Power Quality Disturbances Detection and Classification Rule-Based Decision Tree

F. Zaro
{"title":"Power Quality Disturbances Detection and Classification Rule-Based Decision Tree","authors":"F. Zaro","doi":"10.37394/232014.2021.17.3","DOIUrl":null,"url":null,"abstract":"In this paper, the power quality (PQ) disturbances have been detected and classified using Stockwell’s transform (S-transform) and rule-based decision tree (DT) according to IEEE standards. The proposed technique based on the extracted features of the PQ events signals, which are extracted from the time-frequency analysis. Several PQ disturbances are considered with simple and complex disturbances to include spike, flicker, oscillatory transient, impulsive transient, and notch. The performance and robustness of the proposed technique for the recognition of PQ disturbances have been demonstrated through the results of the various disturbances. By comparing the performance of the proposed technique with other reported studies it was distinguished results under noiseless and noisy conditions.","PeriodicalId":151897,"journal":{"name":"WSEAS Transactions on Signal Processing archive","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"WSEAS Transactions on Signal Processing archive","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37394/232014.2021.17.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

In this paper, the power quality (PQ) disturbances have been detected and classified using Stockwell’s transform (S-transform) and rule-based decision tree (DT) according to IEEE standards. The proposed technique based on the extracted features of the PQ events signals, which are extracted from the time-frequency analysis. Several PQ disturbances are considered with simple and complex disturbances to include spike, flicker, oscillatory transient, impulsive transient, and notch. The performance and robustness of the proposed technique for the recognition of PQ disturbances have been demonstrated through the results of the various disturbances. By comparing the performance of the proposed technique with other reported studies it was distinguished results under noiseless and noisy conditions.
基于规则的电能质量干扰检测与分类决策树
本文根据IEEE标准,利用斯托克韦尔变换(s变换)和基于规则的决策树(DT)对电能质量(PQ)干扰进行检测和分类。提出了一种基于时频分析提取PQ事件信号特征的方法。考虑了几种PQ干扰,包括脉冲、闪烁、振荡瞬态、脉冲瞬态和陷波等简单和复杂的干扰。通过各种干扰的结果证明了所提出的PQ干扰识别技术的性能和鲁棒性。通过与其他已报道的研究进行比较,该方法在无噪声和有噪声条件下得到了明显的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信