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HMM을 이용한 회전체 시스템의 질량편심 결함진단Fault Diagnosis of Rotating System Mass Unbalance Using Hidden Markov Model
- Other Titles
- Fault Diagnosis of Rotating System Mass Unbalance Using Hidden Markov Model
- Issue Date
- Sep-2015
- Publisher
- 한국소음진동공학회
- Keywords
- 은닉 마르코프 모델; 결함 진단; 특징 벡터; 벡터 양자화; 질량 편심; 회전체; Hidden Markov Model; Fault Diagnosis; Feature Vector; Vector Quantization; Mass Unbalance; Rotating System
- Citation
- 한국소음진동공학회논문집, v.25, no.9, pp.637 - 643
- Indexed
- KCI
- Journal Title
- 한국소음진동공학회논문집
- Volume
- 25
- Number
- 9
- Start Page
- 637
- End Page
- 643
- ISSN
- 1598-2785
- Abstract
- 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.
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Collections - 서울 공과대학 > 서울 기계공학부 > 1. Journal Articles
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