베어링 결함이 있는 회전기계의 상태 진단을 위한 은닉 마르코프 모델의 적용

Title
베어링 결함이 있는 회전기계의 상태 진단을 위한 은닉 마르코프 모델의 적용
Other Titles
Application of Hidden Markov Model to Condition Monitoring of Rotating Machine with Mass Unbalance
Authors
유홍희
Keywords
Hidden Markov Model; HMM, 마르코프 모델; Fault Diagnosis; 결함 진단; Feature Vector; 특징벡터; Vector Quantization; 벡터 양자화; Bearing fault; 베어링 결함
Issue Date
2015-05
Publisher
대한기계학회
Citation
2015년도 동역학 및 제어부문 춘계학술대회 논문집, 2015.05, 117-118
Abstract
In recent research, pattern recognition method has been widely used by many researchers for fault diagnoses of mechanical systems. Also it determines the soundness of a mechanical system by detecting variations in the systems's vibration characteristics. Hidden Markov model (HMM) has recently been used as pattern recognition methods in various fields. In this study, a HMM method for the fault diagnosis of a rotating machine with bearing fault is introduced. The existence, location, and quantity of bearing fault are identified. Also Fast Fourier Transform (FFT) is employed to extract feature vector.
URI
http://www.dbpia.co.kr/Journal/ArticleDetail/NODE06340976?TotalCount=1&Seq=1&q=%5B%EB%B2%A0%EC%96%B4%EB%A7%81%20%EC%9C%A0%ED%99%8D%ED%9D%AC%C2%A7coldb%C2%A72%C2%A751%C2%A73%5D&searchWord=%EC%A0%84%EC%B2%B4%3D%5E%24%EB%B2%A0%EC%96%B4%EB%A7%81%20%EC%9C%A0%ED%99%8D%ED%9D%AC%5E*&Multimedia=0&isIdentifyAuthor=0&Collection=0&SearchAll=%EB%B2%A0%EC%96%B4%EB%A7%81%20%EC%9C%A0%ED%99%8D%ED%9D%AC&isFullText=0&specificParam=0&SearchMethod=0&Sort=1&SortType=desc&Page=1&PageSize=20http://hdl.handle.net/20.500.11754/24599
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > MECHANICAL ENGINEERING(기계공학부) > Articles
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