Classification of Power Quality Disturbances by Using DOS-Transform and Support Vector Machines

被引：0

作者：

Kaewarsa, Suriya ^{[1
]}

Attakitmongcol, Kitti ^{[2
]}

机构：

[1] Rajamangala Univ Technol Isan, Sch Elect Engn, Fac Ind & Technol, Sakon Nakhon, Thailand

[2] Suranaree Univ Technol, Sch Elect Engn, Inst Engn, Nakhon Ratchasima, Thailand

来源：

INTERNATIONAL REVIEW OF ELECTRICAL ENGINEERING-IREE | 2010年 / 5卷 / 05期

关键词：

Power Quality; Discrete Orthogonal S-Transform; Support Vector Machines; Wavelet Transform; Neural Network; S-TRANSFORM; NETWORKS; RECOGNITION; SPECTRUM;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a new method based on discrete orthogonal S-transform and support vector machines for classification of power quality disturbances. DOS-transform is mainly used to extract features of power quality disturbances and support vector machines are mainly used to construct a multiclass classifier which can classify power quality disturbances according to the extracted features. Results of simulation and analysis demonstrate that the proposed method can achieve higher correct identification rate, better convergence property and less training time compared with the method based on neural network Copyright (C) 2010 Praise Worthy Prize S.r.l. - All rights reserved.

引用

页码：2177 / 2185

页数：9

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