计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 564-568.

• 综合、交叉与应用 • 上一篇    下一篇

基于EEMD-RobustICA和Prony算法的谐波和间谐波检测方法

杜伟静, 赵峰, 高锋阳   

  1. 兰州交通大学自动化与电气工程学院 兰州730070
  • 出版日期:2019-02-26 发布日期:2019-02-26
  • 通讯作者: 赵 峰(1966-),男,硕士,教授,主要研究方向为铁道电气化与自动化、电能质量分析及控制,E-mail:198209868@qq.com
  • 作者简介:杜伟静(1992-),男,硕士生,主要研究方向为电能质量分析及控制,E-mail:823066763@qq.com;高锋阳(1970-),男,硕士,教授级高级工程师,主要研究方向为大功率电源。
  • 基金资助:
    本文受兰州市人才创新创业项目(2017-RC-95),光电技术与智能控制教育部重点实验室(兰州交通大学)开放课题(KFKT2016-6)资助。

Harmonic and Inter-harmonic Detection Method Based on EEMD-RobustICA and Prony Algorithm

DU Wei-jing, ZHAO Feng, GAO Feng-yang   

  1. College of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China
  • Online:2019-02-26 Published:2019-02-26

摘要: 针对经验模态分解存在的模态混叠现象和Prony算法对噪声敏感的问题,将总体经验模态分解与鲁棒性独立分析法和Prony算法进行有机的结合,应用到谐波和间谐波的检测中。首先将含有噪声的谐波信号进行总体经验模态分解,得到不同阶数的固有模态函数,然后将其作为鲁棒性独立分量分析法的输入,对得到的独立分量进行软阈值去噪后进行逆变换得到重构后的固有模态函数,叠加得到去噪后的信号,最后用Prony算法对谐波和间谐波信号进行参数辨识,得到谐波和间谐波的参数。仿真结果表明,该方法具有较好的抗噪性,克服了Prony算法对噪声敏感的缺点,有效地提高了谐波和间谐波检测的精度。

关键词: Prony算法, 鲁棒性独立分析法, 软阈值去噪, 谐波和间谐波, 总体经验模态分解

Abstract: For the modal aliasing existing in empirical mode decomposition and the noise-sensitive problem of Prony algorithm,a method with the combination of Prony based on Ensemble Empirical Mode Decomposition and Robust Independent Component Analysis was applied to the detection of harmonics and inter-harmonics.First of all,the noise containing harmonic signals was subjected to general empirical mode decomposition to obtain different orders of intrinsic mode functions.Then,it was used as the input of the robust independent component analysis method,and the achieved independent components would be processed by soft-threshold denoising method to attain reconstructed IMFs,which would be added up to acquire denoised signal to be identified with Prony algorithm to identify the parameters of the harmonic signal.The simulation results show that the method has a good antinoise and overcomes the disadvantages of Prony algorithm to noise sensitivity,which effectively improves the accuracy of harmonic and inter-harmonic detection.

Key words: General empirical mode decomposition, Harmonic and inter-harmonic, Prony algorithm, Robust independent analysis method, Soft threshold denoising

中图分类号: 

  • TM711
[1]高云辉,谢小英,牛益国,等.基于FFT的电力系统谐波检测方法综述[J].科技资讯,2017,15(5):49-53,55.
[2]HARRIS F J.On the use of windows for harmonic analysis with the discrete Fourier transform[J].Proceedings of the IEEE,1978,66(1):51-83.
[3]许丹,黄晓明,李献伟,等.基于小波变换的自适应电网谐波检测方法研究[J].电气技术,2017,18(8):37-42.
[4]刘于祥.一种基于准同步采样的电网谐波高精度测量方法[J].仪器仪表用户,2011,18(5):86-88.
[5]李明,王晓茹.一种用于电力系统间谐波谱估计的自回归模型算法[J].中国电机工程学报,2010,30(1):72-76.
[6]孙曙光,庞毅,刘建强.基于Hilbert频移的EEMD谐波检测方法[J].电力系统保护与控制,2017,45(15):85-91.
[7]赵磊.基于Prony的谐波间谐波检测方法和检测系统的研究与应用[D].徐州:中国矿业大学,2016.
[8]CARLSON R.Harmonic analysis for graph refinements and the continuous graph FFT[J].Linear Algebra & Its Applications,2009,430(11):2859-2876.
[9]HUANG N E.New method for nonlinear and nonstationary time series analysis:empirical mode decomposition and Hilbert spectral analysis [C]∥Proceedings of SPIE-The International Society for Optical Engineering.2000:197-209.
[10]AFRONI M J,SUTANTO D,STIRLING D.Analysis of nonstationary power-quality waveforms using iterative Hilbert Huang transform and SAX algorithm[J].IEEE Transactions on Power Delivery,2013,28(4):2134-2144.
[11]赵庆生,王宇,郭贺宏,等.扩展Prony算法在电力系统非整次谐波检测中的应用研究[J].电测与仪表,2016,53(7):57-60,73.
[12]FURUKAWA A,KIYONO J.Separation of harmonic excitation responses from contaminated measurements based on ICA[J].Engineering Structures,2007,29(4):591-608.
[13]吴微,彭华,张帆.FastICA和RobustICA算法在盲源分离中的性能分析[J].计算机应用研究,2014,31(1):95-98,119.
[14]黄丽亚,笪铖璐,杨晨,等.基于脑电EEG的改进EEMD算法[J].计算机科学,2017,44(5):66-70,80.
[15]朱莉,刘向丽.高频股指期现货市场波动跳跃及跳跃溢出检验——基于集合经验模式分解和小波降噪[J].系统科学与数学,2017,37(6):1509-1523.
[16]顾玲玲,刘国庆.一种参考独立成分分析算法在弱信号提取中的应用[J].计算机科学,2016,43(6):122-126.
[17]王继娟.基于FastICA与Prony算法的风电并网对电网低频振荡影响的研究[D].兰州:.兰州交通大学,2016.
[18]王纯子,王晶.基于CEEMDAN与小波软阈值的语音去噪算法研究[J].软件导刊,2017,16(2):67-70.
[19]吴微.含噪盲源分离算法研究及其在水声信号中的应用[D].郑州:解放军信息工程大学,2014.
[20]张文忠,周蓉,武旭红,等.利用白噪声分解特征的EEMD阈值降噪方法[J].测绘科学技术学报,2013,30(3):255-259.
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改进的脊波变换图像半软阈值降噪方法

计算机科学, 2009, 36(3): 241-243.
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