基于小波变换的电能质量监测

针对噪声系数的幅度随着尺度增加而减小的特点,提出了一种改进的基于小波分解层数的波段自适应降噪算法.利用Matlab仿真软件建立了电压暂降的系统模型,运用小波分析的方法对污染白噪声的电压暂降信号进行了时频分析和降噪处理,分析了软硬阈值降噪方法.实验结果表明,该方法通过调整两个可调参数获得较优的小波系数阈值估计,与常见的三种典型算法相比不仅较好地去除了噪声干扰,且信噪比更高,均方误差更小,同时具有更优的信息保全能力.

Power quality monitoring based on wavelet transformation

Aiming at the feature that the amplitude of noise coefficient reduces with increasing the scope, an improved sub band adaptive denoising algorithm based on the wavelet decomposition layers was proposed. The system model for voltage sag was established with the Matlab simulation software. The time frequency analysis and denoising treatment of voltage sag signals contaminated by white noise were performed with the wavelet analysis method, and the soft and hard threshold denoising methods were analyzed. The experimental results show that the superior threshold estimation of wavelet coefficients can be obtained through adjusting two adjustable parameters. Compared with three common typical algorithms, the proposed method can not only eliminate the noise interference better, but also have higher signal to noise ratio （SNR）, smaller mean square error （MSE） and more excellent information keeping ability.