Open AccessVoltage variations identification using gabor transform and rule-based classification method
Author(s) -
Weihown Tee,
M.R. Yusoff,
Muhamad Faizal Yaakub,
Abdul Rahim Abdullah
Publication year - 2020
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v10i1.pp681-689
Subject(s) - voltage sag , matlab , voltage , pattern recognition (psychology) , computer science , gabor transform , artificial intelligence , s transform , time–frequency analysis , identification (biology) , power quality , root mean square , computer vision , engineering , botany , wavelet packet decomposition , wavelet transform , filter (signal processing) , biology , wavelet , electrical engineering , operating system
This paper presents a comparatively contemporary easy to use technique for the identification and classification of voltage variations. The technique was established based on the Gabor Transform and the rule-based classification method. The technique was tested by using mathematical model of Power Quality (PQ) disturbances based on the IEEE Std 519-2009. The PQ disturbances focused were the voltage variations, which included voltage sag, swell and interruption. A total of 80 signals were simulated from the mathematical model in MATLAB and used in this study. The signals were analyzed by using Gabor Transform and the signal pattern, time-frequency representation (TFR) and root-mean-square voltage graph were presented in this paper. The features of the analysis were extracted, and rules were implemented in rule-based classification to identify and classify the voltage variation accordingly. The results showed that this method is easy to be used and has good accuracy in classifying the voltage variation.