Duan Jiajun, male, Ph.D., graduated from the School of Electrical Engineering and Automation, Wuhan University in June 2022 with a Ph.D. degree in Electrical Engineering (Supervisor: Professor He Yigang). In June of the same year, he joined the School of Automation, Nanjing University of Information Scinece & Technology (NUIST). He's currently engaged in the research of transformer condition monitoring and fault diagnosis, et al. He's published 7 academic papers (as the first author), and authorized a total of 12 invention patents, including 2 US invention patents.

publish academic papers: 

[1] Duan Jiajun, He Yigang, et al. Serial transfer learning (STL) theory for processing data insufficiency: Fault diagnosis of transformer windings[J]. International Journal of Electrical Power & Energy Systems, 2021, 130:106965.  (SCI) 

[2] Duan Jiajun, He Yigang, et al. A space hybridization theory for dealing with data insufficiency in intelligent power equipment diagnosis[J]. Electric Power Systems Research, 2021, 199:107363.  (SCI) 

[3] Duan Jiajun, He Yigang, et al. Anti-interference deep visual identification method for fault localization of transformer using a winding model[J]. Sensors, 2019, 19(19):4153.  (SCI) 

[4] Duan Jiajun, He Yigang, et al. Intelligent localization of transformer internal degradations combining deep convolutional neural networks and image segmentation[J]. IEEE Access, 2019, 7:62705-62720. (SCI) 

[5] Duan Jiajun, He Yigang, et al. Fault localization on transformer winding by frequency response analysis and evidential reasoning[C], International Symposium on Test Automation and Instrumentation (ISTAI), Dalian, 2019:9079-9082. (EI) 

[6] Duan Jiajun, He Yigang, et al. Assisted diagnosis of real-virtual twin space for data insufficiency[C], The 9th Frontier Academic Forum of Electrical Engineering (FAFEE), Xi'an, 2021:387-395. (EI) 

[7] 段嘉珺, 应黎明, 等. 基于诱导有序加权证据推理方法的不完全信息下继电保护系统健康状态评价[J]. Power System Protection and Control, 2018, 46(06):106-112. 

Patents：

[1] (Authorized) 深度卷积神经网络融合视觉辨识的电力变压器绕组故障定位方法[P]. ZL201910740874.3, China Invention Patent. 

[2] (Authorized) 基于多阶段迁移学习的变压器故障辨识与定位诊断方法[P]. ZL201911261469.X, China Invention Patent. 

[3] (Authorized) 基于虚实孪生空间的电力设备小样本故障诊断方法及系统[P]. ZL202010273965.3, China Invention Patent. 

[4] (Authorized) 一种基于Bi-LSTM和油中溶解气体分析的变压器故障诊断方法[P]. ZL201910628714.X, China Invention Patent. 

[5] (Authorized) 基于加窗特征希尔伯特图像化的电力设备诊断方法及系统[P]. ZL202010449882.5, China Invention Patent. 

[6] (Authorized) 变压器油中溶解气体的深度并行故障诊断方法及系统[P]. ZL202010134616.3, China Invention Patent. 

[7] (Authorized) 一种单相半桥五电平逆变器开关管开路故障诊断方法[P]. ZL202011508386.9, China Invention Patent. 

[8] (Authorized) 一种地线取能装置[P]. ZL201821532954.7, 实用新型专利. 

[9] (Authorized) 一种基于GSMallat-NIN-CNN网络的电力变压器绕组故障诊断方法[P]. ZL202010513387.6, China Invention Patent. 

[10] (Authorized) 一种Nakagami衰落信道的测试系统及其验证方法[P]. ZL201810201309.5, China Invention Patent. 

[11] (Authorized) 一种抑制多相电机共模电压的空间矢量脉宽调制方法[P]. ZL201810147029.0, China Invention Patent. 

[12] (Authorized) Deep Belief Network feature extraction-based analogue circuit fault diagnosis method[P]. US20190243735, utility patent. 

[13] (Authorized) Space vector pulse width modulation method for suppressing common-mode voltage of multiphase motor[P]. US20190253015, utility patent.

Study and work experiences: 

2012.09-2016.06, Chongqing University, electrical engineering and automation, Bachelor's degree；

2016.09-2022.06, Wuhan University, electrical engineering, PhD；

2022.07-, Nanjing University of Information Science & Technology(NUIST), School of Automation, lecturer；