Advanced Sensors and Artificial Intelligence for Condition Monitoring of Power Electronic Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 556
Special Issue Editors
Interests: model predictive control; power electronics; motor drive control; machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: power electronics; motor drive control; wide bandgap semiconductor
Interests: power electronics; machine learning; artificial intelligence; renewable energy; electric aircraft
Special Issues, Collections and Topics in MDPI journals
Interests: process automation; prototype design and construction for novel (manufacturing) processes; selection and assembling of components; retrofitting and reengineering (manufacturing) equipment
Special Issue Information
Dear Colleagues,
Advanced sensors and artificial intelligence (AI) are revolutionizing the condition monitoring of power electronic systems. On one hand, advanced sensors play a crucial role in monitoring the health and performance of power electronic systems. These sensors can detect various parameters such as temperature, current, and voltage, providing real-time data that are essential for predictive maintenance and fault diagnosis. The integration of advanced sensors allows for more accurate and timely detection of anomalies, which can prevent failures and extend the lifespan of systems with power electronics. On the other hand, AI enhances the capabilities of condition monitoring systems by analyzing the vast amounts of data collected by sensors. AI techniques such as machine learning and fuzzy logic can identify patterns and predict potential issues before leading to system failures.
Therefore, the integration of advanced sensors and AI provides a powerful approach to condition monitoring that paves the way for more intelligent and resilient power electronic systems, ensuring the efficient and reliable operation of power electronic systems.
Scope and Topics:
We welcome original research articles, review papers, and case studies on topics including, but not limited to, the following:
Advanced Sensor Technologies: Development and application of novel sensors for monitoring electrical, thermal, and mechanical parameters in power electronic systems.
AI and Machine Learning: Implementation of AI and machine learning algorithms for fault detection, diagnosis, and prognosis in power electronics.
Data Analytics: Techniques for processing and analyzing large datasets from sensors to extract meaningful insights for condition monitoring.
Predictive Maintenance: Strategies for predictive maintenance using sensor data and AI to enhance the reliability and lifespan of power electronic systems.
Integration and Implementation: Challenges and solutions for integrating advanced sensors and AI into existing power electronic systems.
Case Studies and Applications: Real-world applications and case studies demonstrating the effectiveness of advanced sensors and AI in condition monitoring.
Dr. Yuan Gao
Dr. Haihong Qin
Dr. Yu Zeng
Guest Editors
Dr. Victor Cedeno-Campos
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- sensors
- artificial intelligence
- condition monitoring
- power electronic systems
- predictive maintenance
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