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Power quality disturbance recognition using stransforms and FCM-based decision tree

  • Harbin Institute of Technology
  • Jilin Institute of Chemical Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a new approach for recognizing nonstationary signals in power quality (PQ) disturbances. Meanwhile the new approach includes the most types of PQ disturbance, such as voltage sags, swells, interruptions, transients and harmonics. The new model mainly includes two steps. Firstly, S-transform is used to analyze power system disturbance signals, and two most distinguishing features are extracted. In this process based on these two features, 2D feature vectors are clustered using hierarchical Fuzzy C-means algorithm (FCM). Secondly, a binary decision tree is constructed from FCM cluster centers to automatic recognize disturbance patterns. Finally the simulation results show the validity and efficiency of the proposed model.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Pages232-236
Number of pages5
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009 - Shanghai, China
Duration: 20 Nov 200922 Nov 2009

Publication series

NameProceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Volume4

Conference

Conference2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Country/TerritoryChina
CityShanghai
Period20/11/0922/11/09

Keywords

  • Decision tree
  • Fuzzy C-means algrithm(FCM)
  • Pattern recognition
  • Power quslity(PQ)
  • Power quslity(PQ) disturbance
  • S-transform

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