M. R. Yusoff
Universiti Teknikal Malaysia Melaka

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

Voltage variations identification using gabor transform and rule-based classification method Weihown Tee; M. R. Yusoff; M. Faizal Yaakub; A. R. Abdullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1594.35 KB) | DOI: 10.11591/ijece.v10i1.pp681-689

Abstract

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.
A Critical Review of Time-frequency Distribution Analysis for Detection and Classification of Harmonic Signal in Power Distribution System M. H. Jopri; A. R. Abdullah; T. Sutikno; M. Manap; M. R. Ab Ghani; M. R. Yusoff
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1219.077 KB) | DOI: 10.11591/ijece.v8i6.pp4603-4618

Abstract

This paper presents a critical review of time-frequency distributions (TFDs) analysis for detection and classification of harmonic signal. 100 unique harmonic signals comprise of numerous characteristic are detected and classified by using spectrogram, Gabor transform and S-transform. The rulebased classifier and the threshold settings of the analysis are according to the IEEE Standard 1159 2009. The best TFD for harmonic signals detection and classification is selected through performance analysis with regards to the accuracy, computational complexity and memory size that been used during the analysis.
A verification of periodogram technique for harmonic source diagnostic analytic by using logistic regression M. Manap; M. H. Jopri; A. R. Abdullah; R. Karim; M. R. Yusoff; AH Azahar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.10390

Abstract

A harmonic source diagnostic analytic is vital to identify the root causes and type of harmonic source in power system. This paper introduces a verification of periodogram technique to diagnose harmonic sources by using logistic regression classifier. A periodogram gives a correct and accurate classification of harmonic signals. Signature recognition pattern is used to distinguish the harmonic sources accurately by obtaining the distribution of harmonic and interharmonic components and the harmonic contribution changes. This is achieved by using the significant signature recognition of harmonic producing load obtained from the harmonic contribution changes. To verify the performance of the propose method, a logistic regression classifier will analyse the result and give the accuracy and positive rate percentage of the propose method. The adequacy of the proposed methodology is tested and verified on distribution system for several rectifier and inverter-based loads.