{"title":"Analysis of three phase power quality disturbances","authors":"R. Shilpa, S. Prabhu, P. Puttaswamy","doi":"10.1109/ERECT.2015.7499057","DOIUrl":null,"url":null,"abstract":"The ephemeral power quality distortions such as voltage swell, harmonics, transients, voltage sag are incrementing every day with the proliferation of number of solid state contrivances. The technical difficulties like mis-operation, heating are upshots of this and hence identification and relegation of the noise become an essential work. The three-phase voltage distortions are decomposed by the Multivariate Empirical Mode algorithm, for identification of its features and Support vector machine is used as a classifier. The online authentic-time, three-phase data are additionally tested in the presented approach.","PeriodicalId":140556,"journal":{"name":"2015 International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ERECT.2015.7499057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The ephemeral power quality distortions such as voltage swell, harmonics, transients, voltage sag are incrementing every day with the proliferation of number of solid state contrivances. The technical difficulties like mis-operation, heating are upshots of this and hence identification and relegation of the noise become an essential work. The three-phase voltage distortions are decomposed by the Multivariate Empirical Mode algorithm, for identification of its features and Support vector machine is used as a classifier. The online authentic-time, three-phase data are additionally tested in the presented approach.