評価・診断に関するシンポジウム講演論文集
Online ISSN : 2424-3027
セッションID: 104
会議情報
104 ベイジアンネットワークによる回転機械の状態診断法(セッション1 モデル解析・設計)
朱 晶晶李 可薛 紅濤陳 山鵬
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会議録・要旨集 フリー

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抄録
In order to effectively identify faults of a rotating mechanics, a new kind of symptom parameter ------ Relative Ratio Symptom Parameter (RRSP) is proposed in this paper. Moreover, combined with Bayesian Network, the corresponding fault diagnosis system is built. In the paper, the vibration signals are monitored and measured and the relative ratio symptom parameter is calculated, of which the parameters whose identification index is bigger are chosen as the input of Bayesian Network, by observing and analyzing the output that is the probability of normal state and abnormal states, Bayesian Network in the mechanical fault diagnosis is proved to be effective by real data measured in each state of a rotating machine.
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© 2010 一般社団法人 日本機械学会
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