计及电磁模特高频信号的局部放电模式识别方法
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TM855

基金项目:

中国南方电网有限责任公司科技项目(GZHKJXM20200001)


Pattern recognition of UHF signals in partial discharge considering electromagnetic model
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    特高频(UHF)法局部放电检测已经成为高压GIS及变压器等设备常用的运维检测手段,但由于该方法是通过测量电磁波间接检测局部放电强度,使得基于该方法的局部放电模式识别技术准确率不高,而且一直没有得到很好的解决。本文引入TEm1模截止频率作为PD UHF信号时频分布图的分割依据,对单一绝缘缺陷激发的PD UHF信号进行预处理、时频分布图分割、特征参数提取和选择以及PSO-ELM识别等操作,最终可准确判断出PD信号类型,提高GIS绝缘缺陷类型的识别准确率。这种分割方法增强了图谱特征的空间分布信息,对改善特高频法识别局部放电的准确率具有实际应用价值。

    Abstract:

    Detection of partial discharge by UHF signal has become an ordinary operation and maintenance detection method for High Voltage GIS, transformers, and other equipment. However, this method indirectly detects PD intensity by measuring electromagnetic waves, so the accuracy of PD pattern recognition technology based on this method is not high, and has not been well solved. This paper introduces the cut-off frequency of TEm1 mode as the division basis of the time-frequency distribution of the PD UHF signal. The PD UHF signal excited by a single insulation defect is used for signal preprocessing, time-frequency distribution segmentation, feature parameter extraction and selection, PSO-ELM recognition, and other operations. Finally, the PD signal type can be accurately determined and the identification accuracy of insulation defect types in GIS can be improved. This segmentation method enhances the spatial distribution information of image features, and it is of great practical value to improve the accuracy of the UHF method in PD identification.

    参考文献
    相似文献
    引证文献
引用本文

辛文成,姚森敬,陈浩敏,等.计及电磁模特高频信号的局部放电模式识别方法[J].电力科学与技术学报,2022,37(6):108-115.
XIN Wencheng, YAO Senjing, CHEN Haoming, et al. Pattern recognition of UHF signals in partial discharge considering electromagnetic model[J]. Journal of Electric Power Science and Technology,2022,37(6):108-115.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2023-01-16
  • 出版日期: