Smart and Digital Technologies for Power Transformers: Design, Monitoring, and Applications
A special issue of Technologies (ISSN 2227-7080).
Deadline for manuscript submissions: 31 December 2026 | Viewed by 150
Special Issue Editors
Interests: signal processing; machine learning; deep learning; fault diagnosis; electric machines; bio-inspired algorithms; optimization techniques; cyber–physical systems
Special Issues, Collections and Topics in MDPI journals
Interests: signal processing; digital systems; embedded systems; digital design; machine learning; fault diagnosis; electric machines.
Interests: design of transformers; design of electromagnetic equipment; maintenance of electromagnetic equipment; diagnostics of failures in electromagnetic equipment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Power transformers are critical components in modern electrical systems, ensuring efficient and reliable power transmission. Their design, operation, and maintenance have evolved through ongoing digital transformation and the integration of intelligent systems. Moreover, recent advances in sensing technologies, data analytics, artificial intelligence, and the Internet of Things (IoT) have opened up new opportunities for the development of smart transformers, predictive maintenance frameworks, and advanced diagnostic tools.
This Special Issue aims to gather original research articles, reviews, and case studies focused on innovative methodologies, technologies, and applications for the next generation of power transformers. Topics of interest include the use of smart sensors, digital twins, big data analytics, machine learning and deep learning for design optimization, condition monitoring, fault diagnosis, and asset management.
Dr. Martin Valtierra-Rodriguez
Dr. David Camarena-Martinez
Dr. Juan C. Olivares-Galvan
Guest Editors
Manuscript Submission Information
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Keywords
- fault diagnosis
- intelligent algorithms
- signal processing
- condition monitoring
- predictive maintenance
- cyber–physical systems
- optimization techniques
- machine learning
- bio-inspired computation
- Internet of Things (IoT)
- edge computing
- digital twins
- embedded systems
- new designs
- wireless sensor networks
- edge computing
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