Advanced Online Monitoring and Fault Diagnosis of Power Equipment
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".
Deadline for manuscript submissions: 31 January 2025 | Viewed by 139
Special Issue Editors
Interests: power equipment protection and control; fault analysis and diagnosis of power equipment
Special Issues, Collections and Topics in MDPI journals
Interests: vibration and noise analysis of power equipment
Interests: multi-energy system modeling and security analysis; distribution network security analysis, planning, and operation; new energy development planning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Power equipment is the fundamental component of the power system. Its reliability and stability can guarantee the safe and efficient operation of the system. With the development of the power system, the voltage level continues to rise. High-frequency and high-intensity voltage shocks affect the operational reliability of the power equipment. Moreover, the proportion of new energy sources connected to the grid has significantly increased. Since they are connected to the grid through electronic power equipment, the complexity of harmonic components in the power system is exacerbated. Thus, problems with insulation aging and equipment overheating are accelerating, and the lifespan of equipment is shortening. The above issues pose serious challenges to the safety of power equipment. However, traditional equipment monitoring and fault diagnosis methods are difficult to use in order to cope with unexpected situations and have high operational risks and maintenance costs, low diagnostic accuracy, and a lack of generalizability for equipment with different parameters. Therefore, there is an urgent need for advanced online monitoring and fault diagnosis methods for power equipment to achieve real-time comprehensive status monitoring and accurate fault diagnosis.
Dr. Yikai Wang
Dr. Jiayi Guo
Dr. Chenhui Song
Dr. Junjie Hou
Guest Editors
Manuscript Submission Information
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Keywords
- power equipment protection
- online monitoring
- application of artificial intelligence in fault diagnosis
- mechanical faults
- partial discharge
- insulation deterioration
- fiber optic sensing
- on-load tap changer
- multi-parameter fusion
