...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE sensors journal >Condition Monitoring of Overhead Polymeric Insulators Employing Hyperbolic Window Stockwell Transform of Surface Leakage Current Signals
【24h】

Condition Monitoring of Overhead Polymeric Insulators Employing Hyperbolic Window Stockwell Transform of Surface Leakage Current Signals

机译：架空聚合物绝缘体的状态监测采用双曲窗口储存泄漏电流信号的变换

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this article, an efficient technique has been proposed to estimate the contamination level of overhead polymeric insulators. Deposition of contamination on polymeric insulator surface, is a serious issue as it often results in the flashover and even insulator failure. For estimating the severity of contamination level, surface leakage current (SLC) signals of a 11kV polymeric insulator with contaminated surface has been analyzed in time-frequency domain through hyperbolic window stockwell transform (HST). HST is more flexible than classical stockwell transform. Also, HST can able to handle both the low and high frequencies adequately. Considering the advantage, HST has been used here to estimate contamination degree from SLC signature. HST analysis of SLC signal returned a 2d complex time-frequency HS matrix. The complex time-frequency HS matrix has been separated into magnitude and phase spectrum. Based on the phase and magnitude spectrum, 15 statistical features, namely HST features has been extracted. Thereafter, 5 relevant HST features have been selected through least absolute shrinkage and selection operator (LASSO) feature selection technique. Finally, these relevant HST features are fed to four machine learning classifiers for estimation of contamination degree. It has also been observed that, the proposed framework method offered better classification accuracy compared to other standard time-frequency analysis and existing methods available in literature.
机译：在本文中，已经提出了一种有效的技术来估计架空聚合物绝缘体的污染水平。在聚合物绝缘体表面上沉积污染，是一种严重的问题，因为它通常导致闪络甚至绝缘体故障。为了估计污染水平的严重程度，通过双曲线窗口储存孔变换（HST）在时频域中分析了11kV聚合物绝缘体的表面漏电流（SLC）信号。 HST比古典股票交易更灵活。此外，HST能够充分处理低频和高频。考虑到优点，HST已经在此用于估计SLC签名的污染程度。 SLC信号的HST分析返回了2D复杂时频HS矩阵。复杂的时频HS矩阵已被分成幅度和相频谱。基于相位和幅度频谱，提取了15个统计特征，即HST特征。此后，通过最小绝对收缩和选择操作员（套索）特征选择技术选择了5个相关的HST特征。最后，这些相关的HST功能被馈送到四台机器学习分类器，以估计污染程度。还观察到，与其他标准时频分析和文献中的现有方法相比，所提出的框架方法提供了更好的分类准确性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号