Condition Monitoring Of Rotating Machine With Mass Unbalance Using Hidden Markov Model

은닉 마르코프 모델을 이용한 질량 편심이 있는 회전기기의 상태진단

  • 고정민 (한양대학교 융합기계공학과) ;
  • 최찬규 (한양대학교 융합기계공학과) ;
  • 강토 (한국원자력연구원) ;
  • 한순우 (한국원자력연구원) ;
  • 박진호 (한국원자력연구원) ;
  • 유홍희 (한양대학교 융합기계공학과)
  • Published : 2014.10.29

Abstract

In recent years, a pattern recognition method has been widely used by researchers for fault diagnoses of mechanical systems. A pattern recognition method determines the soundness of a mechanical system by detecting variations in the system's vibration characteristics. Hidden Markov model has recently been used as pattern recognition methods in various fields. In this study, a HMM method for the fault diagnosis of a mechanical system is introduced, and a rotating machine with mass unbalance is selected for fault diagnosis. Moreover, a diagnosis procedure to identity the size of a defect is proposed in this study.

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