HMM을 이용한 회전체 시스템의 질량편심 결함진단

Fault Diagnosis of Rotating System Mass Unbalance Using Hidden Markov Model
  • 고정민
  • 최찬규
  • 강토
  • 한순우
  • 박진호
  • 외 1명

초록

In recent years, pattern recognition methods have been widely used by many researchers for fault diagnoses of mechanical systems. The soundness of a mechanical system can be checked by analyzing the variation of the system vibration characteristic along with a pattern recognition method. Recently, the hidden Markov model has been widely used as a pattern recognition method in various fields. In this paper, the hidden Markov model is employed for the fault diagnosis of the mass unbalance of a rotating system. Mass unbalance is one of the critical faults in the rotating system. A procedure to identity the location and size of the mass unbalance is proposed and the accuracy of the procedure is validated through experiment.

키워드

은닉 마르코프 모델결함 진단특징 벡터벡터 양자화질량 편심회전체Hidden Markov ModelFault DiagnosisFeature VectorVector QuantizationMass UnbalanceRotating System
제목
HMM을 이용한 회전체 시스템의 질량편심 결함진단
제목 (타언어)
Fault Diagnosis of Rotating System Mass Unbalance Using Hidden Markov Model
저자
고정민최찬규강토한순우박진호유홍희
DOI
10.5050/KSNVE.2015.25.9.637
발행일
2015-09
저널명
한국소음진동공학회논문집
25
9
페이지
637 ~ 643