期刊文献+

基于EEMD阈值的绝缘子泄漏电流去噪的研究 被引量:8

Research on De-nosing of Insulator Leakage Current Based on EEMD Threshold
原文传递
导出
摘要 绝缘子泄漏电流信号的采集受很多噪声信号的干扰,直接使用将影响准确地提取其特征量,本文对基于EEMD(Ensemble Empirical Mode Decomposition)阈值的绝缘子泄露电流去噪方法进行研究,借鉴小波去噪的4种阈值方法对泄漏电流信号进行去噪,分别是自适应阈值、固定阈值、启发式阈值和极大极小阈值,对EEMD阈值的去噪方法进行研究,通过对去噪前后信号的波形、有效值和谐波幅值比这3个特征量进行分析比较,综合比较仿真和实测信号去噪前后的效果,得出固定阈值是EEMD去噪方法的最佳阈值。 There is a large amount of noise in the process of measuring insulator leakage current, so it is a difficult task to pick up useful information if we use the signal directly. In this paper, we use four threshold, namely, the self-adaptive threshold, the fixed threshold, the heuristic threshold and the minimax threshold to filter the noises from measured leakage current with different signal-to-noise ratio (SNR) based on the research of the EEMD (Ensemble Empirical Mode Decomposition) de-noising method. Through the analysis and comparison of three characteristics of the signal pre-and-post de- noised, including waveforms, RMS and harmonic amplitude value ratio leakage, and the effect of simulation and actual measurement for signal pre-and-post de-noised. It is obtained that fixed threshold is the best threshold for EEMD De-nosing Method.
出处 《电瓷避雷器》 CAS 北大核心 2012年第4期28-32,共5页 Insulators and Surge Arresters
关键词 绝缘子泄漏电流 信号去噪 阈值 经验模态分解 insulator leakage current signal de-noising threshold EEMD
  • 相关文献

参考文献14

  • 1李璟延,司马文霞,姚陈果,孙才新.染污绝缘子安全区泄漏电流检测中去除信号干扰方法[J].电力系统自动化,2008,32(5):85-89. 被引量:19
  • 2赵汉表,林辉,廖胜蓝,谢利理.小波变换在绝缘子泄漏电流检测中的应用[J].高电压技术,2005,31(4):34-36. 被引量:20
  • 3HUANG Norden E,ZHANG Shen,LONG Steven R. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J]. The Royal Society, 1998,454 : 903-995.
  • 4孙金宝,朱永利,刘丽轻,黄建才.基于EMD的绝缘子泄漏电流去除噪声研究[J].华北电力大学学报(自然科学版),2010,37(6):1-5. 被引量:19
  • 5WU Z, HUANG N E. Ensemble empirical mode decompo- sition:A noise-assisted data analysis method [J]. Advances in Adaptive Data Analysis, 2009,1 ( 1 ) : 1-41.
  • 6Patrick Flandrin,Gabriel Rilling,Paulo Goncalvrs. Empri- eal mode decomposition as a filter bank [J]. IEEE Signal Process Letters, 2004,11 (2) : 112-114.
  • 7Yannis Kopsinis, Stephen McLaughin. Development of EMD-based denoising methods inspired by wavelet thresh- olding [J]. IEEE Transactions on Signal Processing, 2009,57 (4) : 1351-1362.
  • 8Khaldi K, Boudraa,A-O.,et al. Speech signal noise reduc- tion by EMD[J]. ISCCSP International Symposium on Com- munications, Control and Signal Processing, 2008,12 (14): 1155-1158.
  • 9George Tsolis, Thomas D.Xenos. Signal Denoising Using Empirical Mode Decomposition and Higher Order Statistics [J]. International Journal of Signal Processing, Image Pro- cessing and Pattern Recognition,2011,4(2):91-106.
  • 10TRNKA P, HOFREITER M. The Empirical Mode Decom- position in Real-Time[J]. Proceedings of the 18th Interna- tional Conference on Process Control,2011,14(17): 284-289.

二级参考文献58

共引文献92

同被引文献101

引证文献8

二级引证文献40

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部