基于压缩感知的电力信号压缩与重构研究

发布时间：2018-09-03 11:01

【摘要】：针对电力信号的采集和压缩问题,提出采用压缩感知理论对电力信号进行压缩采样和重构的方法,避免了传统的冗余采样。首先对采用压缩感知理论进行电能信号压缩采样的可行性进行了分析,并讨论了几种典型的压缩感知重构算法的具体实现方法和特性;然后采用这些算法,对一维稀疏信号和傅里叶变换基下稀疏的含有谐波和间谐波的电力信号进行重构实验。仿真结果表明,贪婪类压缩感知重构算法计算复杂度低、速度快,更适合一维电力信号的重构,其中SAMP算法可以在稀疏度未知的情况下,使用更少的采样值精确重构原始信号。
[Abstract]:Aiming at the problem of power signal acquisition and compression, a compression sensing theory is proposed to compress and reconstruct the power signal, which avoids the traditional redundant sampling. Firstly, the feasibility of compressed sensing theory for power signal compression sampling is analyzed, and the specific implementation methods and characteristics of several typical compression sensing reconstruction algorithms are discussed, and then these algorithms are adopted. In this paper, the sparse power signals with harmonics and interharmonics under one dimensional sparse signal and Fourier transform basis are reconstructed. The simulation results show that the greedy compression perceptual reconstruction algorithm has the advantages of low computational complexity and high speed, and it is more suitable for the reconstruction of one-dimensional power signals. The SAMP algorithm can accurately reconstruct the original signals with fewer sampling values when the sparsity is unknown.
【作者单位】：东北石油大学秦皇岛分校;燕山大学电气工程学院河北省测试计量技术及仪器重点实验室;
【基金】：秦皇岛市科技支撑计划项目(201302A042)
【分类号】：TM711;TN911.7

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