储能科学与技术 ›› 2024, Vol. 13 ›› Issue (8): 2758-2760.doi: 10.19799/j.cnki.2095-4239.2024.0696

• 储能系统与工程 • 上一篇    下一篇

基于声纹特征的储能型变压器运维检测技术

宋金伟1(), 宣东海1, 王维佳2, 孙飞2, 宋彦3   

  1. 1.国家电网有限公司大数据中心,北京 100052
    2.安徽继远软件有限公司,安徽 合肥 230088
    3.中国科学技术大学信息科学技术学院,安徽 合肥 230041
  • 收稿日期:2024-07-29 修回日期:2024-08-02 出版日期:2024-08-28 发布日期:2024-08-15
  • 通讯作者: 宋金伟 E-mail:songjinwei1212@163.com
  • 作者简介:宋金伟(1983—),男,博士,高级工程师,研究方向为人工智能、大数据、图计算技术,E-mail:songjinwei1212@163.com
  • 基金资助:
    国网大数据中心科技项目(SGSJ0000SJJS2100079)

Operation and maintenance detection technology for energy storage transformers based on voiceprint features

Jinwei SONG1(), Donghai XUAN1, Weijia WANG2, Fei SUN2, Yan SONG3   

  1. 1.Big Data Center, State Grid, Beijing 100052, China
    2.Anhui Jiyuan Software Co. , Ltd, Hefei 230088, Anhui, China
    3.School of Information and Technology, University of Science and Technology of China, Hefei 230041, Anhui, China
  • Received:2024-07-29 Revised:2024-08-02 Online:2024-08-28 Published:2024-08-15
  • Contact: Jinwei SONG E-mail:songjinwei1212@163.com

摘要:

噪声声纹情况可以提取大量储能变压器机械状态信息,基于声纹特征与振动信号成型分析法是变压器机械状态检测中较为先进的一种手段。对此,本文结合实际情况综述了声纹特征下储能型变压器的运维检测技术。首先结合实例分析了目前国内外常用优质的声纹振动检测技术研究发展情况,然后从绕组振动原理、铁心振动原理和直流偏磁下铁心振动情况三个方面分析储能变压器振动模型。最后归纳总结了各类变压器特征诊断办法,实现变压器的问题检测。

关键词: 声纹特征, 储能, 变压器, 振动

Abstract:

The noise voiceprint situation can extract a large amount of mechanical status information of energy storage transformers. The method based on voiceprint features and vibration signal shaping analysis is a more advanced means in transformer mechanical status detection. This article summarizes the operation and maintenance detection techniques of energy storage transformers based on voiceprint characteristics, combined with practical situations. Firstly, the research and development status of commonly used high-quality voiceprint vibration detection technologies at home and abroad were analyzed through examples. Then, the vibration model of energy storage transformers was divided from three aspects: winding vibration principle, iron core vibration principle, and iron core vibration under DC bias magnetization. Finally, various transformer feature diagnosis methods were summarized to achieve transformer problem detection.

Key words: voiceprint features, energy storage, transformer, vibration

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