대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)

대한전기학회 (The Korean Institute of Electrical Engineers)
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전력 외란 자동 식별을 위한 특징 벡터 추출 기법

A Feature Vector Extraction Method For the Automatic Classification of Power Quality Disturbances

  • 이철호 (한양대학고 전기공학과) ;
  • 이재상 (한양대학고 전기공학과) ;
  • 조관영 (한양대학고 전기공학과) ;
  • 정지현 (한양대학고 전기공학과) ;
  • 남상원 (한양대학고 전기공학과)
  • Lee, Chul-Ho (Dept. of Electrical Engineering, Hanyang University) ;
  • Lee, Jae-Sang (Dept. of Electrical Engineering, Hanyang University) ;
  • Cho, Kwan-Young (Dept. of Electrical Engineering, Hanyang University) ;
  • Chung, Ji-Hyun (Dept. of Electrical Engineering, Hanyang University) ;
  • Nam, Sang-Won (Dept. of Electrical Engineering, Hanyang University)
  • 발행 : 1996.11.16
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초록

The objective of this paper is to present a new feature-vector extraction method for the automatic detection and classification of power quality(PQ) disturbances, where FFT, DWT(Discrete Wavelet Transform), and data compression are utilized to extract an appropriate feature vector. In particular, the proposed classifier consists of three parts: i.e., (i) automatic detection of PQ disturbances, where the wavelet transform and signal power estimation method are utilized to detect each disturbance, (ii) feature vector extraction from the detected disturbance, and (iii) automatic classification, where Multi-Layer Perceptron(MLP) is used to classify each disturbance from the corresponding extracted feature vector. To demonstrate the performance and applicability of the proposed classification algorithm, some test results obtained by analyzing 7-class power quality disturbances generated by the EMTP are also provided.

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