include, but are not limited to, the following:
- Condition monitoring of power systems;
- Fault diagnosis of transformers, machines, reactors, cables, etc.;
- Innovative applications of technologies such as signal processing and image recognition;
- Multi-source data fusion and intelligent analysis;
- New fault diagnosis methods based on machine learning and deep learning.
We look forward to receiving your contributions.
Dr. Zhongyong Zhao
Dr. Xiaozhen Zhao
Guest Editors
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Keywords
- fault diagnosis
- fault detection
- condition monitoring
- power system
- power equipment
- application of artificial intelligence
- deep learning
- insulation fault
- mechanical fault
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