说明：  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。
(An electric energy based on Mallat algorithm and fast Fourier transform is proposed. Quality analysis method. Wavelet de-noising is applied to sampled signals according to the signal burst. The first and second layers obtained by Mallat decomposition algorithm will be used for the detection results of change points. The layer high frequency coefficient is used as a criterion to distinguish the steady and unsteady disturbances, and then the disturbances are solved. The duration of movement. According to the principle of frequency band division of multi-resolution analysis, Mallat is adopted. The reconstructed algorithm extracts the transient disturbance waveform and compiles an accurate voltage discriminant. Recognition subroutine for short-term variation disturbances such as sudden drop, sudden rise and power outage)