상세 보기
초록
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.
키워드
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)
- 제목
- HMM을 이용한 회전체 결함 진단
- 제목 (타언어)
- Fault diagnosis of rotating system using Hidden markov model
- 저자
- 고정민; 최찬규; 강토; 한순우; 박진호; 유홍희
- 발행일
- 2015-04
- 유형
- Proceeding
- 저널명
- 한국소음진동공학회 2015년도 춘계학술대회 논문집
- 페이지
- 830 ~ 831