基于变分模态分解和希尔伯特变换的直流纹波检测

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Abstract It is important to accurately detect the ripple component of DC signal to evaluate the quality of DC power supply. In this paper, a combined algorithm based on the variational mode decomposition (VMD) and Hilbert transform (HT) is proposed to detect and analyze the characteristics of the ripple components of DC signals. Firstly, the optimal modal number of VMD algorithm is determined by means of permutation entropy mean method. By using VMD algorithm, DC signal can be accurately decomposed into a series of AM-FM functions. Then, the HT algorithm is applied to each AM-FM function to obtain the corresponding instantaneous amplitude and frequency, and determine the characteristics of DC signal. Finally, the feasibility and effectiveness of the proposed combined vmd-ht algorithm are verified by simulation and experiment. Compared with ensemble empirical modes decomposition (EEMD)-HT algorithm, VMD-HT algorithm has higher decomposition accuracy and more robust to noise for complicated signal. Moreover, VMD-HT algorithm has non-sensitive to sampling frequency. The proposed algorithm can be applied to DC ripple detection.

Key words： variational mode decomposition (VMD) permutation entropy Hilbert transform (HT) instantaneous amplitude

Received: 09 March 2020

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	Articles by authors
	Qu Longteng
	Li Peixing
	Qiao Zhuangzhuang

Cite this article:

Qu Longteng,Li Peixing,Qiao Zhuangzhuang. DC ripple detection based on variational mode decomposition and Hilbert transform[J]. Electrical Engineering, 2020, 21(8): 66-72.

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http://dqjs.cesmedia.cn/EN/Y2020/V21/I8/66

[1] 周逢权, 黄伟. 直流配电网系统关键技术探讨[J]. 电力系统保护与控制, 2014, 42(22): 62-67.
[2] 胡晓曦, 刘含露, 熊婷婷, 等. 基于希尔伯特-黄变换的复杂电能质量信号检测技术[J]. 电气技术, 2012, 13(5): 6-10.
[3] 熊卫华, 赵光宙. 基于希尔伯特-黄变换的变压器铁心振动特性分析[J]. 电工技术学报, 2006, 21(8): 9-13.
[4] 梅永, 王柏林. 降阶快速傅里叶变换算法在电力系统谐波分析中的应用[J]. 电网技术, 2010, 324(11): 117-120.
[5] 曹玲芝, 刘俊飞, 郑晓婉. 基于EEMD的HHT在电能质量多扰动分类识别中的应用[J]. 电气技术, 2017, 18(4): 66-70.
[6] 黄传金, 周铜. 基于变分模态分解的电能质量扰动检测新方法[J]. 电力自动化设备, 2018, 38(3): 116-123.
[7] 朱永利, 贾亚飞, 王刘旺, 等. 基于改进变分模态分解和Hilbert变换的变压器局部放电信号特征提取及分类[J]. 电工技术学报, 2017, 32(9): 221-235.
[8] 刘长良, 武英杰, 甄成刚. 基于变分模态分解和模糊C均值聚类的滚动轴承故障诊断[J]. 中国电机工程学报, 2015, 35(13): 3358-3365.
[9] He Wen, Zhang Junhao, Zhuo Meng, et al.Harmonic estimation using symmetrical interpolation FFT based on triangular self-convolution window[J]. IEEE Transa- ctions on Industrial Informatics, 2015, 11(1): 16-26.
[10] 李天云, 赵妍, 韩永强, 等. Hilbert-Huang变换方法在谐波和电压闪变检测中的应用[J]. 电网技术, 2005(2): 73-77.
[11] 戴婷, 张榆锋, 章克信, 等. 经验模态分解及其模态混叠消除的研究进展[J]. 电子技术应用, 2019, 45(3): 7-12.
[12] Dragomiretskiy K, Zosso D.Variational mode decom- position[J]. IEEE Transactions on Signal Processing. 2014, 62(3): 531-544.
[13] 朱静. 浅谈直流电源纹波测量方法[J]. 民营科技, 2018, 217(4): 126-127.
[14] Mariscotti A.Methods for ripple index evaluation in DC low voltage distribution networks[C]//In Pro- ceedings of the IEEE Instrumentation & Measure- ment Technology Conference, Warshaw, Poland, 2007(1-3): 1-4.
[15] 何军娜. 基于小波及排列熵奇异性检测的行波故障测距研究[D]. 南昌: 华东交通大学, 2015.