Transactions of the Korean Society of Mechanical Engineers A (대한기계학회논문집A)

The Korean Society of Mechanical Engineers (대한기계학회)
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Pattern Recognition of Rotor Fault Signal Using Bidden Markov Model

은닉 마르코프 모형을 이용한 회전체 결함신호의 패턴 인식

  • 이종민 (한국과학기술연구원 트라이볼로지 연구센터) ;
  • 김승종 (한국과학기술연구원 트라이볼로지 연구센터) ;
  • 황요하 (한국과학기술연구원 트라이볼로지 연구센터) ;
  • 송창섭 (한양대학교 기계공학)
  • Published : 2003.11.01
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Abstract

Hidden Markov Model(HMM) has been widely used in speech recognition, however, its use in machine condition monitoring has been very limited despite its good potential. In this paper, HMM is used to recognize rotor fault pattern. First, we set up rotor kit under unbalance and oil whirl conditions. Time signals of two failure conditions were sampled and translated to auto power spectrums. Using filter bank, feature vectors were calculated from these auto power spectrums. Next, continuous HMM and discrete HMM were trained with scaled forward/backward variables and diagonal covariance matrix. Finally, each HMM was applied to all sampled data to prove fault recognition ability. It was found that HMM has good recognition ability despite of small number of training data set in rotor fault pattern recognition.

Keywords

References

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