基于SVD-ILMD的暂态电能质量扰动定位检测方法

A location and detection method for transient power quality disturbance using SVD-ILMD

为实现对电网非平稳扰动信号的快速、准确分析,提出了融合SVD(奇异值分解)与ILMD(优化局部均值分解)的暂态电能质量扰动定位检测方法。首先,通过ILMD与模糊隶属度函数阈值处理噪声信息,削弱噪声干扰;然后,构造差值信号并利用滑窗SVD增强扰动特征,进一步抑制噪声干扰;最后,基于特征增强信号提出一种自适应阈值截断的暂态电能质量扰动定位检测方法。经仿真分析与算法对比,验证了所提方法定位准确、抗噪性强、计算量小,对过零与微弱扰动也有较好的定位效果。

Swiftly and accurately analyze non-stationary disturbance signals within the power grid,a location and de⁃tection method for transient power quality disturbance that combines singular value decomposition(SVD)and im⁃proved local mean decomposition(ILMD)is proposed.First,noise information is processed by using ILMD and a fuzzy membership function threshold to mitigate noise interference.Then,a difference signal is formulated,and a sliding window SVD is employed to amplify the disturbance features while further suppressing noise interference.In conclusion,an adaptive threshold truncation-based approach for localizing and detecting transient power quality dis⁃turbances is proposed,utilizing the feature-enhanced signal.Simulation analysis and algorithm comparisons confirm that the proposed method exhibits precise location,robust resistance to noise,and low computational complexity.