基于STEKF和VMD-SVD的电能质量扰动信号去噪方法

A Denoising Method for Power Quality Disturbance Signals Based on STEKF and VMD-SVD

为有效去除电能质量扰动信号噪声,提出一种基于强跟踪扩展卡尔曼滤波(STEKF)、变分模态分解(VMD)和奇异值分解(SVD)的电能质量扰动信号去噪方法。首先通过STEKF判定扰动类型、定位扰动起止时刻,并对信号进行分段;然后采用VMD对每段信号进行初步去噪,同时分解出信号的暂态分量和稳态分量;再利用SVD对信号的稳态分量进行二次去噪并保留信号的暂态分量;最后对信号进行重构获得去噪后的信号。仿真结果表明,所提方法能有效抑制各类扰动信号的噪声,去噪后信噪比显著提高,均方根误差大幅降低,且去噪性能优于传统方法。

In order to reduce the noise of power quality disturbance signals,a denoising method for power quality disturbance signals based on strong tracking extended Kalman filter(STEKF),variational mode de⁃composition(VMD)and singular value decomposition(SVD)is proposed.Firstly,the disturbance type of sig⁃nal is judged,the beginning and the ending time of disturbance is indicated by STEKF,and then the signal is segmented.Secondly,VMD is used to denoise each segment of the signal preliminarily,and decompose the transient and steady-state component at the same time.Thirdly,the steady-state component is denoised for the second time by SVD and the actual value of the transient component is retained.Finally,the denoised sig⁃nal is obtained by reconstructing the signal.The simulation results demonstrate that the proposed method can effectively suppress the noise of all kinds of disturbance signals,significantly improve the signal-to-noise ra⁃tio,greatly reduce the error of mean square,and the denoising performance is better than the traditional meth⁃ods.