|3/2017 - 8|
Research and Implementation of a USB Interfaced Real-Time Power Quality Disturbance Classification SystemGOK, M. , SEFA, I.
|View the paper record and citations in|
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (1,660 KB) | Citation | Downloads: 572 | Views: 1,290|
discrete transforms, graphical user interfaces, neural networks, power quality, real-time system
power(46), quality(29), transform(19), system(17), classification(17), disturbances(16), systems(10), detection(10), time(9), real(8)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2017-08-31
Volume 17, Issue 3, Year 2017, On page(s): 61 - 70
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.03008
Web of Science Accession Number: 000410369500008
SCOPUS ID: 85028532369
In this study, the research and implementation of an automatic power quality (PQ) recognition system are presented. This system contains a USB interfaced multichannel data acquisition (DAQ) device and a graphical user interfaced (GUI) application. The DAQ device consists of an analog-to-digital (ADC) converter, field programmable gate array (FPGA) and a USB first in first out (FIFO) buffer interface chip. The application employs Stockwell Transform (ST) technique combined with neural network model to build the classifier. Eight basic and two combined PQ disturbances are determined for the classification. Different from the previous studies, the synthetic signals used for neural network training are modified by adding the harmonics detected in the real signal. This approach is used to increase the classifier accuracy against the real line power signal. Also, ST is simplified by using only the frequencies which are required in the feature extraction step to reduce the processing time. Developed application handles the signal processing, the classification, and the database recording tasks by using multi-threaded programming approach under the mean time of 41 ms. The experimental results show that the proposed power quality disturbance detection system is capable of recognizing and reporting power quality faults effectively within the real-time requirements.
Web of Science® Times Cited: 9 [View]
View record in Web of Science® [View]
View Related Records® [View]
SCOPUS® Times Cited: 9
View record in SCOPUS® [Free preview]
View citations in SCOPUS® [Free preview]
 Dual Tree Complex Wavelet Transform with Multiobjective Optimization Algorithm for Real‐Time Power Quality Events Classification, Rahul,, Advanced Theory and Simulations, ISSN 2513-0390, Issue 10, Volume 3, 2020.
Digital Object Identifier: 10.1002/adts.202000141 [CrossRef]
 Real-Time Implementation of Optimized Power Quality Events Classifier, Markovska, Marija, Taskovski, Dimitar, Kokolanski, Zivko, Dimchev, Vladimir, Velkovski, Bodan, IEEE Transactions on Industry Applications, ISSN 0093-9994, 2020.
Digital Object Identifier: 10.1109/TIA.2020.2991950 [CrossRef]
 Review of Signal Processing Techniques and Machine Learning Algorithms for Power Quality Analysis, Rahul,, Advanced Theory and Simulations, ISSN 2513-0390, Issue 10, Volume 3, 2020.
Digital Object Identifier: 10.1002/adts.202000118 [CrossRef]
 An Advanced Genetic Algorithm with Improved Support Vector Machine for Multi-Class Classification of Real Power Quality Events, Rahul, , Choudhary, Bharat, Electric Power Systems Research, ISSN 0378-7796, Issue , 2021.
Digital Object Identifier: 10.1016/j.epsr.2020.106879 [CrossRef]
 A Novel Approach to Power Quality Analysis: Adaptive FEM Algorithm with Sparse Signal Decomposition, Rahul,, Advanced Theory and Simulations, ISSN 2513-0390, Issue 9, Volume 3, 2020.
Digital Object Identifier: 10.1002/adts.202000095 [CrossRef]
 An Efficient and High-Speed Disturbance Detection Algorithm Design with Emphasis on Operation of Static Transfer Switch, USMAN, A., CHOUDHRY, M. A., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 21, 2021.
Digital Object Identifier: 10.4316/AECE.2021.02010 [CrossRef] [Full text]
 Three-Layer Bayesian Network for Classification of Complex Power Quality Disturbances, Luo, Yi, Li, Kaicheng, Li, Yuanzheng, Cai, Delong, Zhao, Chen, Meng, Qingxu, IEEE Transactions on Industrial Informatics, ISSN 1551-3203, Issue 9, Volume 14, 2018.
Digital Object Identifier: 10.1109/TII.2017.2785321 [CrossRef]
 Controllable AC/DC Integration for Power Quality Improvement in Microgrids, KARABIBER, A., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 19, 2019.
Digital Object Identifier: 10.4316/AECE.2019.02013 [CrossRef] [Full text]
 A precision detection technique for power disturbance in electrical system, Usman, Adil, Choudhry, Mohammad Ahmad, Electrical Engineering, ISSN 0948-7921, 2021.
Digital Object Identifier: 10.1007/s00202-021-01343-0 [CrossRef]
Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.
Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.