基于信号相关性和小波方法的电能质量去噪算法

A Power Quality Signals De-Noising Algorithm Based on Signals' Multi-Scales Correlation and the Wavelet Transform Theory

提出了一种基于小波原理的电能质量信号去噪算法。基于软阈值原理的小波去噪算法在电能质量信号检测中得到很好的应用。但其存在阈值计算受噪声强度的缺点 ,当信号被强噪声“淹没”时 ,该方法仍然会失效。本文在对电力信号进行小波空间中的自相关性关系分析的基础上 ,结合软阈值算法和小波原理 ,构造了能有效地处理各种电能质量信号的去噪算法 ,该算法能弥补传统软阈值算法的缺陷 ,较好地解决了保护信号局部特征与抑制噪声之间的矛盾。计算结果表明上述检测算法是有效的。

A new de-noising algorithm is proposed in this paper.The soft-threshold theory has been used to de-noising the power quality(PQ)signals as well as the wavelet transform technique has been proposed for detecting and analyzing PQ signals.But when the noise is so strong that the PQ signal is submerged in noises,this two algorithm would be abated,or even lead to a wrong judgement.Based on the wavelet coefficients correlation in wavelet multi-scale spaces,a new algorithm combined with the soft-threshold and wavelet transform theory was proposed.It can deal with PQ signals under strong noise environment.And this method can settle the conflict between the signals local characteristic protection and noises restriction commendably.Finally,the validity of the proposed method is verified by the results of the calculation.