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HMM을 이용한 회전체 시스템의 질량편심 결함진단

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dc.contributor.author고정민-
dc.contributor.author최찬규-
dc.contributor.author강토-
dc.contributor.author한순우-
dc.contributor.author박진호-
dc.contributor.author유홍희-
dc.date.accessioned2022-07-15T21:04:35Z-
dc.date.available2022-07-15T21:04:35Z-
dc.date.created2021-05-13-
dc.date.issued2015-09-
dc.identifier.issn1598-2785-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/156404-
dc.description.abstractIn 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.-
dc.language한국어-
dc.language.isoko-
dc.publisher한국소음진동공학회-
dc.titleHMM을 이용한 회전체 시스템의 질량편심 결함진단-
dc.title.alternativeFault Diagnosis of Rotating System Mass Unbalance Using Hidden Markov Model-
dc.typeArticle-
dc.contributor.affiliatedAuthor유홍희-
dc.identifier.doi10.5050/KSNVE.2015.25.9.637-
dc.identifier.bibliographicCitation한국소음진동공학회논문집, v.25, no.9, pp.637 - 643-
dc.relation.isPartOf한국소음진동공학회논문집-
dc.citation.title한국소음진동공학회논문집-
dc.citation.volume25-
dc.citation.number9-
dc.citation.startPage637-
dc.citation.endPage643-
dc.type.rimsART-
dc.identifier.kciidART002029781-
dc.description.journalClass2-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthor은닉 마르코프 모델-
dc.subject.keywordAuthor결함 진단-
dc.subject.keywordAuthor특징 벡터-
dc.subject.keywordAuthor벡터 양자화-
dc.subject.keywordAuthor질량 편심-
dc.subject.keywordAuthor회전체-
dc.subject.keywordAuthorHidden Markov Model-
dc.subject.keywordAuthorFault Diagnosis-
dc.subject.keywordAuthorFeature Vector-
dc.subject.keywordAuthorVector Quantization-
dc.subject.keywordAuthorMass Unbalance-
dc.subject.keywordAuthorRotating System-
dc.identifier.urlhttp://koreascience.or.kr/article/JAKO201536553081542.page-
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