基于Mallat算法和快速傅里叶变换的电能质量分析方法

提出了一种基于Mallat算法和快速傅里叶变换的电能质量分析方法。将小波消噪应用于采样信号，根据信号的突变点检测结果，将采用Mallat分解算法得到的第一层和第二层高频系数作为区分稳态和非稳态扰动的判据，进而求出扰动的持续时间。根据多分辨分析的频带划分原理，采用Mallat重构算法提取出了暂态扰动波形，并编制了可准确判别电压骤降、骤升和断电等短期变化扰动的识别子程序。对于稳态扰动，提出可将快速傅里叶变换作为区分谐波和闪变的一种手段。Matlab的仿真结果验证了该方法的准确性和有效性。

A Power Quality Analysis Method Based on Mallat Algorithm and Fast Fourier Transform

Based on Mallat algorithm and fast Fourier transform (FFT), the authors propose a power quality analysis method. In this method, the wavelet denoising is applied to sampled signals; according to the detection results of catastrophe point of signals, the high frequency coefficients of the first level and the second level obtained by Mallat decomposition algorithm are taken as the criteria to distinguish steady state disturbance from non-steady state disturbance, and then the duration of disturbance can be solved. In the light of frequency band division principle of multi-resolution analysis, by use of Mallat reconstruction algorithm the transient disturbance waveform is extracted, moreover an identification subroutine that can accurately distinguish short-term variation disturbances such as voltage sag, voltage swell and interruption is programmed. For steady state disturbance, the authors point out that FFT can be used as a tool to distinguish harmonics from flicker. The effectiveness and accuracy of the proposed method is validated by Matlab-based simulation results.