基于奇异值分解的电能质量信号去噪

Power quality signals' de-noising method based on singular value decomposition (SVD)

提出了一种基于奇异值分解的电能质量扰动信号去噪算法。算法重构采集信号时间序列的吸引子轨迹矩阵,根据轨迹矩阵奇异值的加权能量贡献率(PCTE)选择奇异值进行扰动信号重建,重建信号即为去除噪声后的电能质量扰动信号。仿真试验结果表明奇异值分解能够有效地提高扰动信号的信噪比,保持原始电能质量信号的扰动特征,此算法理论基础完善,易于实现,有良好的发展前景。

A power quality signals＇ de-noising method based on singular value decomposition （SVD） is proposed in this paper. A track matrix of attractor is reconstructed based on time series, then according to the singular values＇ percent of contribution to total energy （PCTE） , disturbance signal is reconstructed, which is the de-noised power quality signal. Simulation results indicate that SVD can improve SNR and keep original disturbances＇ characters. The proposed algorithm＇s theory foundation is consummate and is easy to be carried out, so it has nice developmental foreground.