DocumentCode :
2157294
Title :
Feature vector extraction by using empirical mode decomposition from power quality disturbances
Author :
Yalcin, Tolga ; Ozgonenel, Okan
Author_Institution :
Electr. & Electron. Eng. Dept., Ondokuz Mayis Univ., Kurupelit - Samsun, Turkey
fYear :
2012
fDate :
18-20 April 2012
Firstpage :
1
Lastpage :
4
Abstract :
Power quality assumes that voltages/currents are in rated frequency and values from transmission to distribution and their shape is pure sinusoid and except these comments the distributed electrical energy is assumed as `not in good quality´. In this paper, the method known as empirical mode decomposition (EMD) will be used for extracting feature vectors from distorted power signal. The proposed method uses three phase normalized voltage/current signals but single phase analysis of voltage signals will be implemented in this work. Power disturbances such as voltage sag, swell, interrupt, flicker and DC component analysis are successfully decomposed to obtain feature vectors for any classification algorithm by using EMD.
Keywords :
feature extraction; power distribution; signal classification; signal detection; DC component analysis; EMD; classification algorithm; distorted power signal; distributed electrical energy; empirical mode decomposition; feature vector extraction; phase normalized current signals; phase normalized voltage signals; power distribution; power disturbances; power quality disturbances; power transmission; single phase analysis; voltage sag; Feature extraction; Monitoring; Power quality; Real time systems; Signal processing; Vectors; Voltage fluctuations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2012 20th
Conference_Location :
Mugla
Print_ISBN :
978-1-4673-0055-1
Electronic_ISBN :
978-1-4673-0054-4
Type :
conf
DOI :
10.1109/SIU.2012.6204434
Filename :
6204434
Link To Document :
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