[1]满蔚仕,张志禹,郗垒.基于快速S变换的电能质量主成分分析方法[J].控制与信息技术,2013,(06):29-35.[doi:10.13889/j.issn.2095-3631.2013.06.008]
 MAN Wei-shi,ZHANG Zhi-yu,XI Lei.An Analysis Method of Principal Components of Power Quality Based on Fast S-transform[J].High Power Converter Technology,2013,(06):29-35.[doi:10.13889/j.issn.2095-3631.2013.06.008]
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基于快速S变换的电能质量主成分分析方法()
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《控制与信息技术》[ISSN:2095-3631/CN:43-1486/U]

卷:
期数:
2013年06期
页码:
29-35
栏目:
“分布式发电、智能电网与电能质量”专刊
出版日期:
2013-12-31

文章信息/Info

Title:
An Analysis Method of Principal Components of Power Quality Based on Fast S-transform
文章编号:
2095-3631(2013)06-0029-07
作者:
满蔚仕张志禹郗垒
西安理工大学自动化学院
Author(s):
MAN Wei-shiZHANG Zhi-yuXI Lei
(School of Automation, Xi’an University of Technology, Xi’an, Shaanxi 710048, China)
关键词:
电能质量快速S 变换主成分分析识别实时性
Keywords:
power quality fast S-transform PCA classification real-time
分类号:
TM714
DOI:
10.13889/j.issn.2095-3631.2013.06.008
文献标志码:
A
摘要:
针对电能质量分析中S 变换计算量大,及支持向量机分类识别需要设定特征参数的问题,文章将一种新的S 变换的快速算法(FST)与主成分分析(PCA)相结合,并应用于电能质量分类识别。首先从FST 域提取几种电压扰动的模系数;进而利用P C A 进行降维处理并提取主要特征成分;然后获得投影矩阵;最后待识别电压信号投影后,根据最近邻分类器进行分类识别。仿真结果表明,电压扰动FST 域模系数的特征成分主要在低频段,因此识别结果准确率高、计算时间短,并且算法本身有一定的抗噪声能力,能较好地实时处理电能质量扰动。
Abstract:
To handle the problems in power quality analysis such as a large amount of calculation for S-transform, requiring setting feature parameters to the support vector machine classification, etc, it proposed a new approach which combined the fast S-transform (FST) algorithm with the principal component analysis (PCA) to classify the power quality disturbances. Firstly, the module coefficients of several voltage disturbances were extracted from FST domain. Then, PCA was applied to descend dimension and extract the main feature components and the projection matrix was obtained accordingly. Finally, the voltage signals were projected and classified by the nearest neighbor classifier. The simulation results show that the feature components of the FST module coefficients for voltage disturbances are focused on low-frequency band, so that the algorithm has the advantages of high accuracy, short runtime and somewhat anti-interference ability. Furthermore, It is a good choice to deal with PQDs via real-time identification.

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备注/Memo

备注/Memo:
收稿日期:2013- 08- 19
作者简介:满蔚仕(1969- ),男,博士,讲师,主要从事电能质量及信号分析领域的研究工作。
基金项目:陕西省教育厅科学研究计划项目(2013JK09 97)
更新日期/Last Update: 2016-05-10