Fault classification in power systems using EMD and SVM

被引：81

作者：

Babu, N. Ramesh ^{[1
]}

Mohan, B. Jagan ^{[1
]}

机构：

[1] VIT Univ, Sch Elect Engn, Vellore, Tamil Nadu, India

来源：

AIN SHAMS ENGINEERING JOURNAL | 2017年 / 8卷 / 02期

关键词：

Fault classification; Empirical Mode Decomposition (EMD); Support Vector Machines (SVMs); EMPIRICAL-MODE DECOMPOSITION;

D O I：

10.1016/j.asej.2015.08.005

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In recent years, power quality has become the main concern in power system engineering. Classification of power system faults is the first stage for improving power quality and ensuring the system protection. For this purpose a robust classifier is necessary. In this paper, classification of power system faults using Empirical Mode Decomposition (EMD) and Support Vector Machines (SVMs) is proposed. EMD is used for decomposing voltages of transmission line into Intrinsic Mode Functions (IMFs). Hilbert Huang Transform (HHT) is used for extracting characteristic features from IMFs. A multiple SVM model is introduced for classifying the fault condition among ten power system faults. Algorithm is validated using MATLAB/SIMULINK environment. Results demonstrate that the combination of EMD and SVM can be an efficient classifier with acceptable levels of accuracy. (C) 2015 Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.

引用

页码：103 / 111

页数：9

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