本文提出了一种自动检测和电能质量扰动分类模糊专家系统。有关干扰的类型包括电压骤降，骤升，中断，切换瞬变，冲动，闪烁，谐波和缺口。据推测，在所分析的波形采样的形式提供。傅立叶变换和小波分析，利用独特的功能获得的波形一个模糊专家系统为主体的决定有关的干扰类型而设计的。仿真研究，验证了该方法的比较研究人工神经网络为基础的分类方法和该方法研究的准确性也报告，以显示该方法的优点-This paper presents a fuzzy-expert system for automated detection and classification of power quality disturbances. The types of concerned disturbances include voltage sags, swells, interruptions, switching transients, impulses, flickers, harmonics, and notches. It is assumed that the analyzed waveforms are available in sampled form. Fourier transform and wavelet analysis are utilized to obtain unique features for the waveforms A fuzzy-expert system is designed for making a decision regarding the type of the disturbance. Simulation studies are presented to verify the accuracy of the proposed approach Comparison studies between an Artificial Neural Network based classification technique and the proposed approach are also reported to show the advantages of the proposed approach.