一种基于小波变换的电能质量特征量提取及分类的方法  

An approach to the extraction and classification of feature vector for power quality based on wavelet

作　　者：吴晓朝[1] 方立新 郭红霞[2] 

机构地区：[1]63880部队 [2]华南理工大学电力学院

出　　处：《控制理论与应用》2008年第2期325-328,共4页Control Theory & Applications

基　　金：国家自然科学基金重点资助项目(60534040);广东省自然科学基金资助项目(020906)

摘　　要：提出了一种利用小波变换实现动态电能质量特征量扰动(电压上升、电压凹陷、电压中断、电压瞬变和电压缺口等)的提取以及分类方法.利用小波变换的奇异性检测原理提取动态电能质量信号中的突变,并进行定位,确定信号变化的时间,并用电压均值法确定扰动的类别,并通过仿真表明方法的有效性.最后讨论了本方法在DSP上的实现.An approach to the extraction and classification of feature vector for power quality based on wavelet is proposed in this paper. The disturbances include the voltage swells, sags, interruptions, transients and notchs. With the singularity principle of wavelet transform, the abrupt changes in the signal of the dynamic power quality are extracted and located, and the time during signal variation is then defined. Thus, the disturbances can be classified by the voltage averaging method. The results of MATLAB simulation show its validity. Finally, the proposed method is realized on a digital signal processor（DSP）.

关 键 词：小波变换 电能质量 扰动识别与分类 

分 类 号：TM933.4[电气工程—电力电子与电力传动]