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Intelligent Methods for Characterization of Electrical Power Quality Signals using Higher Order Statistical Features

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Author
Palomares-Salas, José Carlos
González de la Rosa, Juan José
Agüera Pérez, Agustín
Moreno-Muñoz, A.
Publisher
SIGMA NOT
Date
2012
Subject
Higher-Order Statistics (HOS)
Artificial Neural Networks (ANN)
Power-Quality (PQ)
Self Organizing Maps (SOM)
Transients
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Abstract
This paper considers a few important techniques classification for to identify several power quality disturbances. For this purpose, a process based in HOS has been realized to extract features that help in classification. In this stage the geometrical pattern established via higher-order statistical measurements is obtained, and this pattern is function of the amplitudes and frequencies of the power quality disturbances associated to the 50-Hz power-line. Once the features are managed will be segmented to form training and test sets and them will be applied in the statistical methods used to perform automatic classification of PQ disturbances. The best technique of those compared is selected according to correlation and mistake rates.
URI
http://hdl.handle.net/10396/15647
Fuente
Przegląd Elektrotechniczny 8, 236-243 (2012)
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