🎓 Education & Experience:
Dr. Cao Chen completed his postdoctoral research at Shenyang University of Technology between 2018 and 2020. He then transitioned to academia, first as a Lecturer (2020-2021) and later as an Associate Professor (2021-present) at the School of Electrical Engineering, Shenyang University of Technology. His extensive teaching portfolio includes undergraduate and postgraduate courses on electrical engineering, switchgear disconnection technology, and energy and power engineering.
🏆 Awards and Honors:
Dr. Cao Chen has received numerous prestigious awards, including the Liaoning Provincial Science and Technology Progress Second Prize (2024, First Completer) and First Prize (2019) for advancements in transformer performance enhancement and switchgear flexibility. Additionally, he has won China Machinery Industry Science and Technology First Prizes (2016, 2024) for his pioneering work in high-voltage switching and overvoltage suppression technologies. He is also actively involved in IEEE PES Power Interruption Technical Committee (China) and multiple committees of the China Electrotechnical Society.
🔬 Research Focus:
Dr. Cao Chen’s research revolves around transformer diagnostics, power equipment reliability, and fault detection. His work focuses on developing advanced online monitoring and fault diagnosis techniques for power transformers using vibration-based methods and multi-source data fusion. He has spearheaded multiple projects funded by the National Natural Science Foundation of China, provincial departments, and corporate enterprises, driving innovation in power system reliability.
🔚 Conclusion:
Dr. Cao Chen is a pioneering researcher and educator in electrical engineering, particularly in power equipment diagnostics and fault analysis. His groundbreaking work in transformer monitoring, fault detection, and power system reliability has earned him national and international recognition. As a leader in scientific research, a dedicated professor, and a key contributor to industrial advancements, he continues to push the boundaries of electrical engineering through innovative solutions and impactful research. 🚀
📖 Publications:
State Diagnosis Method of Transformer Winding Deformation Based on Fusing Vibration and Reactance Parameters. IET Electric Power Applications. (Cited in SCI Zone 2)
Research on Simulation Analysis and Joint Diagnosis Algorithm of Transformer Core-Loosening Faults Based on Vibration Characteristics. Energies. (Read here)
Transformer winding mechanical state diagnosis method based on current-frequency-vibration parameters. Journal of Electric Machines and Control.
Magnetostrictive vibration model and loose fault diagnosis method of transformer core based on elastic mechanics-thermodynamics. High Voltage Technology.
Monitoring Method on Loosened State and Deformational Fault of Transformer Winding Based on Vibration and Reactance Information. IEEE ACCESS. (Cited in SCI Zone 1)