242 / 2021-11-04 10:15:14
State Identification of Transformers under DC Bias Based on Nonlinear Vibration Feature
Extreme learning machine,DC bias,Mutual information,Transformer vibration
Final Paper
Jing Wu / Zhejiang Dayou Industrial Co., Ltd
Jie Xu / Zhejiang Dayou Industrial Co., Ltd
Weiyan Zheng / Zhejiang Dayou Industrial Co., Ltd
Ming Jin / Zhejiang Dayou Industrial Co., Ltd
Jingchun Zhang / China Jiliang University
Guoping Zou / Zhejiang University
Power transformers under DC bias means that there is a DC component in the magnetic flux, which has an important impact on the vibration of transformer. In this paper, the mechanism of the transformer vibration caused by magnetic DC bias is reviewed. Next, a feature extraction method based on vibration mutual information is proposed, and a neutral point current prediction model based on the extreme learning machine (ELM) algorithm is also established. Finally, experiments are conducted to verify the feature extraction method, and the neutral point current prediction model is trained and tested. The results show that the extracted nonlinear vibration feature combined with the ELM method can identify the transformer state under DC bias.
Important Date
  • Conference Date

    Jul 11

    2023

    to

    Aug 18

    2023

  • Nov 10 2021

    Draft paper submission deadline

  • Dec 10 2021

    Registration deadline

  • Dec 11 2021

    Contribution Submission Deadline

Sponsored By
IEEE IAS
Organized By
IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST