吉林大学学报(信息科学版) ›› 2014, Vol. 32 ›› Issue (6): 618-623.

• 论文 • 上一篇    下一篇

压缩传感在电能质量扰动信号分析中的应用

于华楠1, 张敬傑2, 代芳琳1   

  1. 1. 东北电力大学 信息工程学院, 吉林 吉林 132012; 2. 吉林大学 物理学院, 长春 130012
  • 收稿日期:2014-10-22 出版日期:2014-11-25 发布日期:2015-01-09
  • 作者简介:于华楠(1981—), 女, 吉林省吉林市人, 东北电力大学副教授, 博士, 主要从事压缩传感理论、 水声通信和无线通信信道估计研究, (Tel)86-13704410175(E-mail)yhn810117@163.com。
  • 基金资助:

    国家自然科学基金资助项目(551307020)

Application of Power Quality Disturbance Signal Based on Compressed Sensing

YU Huanan1, ZHANG Jingjie2, DAI Fanglin1   

  1. 1. College of Information Engineering, Northeast Dianli University, Jilin 132012, China;2. College of Physics, Jilin University, Changchun 130012, China
  • Received:2014-10-22 Online:2014-11-25 Published:2015-01-09

摘要:

针对电能质量扰动信号分析中, 传统信号处理方法存在采样数据量极大、 采样时间长、 压缩时浪费采样资源等问题, 将压缩传感(CS: Compressed Sensing)应用于电能质量扰动信号分析中。实现了采样与压缩同时完成, 极大地降低了采集的数据量和采样速率。通过对压缩传感的过完备字典设计, 实现了压缩传感同时检测多个电能质量扰动信号, 以及压缩传感对信号在一维、 二维上的重构, 并对重构的电能质量扰动信号进行分析。实验结果表明, 与传统的电能质量扰动信号处理方法相比, 该算法在采样数据量、 重构效果方面都有很大提升, 得到的重构信号误差更小, 对信号的分析更准确。

关键词: 压缩传感, 电能质量, 扰动信号, 字典, 分析

Abstract:

In power quality disturbance signal analysis, traditional signal processing methods are based on Nyquist sampling theorem. Sampling of huge amount data and sampling time are long, wasting sampling resources. The CS(Compressed Sensing) is put foruard in the application of the power quality disturbance signal analysis. Compressed sensing algorithm is not based on the Nyquist sampling theorem. Sampling and compression are made at the same time reduceing the amount of data collected and sampling rate. Based on compressed sensing a complete dictionary design, realized the compressed sensing d
etection of multiple power quality disturbance signals at the same time, also has realized the compressed sensing signal on the one dimensional and two dimensional reconstruction. And the reconstruction of power quality disturbance signal analysis. Experimental results show that compared with the traditional signal processing method of power quality disturbance, the effect of the algorithm in the amount of sampling data, refactoring has improved, the reconstructed signal error smaller and more accurate analysis of the signal.

Key words: compressed sensing(CS), power quality, disturbance signal, dictionary, analysis

中图分类号: 

  • TM933