한국소음진동공학회:학술대회논문집 (Proceedings of the Korean Society for Noise and Vibration Engineering Conference)
- 한국소음진동공학회 2014년도 추계학술대회 논문집
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- Pages.833-834
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- 2014
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- 1598-2548(pISSN)
은닉 마르코프 모델을 이용한 질량 편심이 있는 회전기기의 상태진단
Condition Monitoring Of Rotating Machine With Mass Unbalance Using Hidden Markov Model
초록
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.
키워드