CORRECTION article

Front. Energy Res., 27 June 2023

Sec. Smart Grids

Volume 11 - 2023 | https://doi.org/10.3389/fenrg.2023.1232841

Corrigendum: Transformer fault diagnosis based on probabilistic neural networks combined with vibration and noise characteristics

  • 1. State Grid Ningxia Electric Power Co., Ltd., Electric Power Research Institute, Yinchuan, China

  • 2. School of Electrical Engineering, Shenyang University of Technology, Shengyang, China

  • 3. Maintenance Company of State Grid Ningxia Electric Power Co., Ltd., Yinchuan, China

In the published article, there was an error in the Funding statement. The sentence “Science and Technology Project of State Grid Ningxia Electric Power Co., Ltd. (5229DK200051)” is incorrect. The correct sentence appears below.

“Science and Technology Project of State Grid Ningxia Electric Power Co., Ltd. (5229DK20004N).”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Statements

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Summary

Keywords

transformer, vibration and noise, probabilistic neural networks, DC bias, multi-point grounding, short-circuit between silicon steel sheets, fault diagnosis

Citation

Zhou X, Luo Y, Tian T, Bai H, Wu P and Liu W (2023) Corrigendum: Transformer fault diagnosis based on probabilistic neural networks combined with vibration and noise characteristics. Front. Energy Res. 11:1232841. doi: 10.3389/fenrg.2023.1232841

Received

01 June 2023

Accepted

21 June 2023

Published

27 June 2023

Approved by

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Volume

11 - 2023

Updates

Copyright

*Correspondence: Tian Tian,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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