한국지능시스템학회:학술대회논문집 (Proceedings of the Korean Institute of Intelligent Systems Conference)

한국지능시스템학회 (Korean Institute of Intelligent Systems)
권호 표지

카오스 특징 추출에 의한 고저항 지락사고의 패턴인식

Recognition of High Impedance Fault Patterns according to the Chaotic Features

  • 신승연 (숭실대학교 전기공학과) ;
  • 공성곤 (숭실대학교 전기공학과)
  • 발행 : 1997.10.01
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초록

This paper presents recognition of high impedance fault patterns based of chaotic features using the Radial Basis Function Network(RBFN). The chaos attractor is reconstructed from the fault current data for pattern recognition. The RBFN successfully classifies the three kinds of fault pattems and one normal pattem.

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