一种改进EMD-SVD算法的暂态电能质量扰动信号消噪研究

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.

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

An Improved SVD de-noising method combined with 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, using left and right singular vectors to determine the singular matrix, and then uses an improved singular value difference method 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 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 2.9db and 7.3db respectively, the validity of this algorithm is verified.