压缩传感在电能质量扰动信号分析中的应用

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。

Application of Power Quality Disturbance Signal Based on Compressed Sensing

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 detection 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.