Review for AI-based Open-Circuit Faults Diagnosis Methods in Power Electronics Converters
It addresses fault diagnosis for power electronics converters in aerospace and energy systems, but is incremental as it builds on existing review and proposes a hybrid method.
The paper reviews AI-based methods for diagnosing open-circuit faults in power electronics converters, proposing a method combining random forests and transient fault features to improve reliability and reduce maintenance costs.
Power electronics converters have been widely used in aerospace system, DC transmission, distributed energy, smart grid and so forth, and the reliability of power electronics converters has been a hotspot in academia and industry. It is of great significance to carry out power electronics converters open-circuit faults monitoring and intelligent fault diagnosis to avoid secondary faults, reduce time and cost of operation and maintenance, and improve the reliability of power electronics system. Firstly, the faults features of power electronic converters are analyzed and summarized. Secondly, some AI-based fault diagnosis methods and application examples in power electronics converters are reviewed, and a fault diagnosis method based on the combination of random forests and transient fault features is proposed for three-phase power electronics converters. Finally, the future research challenges and directions of AI-based fault diagnosis methods are pointed out.