【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。更多还原

【Abstract】 A method for compressive sampling and reconstruction of power signal based on compressed sensing theory is proposed to solve the problem of acquisition and compression of the electrical signal,and thus avoiding the redundancy sampling. Firstly,the implementation steps and the characteristic of the compressed sensing reconstruction algorithm such as IRLS,OMP,SP and SAMP are analyzed. Secondly,one-dimensional sparse signal and the power signal containing harmonics and inter-harmonics components,which are sparse under the Fourier transform are reconstructed under the four algorithms. The simulation results show that the greedy algorithm is more suitable for the electrical signal reconstruction due to its fast speed and low computational complexity. Compared with other greedy algorithms,the SAMP algorithm can reconstruct the original electrical signal with fewer sampling in the situation of unknown sparsity.更多还原