一种改进EMD-SVD算法的暂态电能质量扰动信号消噪研究  

Research on de-noising of transient power quality disturbance signal based on the improved EMD-SVD algorithm

作　　者：布左拉·达吾提 帕孜来·马合木提[1] 董永昌 葛震君 Buzuola Dawuti;Pazilai Mahemuti;Dong Yongchang;Ge Zhenjun(School of Electrical Engineering,Xinjiang University,Urumqi 830047,China)

机构地区：[1]新疆大学电气工程学院,乌鲁木齐830047

出　　处：《电测与仪表》2021年第12期69-75,共7页Electrical Measurement & Instrumentation

基　　金：国家自然科学基金资助项目(61364010);新疆维吾尔自治区自然科学基金资助项目(2016D01C038)。

摘　　要：针对小波变换在暂态电能质量消噪方面对高频有用信号误滤除,造成消噪后信号失真严重,或毛刺过多现象,提出一种结合经验模态分解(EMD)的改进奇异值分解(SVD)降噪方法,该方法采用EMD将噪声信号进行初步滤除,通过构造Hankel矩阵,利用左右奇异向量确定奇异矩阵,根据奇异值的分布规律,提出一种改进的奇异值差分方法来确定有效奇异矩阵阶次,从而完成消噪后信号的重构。结果显示该方法去噪效果较好,特别对电压暂降和电压中断的效果最为明显,其信噪比分别提高了2.9 dB和7.3 dB以上,验证了所述方法的有效性。An improved singular value decomposition(SVD)de-noising method combined with empirical mode decomposition(EMD)is proposed to deal with the bad phenomena of wavelet transform in transient power quality de-noising,wavelet transform can filter out the high frequency useful signal by mistake,and resulting in serious signal distortion or excessive burr after noise elimination.In this method,the noise signal is firstly filtered by EMD,and then,by constructing a Hankel matrix,the left and right singular vectors are used to determine the singular matrix,and then,an improved singular value difference method is used to determine the rank of the effective singular matrix according to the rules of singular value distribution,thus,the signal reconstruction after de-noising is completed.The results show that this proposed method is effective in de-noising,in particular,the effect of voltage sag and voltage interruption is the most obvious.Its signal-to-noise ratio is more than 2.9 dB and 7.3 dB respectively,the validity of this algorithm is verified.

关 键 词：暂态电能质量 经验模态分解 奇异值分解 奇异值差分 

分 类 号：TM93[电气工程—电力电子与电力传动]