Academic Seminar — IoT-Based Online Degradation Assessment and Fault Prediction for Power Equipment
Dr. Yuehan Qu from the School of Electrical Engineering delivered an academic seminar titled “Online Degradation Assessment and Fault Prediction of Power Equipment Based on IoT Sensing Technologies” on November 5, 2025, in Room A412 of the Electrotechnics Building, Northeast Electric Power University.
The seminar introduced recent advances in online degradation evaluation, deterioration indicators, prediction models under incomplete data, and failure forecasting considering probabilistic thresholds. Dr. Qu also discussed challenges brought by high-penetration renewables and large-scale power electronic interfaces, as well as the development of intelligent O&M cloud platforms.
The event attracted faculty members, master’s and PhD students, and featured active discussion on degradation mechanisms, simulation scenarios, and predictive algorithms.
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- Northeast Electric Power University
- School of Electrical Engineering
- Jilin, Jilin
- China 132012
- Building: Electrical Engineering Building
- Room Number: A412
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For inquiries regarding this seminar or Chapter activities, please contact:
Dr. Yang Li
Chair, IEEE Systems Council Harbin Section Chapter (CH11207)
Email: liyangnedu@gmail.comCo-organizing Institution:
School of Electrical Engineering,
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Speakers
Yuehan Qu of School of Electrical Engineering, Northeast Electric Power University
Online Degradation Assessment and Fault Prediction of Power Equipment Based on IoT Sensing Technologies
This seminar introduces an integrated framework for online degradation assessment and fault prediction of power equipment using IoT-based sensing technologies. It covers the construction of comprehensive degradation indicators, online evaluation models suited for complex field conditions, prediction algorithms under incomplete data, and fault forecasting mechanisms considering stochastic threshold distributions. The talk also discusses new damage pathways and failure mechanisms arising from high-penetration renewables and power electronic devices.
Biography:
Dr. Yuehan Qu received his Ph.D. degree from North China Electric Power University and is currently an Associate Professor at the School of Electrical Engineering, Northeast Electric Power University, as well as a master's supervisor and selected talent of Jilin Province.
His research focuses on degradation mechanisms and fault prediction of power equipment. Over the past four years, he has conducted R&D on online monitoring, damage assessment, fault prediction algorithms, and intelligent operation-and-maintenance platforms for power equipment. His recent work emphasizes new damage pathways, fault mechanisms, and smart O&M strategies arising from high-penetration renewable energy and large-scale power electronic device integration.
Dr. Qu has led or participated in one provincial-level project, one departmental project, and three industry-sponsored projects, and has published over ten SCI/EI-indexed papers. He serves as a reviewer for several international journals, including IEEE Transactions on Reliability, Scientific Reports, Electrical Engineering, and IET Generation, Transmission & Distribution.
Email:
Address:No. 169 Changchun Road, School of Electrical Engineering, Jilin, Jilin, China, 132012
Agenda
Agenda (14:00-16:00)
14:00 – 14:10
Opening Remarks & Speaker Introduction
Host: Prof. Ge Jinming, School of Electrical Engineering, Northeast Electric Power University
14:10 – 14:40
Session 1 – IoT-Based Sensing and Degradation Assessment Frameworks
• Background and significance of online degradation assessment
• IoT-enabled sensing technologies for power equipment health monitoring
• Construction of comprehensive degradation/damage indices
14:40 – 15:20
Session 2 – Degradation Modeling and Trend Prediction Methods
• Online degradation evaluation models for complex operating conditions
• Trend prediction under incomplete or uncertain degradation data
• Fault forecasting considering stochastic threshold characteristics
15:20 – 16:00
Q&A, Discussion & Interaction
Open discussion with faculty, master’s students, and PhD students on modeling challenges, forecasting mechanisms, and IoT-based health management.
Media
| Seminar Poster — IoT-Based Online Degradation Assessment and Fault Prediction for Power Equipment | Official poster for the academic seminar delivered by Dr. Yuehan Qu on November 5, 2025. The poster presents the seminar title, abstract, speaker biography, schedule, venue information, and online participation details. It highlights IoT-based online degradation assessment and fault prediction methods for power equipment as the seminar’s main theme. | 340.82 KiB |
| Lecture Photo — Seminar by Dr. Yuehan Qu (2025-11-05) | Lecture photo from the academic seminar delivered by Dr. Yuehan Qu at Northeast Electric Power University on November 5, 2025. The image captures the in-person session where Dr. Qu presented IoT-based approaches for online degradation assessment and fault prediction of power equipment, with active participation from students and faculty members. | 157.23 KiB |