Interharmonic detection based on support vector machine

被引：0

作者：

Zhou Li ^{[1
]}

Liu Kaipei ^{[1
]}

Ma Bingwei ^{[1
]}

Tao Qian ^{[1
]}

机构：

[1] Wuhan Univ, Sch Elect Engn, Wuhan 430072, Peoples R China

来源：

ICIEA 2006: 1ST IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-3, PROCEEDINGS | 2006年

关键词：

support vector machine; interharmonic; LabVIEW;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Support vector machine (SVM) based on the principle of structure risk minimization provides A new perspective in machine learning, and has been successfully applied to many areas in the last years, especially for pattern recognition and function fitting. In this paper, because of the adjustable resolution of the SVM algorithm, a new way to measure interharmonic is put forward, namely using wide analytical domain of frequency with low resolution at first and then using narrow analytical domain of frequency with high resolution to obtain the frequency spectrum of the signal. And based on this new method, the interharmonic detection system is designed and implemented with the prevailing and powerful software platform of LabVIEW with graphical nature.

引用

页码：1047 / 1050

页数：4

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