Embedded Power Quality Monitoring System based on Independent Component Analysis and SVMs

被引:0
|
作者
Ruiz-Llata, Marta [1 ]
Guarnizo, Guillermo [1 ]
Boya, Carlos [1 ]
机构
[1] Univ Carlos III Madrid, Dept Elect Technol, Madrid 28911, Spain
关键词
SUPPORT VECTOR MACHINE; CLASSIFICATION; DISTURBANCES;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
On-line identification and classification of voltage and current disturbances in power systems are important tasks in the power quality monitoring and protection of power systems. Some power quality disturbances are non-stationary and transitory while other are steady-state variations that distort the voltage signal. One, two or more different power quality disturbances may appear at the same time. In this paper we propose a power quality monitoring system that employs Independent Component Analysis algorithm that is able to decouple multiple simultaneous power quality disturbances, and Support Vector Machines for identification the occurrence of a disturbance. We also show the first steps towards embedding the proposed system on an FPGA for online power quality monitoring.
引用
收藏
页码:2229 / 2234
页数:6
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