Proceedings of the KIPE Conference (전력전자학회:학술대회논문집)

The Korean Institute of Power Electronics (전력전자학회)
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A Power Quality Monitoring system using wavelet based RBF network

웨이블릿 기반의 RBF 신경망을 이용한 전력품질 진단시스템

  • Kim Hong kyun (School of electrical and computer engineering, Chungbuk National University) ;
  • Lee Jinmok (School of electrical and computer engineering, Chungbuk National University) ;
  • Choi Jeaho (School of electrical and computer engineering, Chungbuk National University) ;
  • Lee Sanghoon (Poscon Ltd.) ;
  • Kim Jaesig (Poscon Ltd.)
  • 김홍균 (충북대학교 전기전자 컴퓨터공학부) ;
  • 이진목 (충북대학교 전기전자 컴퓨터공학부) ;
  • 최재호 (충북대학교 전기전자 컴퓨터공학부) ;
  • 이상훈 ((주)포스콘) ;
  • 김재식 ((주)포스콘)
  • Published : 2004.07.01
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Abstract

This paper presents a wavelet-based neural network technology for the detection and classification of the various types of power quality disturbances. Power quality phenomena are short-time problems and of many varieties. Particularly, the transients happen during very short durations to the nano- and microsecond. Thus, a method for detecting and classifying transient signals at the same time and in an automatic combines the properties of the wavelet transform and the advantages of neural networks. Especially, the additional feature extraction to improve the recognition rate is considered. The configuration of the hardware of WN (PQ-DAS) and some case studies are described.

Keywords