Detection and Classification of Defect Signals from Rotator by AE Signal Pattern Recognition

AE 신호 형상 인식법에 의한 회전체의 신호 검출 및 분류 연구

  • 김구영 (LG전선 알루미늄기술그룹) ;
  • 이강용 (연세대학교 기계공학과) ;
  • 김희수 (한국전력공사 전력연구원 발전설비지원그룹) ;
  • 이현 (한국전력공사 전력연구원 발전설비지원그룹)
  • Published : 2001.09.01

Abstract

The signal pattern recognition method by acoustic emission signal is applied to detect and classify the defects of a journal bearing in a power plant. AE signals of main defects such as overheating, wear and corrosion are obtained from a small scale model. To detect and classify the defects, AE signal pattern recognition program is developed. As the classification methods, the wavelet transformation analysis, the frequency domain analysis and time domain analysis are used. Among three analyses, the wavelet transformation analysis is most effective to detect and classify the defects of the journal bearing..