Special Session SS07

Intelligent Condition Sensing and Health Management of Electrical Equipment

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Introduction:

Medium- and high-frequency electrical equipment, represented by inverter-fed motors and medium/high-frequency transformers, is crucial for the development of electrified transportation and modern distribution networks. Under operating conditions characterized by high-frequency pulse voltages and multi-stress coupling, issues such as winding insulation aging, performance degradation, and sudden equipment faults have become increasingly prominent. However, due to the difficulty of internal condition sensing and the complexity of failure mechanisms under multi-stress conditions, achieving accurate condition sensing and scientific health management of electrical equipment has emerged as a major challenge. This special session aims to explore new theories and methods that integrate failure mechanism analysis, advanced sensing technologies, digital twins, and physics-informed neural networks (PINNs). The session focuses on the failure mechanisms and condition evolution laws of electrical equipment, exploring cutting-edge technologies such as intelligent early fault warning, online partial discharge monitoring, insulation reliability assessment, and lifetime prediction. Ultimately, it seeks to provide innovative solutions for the safe and stable operation and full-lifecycle maintenance of electrical equipment.
The topics of interest include, but are not limited to:
1. Failure mechanisms and degradation modeling of electrical equipment;
2. Intelligent condition sensing and sensor technologies for electrical equipment;
3. Partial discharge detection and online monitoring technologies;
4. Insulation reliability assessment and lifetime prediction methods;
5. Fault diagnosis and early warning for electrical equipment;
6. Equipment condition assessment and health management based on digital twins;
7. Intelligent maintenance integrating data-driven and physics-based models;
8. Applications of artificial intelligence in equipment condition monitoring;
9. New technologies for condition assessment of motors and transformers;
10. Multiphysics analysis, testing, and evaluation of medium- and high-frequency electrical equipment.

SS07's Session Chair:

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Assoc. Prof. Yatai Ji, North China Electric Power University, China

SS07's Session Co-chairs:

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Assoc. Res. Prof. Hengliang Zhang, Southeast University, China

Assoc. Prof. Dayong Zheng, Beijing Jiaotong University, China

Lect. Xiaowei Ju, Shenyang University of Technology, China

Asst. Res. Dongbo Guo, Tsinghua University, China