Show simple item record

dc.contributor.authorUcar, F. and Alcin, O.F. and Dandil, B. and Ata, F.
dc.date.accessioned2021-04-08T12:08:29Z
dc.date.available2021-04-08T12:08:29Z
dc.date.issued2016
dc.identifier10.1109/MMAR.2016.7575171
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84991769772&doi=10.1109%2fMMAR.2016.7575171&partnerID=40&md5=377ce5b3900eb46c0efdcf399350d234
dc.identifier.urihttp://acikerisim.bingol.edu.tr/handle/20.500.12898/4617
dc.description.abstractToday's industrial environment is smarter than ever before. Most production lines include electrical devices which are able to communicate each other and controlled from a single station with automation systems. Most of those elements have an internet connection link known as industrial internet. Development of smart technology with industrial internet comes with a need of monitoring. Monitoring technologies are emergent systems that focus on fault detection, grid self - healings and online tracking of power quality issues. Present study deals with one of the essential part of an electricity grid monitoring system called power quality event classification in a manner of machine learning topic. Power quality events to be processed are generated synthetically by means of a comprehensive software tool. Classification of real-like dataset is executed using extreme learning machine which is an extremely fast learning algorithm applied to single layer neural networks. Basic statistical criteria and wavelet - entropy methods are handled to achieve distinctive features of dataset. As a performance evaluation instrument, conventional artificial neural network structure is run too. Detailed results are discussed to prove the satisfactory performance of proposed pattern recognition model. © 2016 IEEE.
dc.language.isoEnglish
dc.source2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016
dc.titleMachine learning based power quality event classification using wavelet - Entropy and basic statistical features


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record