电能质量扰动分类的改进std_MRA曲线分类法  

Improved Std_MRA Curve Fitting Method for Classifying Power Quality Disturbance

作　　者：仰彩霞[1] 刘开培[1] 余瑜[2] 苏毅[1] 

机构地区：[1]武汉大学电气工程学院,武汉430072 [2]湖北工业大学电气与电子工程学院,武汉430068

出　　处：《高电压技术》2009年第6期1472-1475,共4页High Voltage Engineering

基　　金：国家自然科学基金(50677048)~~

摘　　要：为了对电能质量进行有效治理,以提高用电效率,有必要对电能质量进行快速检测和准确分类。首先介绍std_MRA曲线分类法,提出多分辨率信号分解技术,该技术在分析暂态信号时非常有效,不仅能对电能质量扰动进行分类,而且能分辨相似干扰。在std_MRA曲线分类法的基础上提出改进的std_MRA曲线分类法—利用多分辨率信号分解技术对信号进行分解,绘出改进的std_MRA曲线对扰动信号进行分类。Matlab仿真表明,该方法不仅能对常见扰动进行准确分类,而且运算量小。To improve the power efficiency , it is necessary to detect the power quality signals sensitively , classify them accurately and clarify them effectively. We introduced the std_MRA curve classification fitting method, and presented a multiresolution signal decomposition technique as an efficient method in analyzing transient events. The multiresolution signal decomposition has the ability to classify different power quality disturbance and furthermore distinguish similar disturbance. Moreover,we put forward an improved std MRA curve classification fitting method--using tlie multiresolution signal decomposition technique to decompose the transient events and portraying the improved std_MRA curve for classifying. The Matlab simulation demonstrates that this method can not only classify the usual power quality events, but also has less computation than the std_MRA curve classification fitting method.

关 键 词：暂态信号 扰动分类 电能质量 小波变换 信号分解 std—MRA曲线 

分 类 号：TM711[电气工程—电力系统及自动化]