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HMM을 이용한 회전체 결함 진단Fault diagnosis of rotating system using Hidden markov model
- Other Titles
- Fault diagnosis of rotating system using Hidden markov model
- Issue Date
- Apr-2015
- Publisher
- 한국소음진동공학회
- Keywords
- Hidden Markov Model(HMM; 은닉 마르코프 모델); Fault Diagnosis(결함 진단); Feature Vector(특징벡터); Vector Quantization(벡터 양자화); Mass unbalance(질량 편심); Rotating Machine(회전 기기)
- Citation
- 한국소음진동공학회 2015년도 춘계학술대회 논문집, pp.830 - 831
- Indexed
- OTHER
- Journal Title
- 한국소음진동공학회 2015년도 춘계학술대회 논문집
- Start Page
- 830
- End Page
- 831
- ISSN
- 1598-2548
- Abstract
- In recent years, pattern recognition methods have been widely used by many 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 paper, a hidden markov model method for the fault diagnosis of a rotating system is introduced, and a rotating machine with mass unbalance and bearing fault is selected for fault diagnosis. Moreover, a diagnosis procedure to identity the size of a defect is proposed in this paper.
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Collections - 서울 공과대학 > 서울 기계공학부 > 1. Journal Articles
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