An extension of the infograms to novel Bayesian inference for bearing fault feature identification

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An extension of the infograms to novel Bayesian inference for bearing fault feature identification

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作者：Dong Wang ^{dongwang4-c@my.cityu.edu.hk" class="auth_mail" title="E-mail the corresponding author}
关键词：Infogram ; Bayesian inference ; Spherical cubature integration ; Wavelet transform ; Bearing fault diagnosis
刊名：Mechanical Systems and Signal Processing
出版年：2016
出版时间：1 December 2016
年：2016
卷：80
期：Complete
页码：19-30
全文大小：1456 K

文摘

•: The infograms are extended to Bayesian inference based optimal filtering.
•: Infograms based state space models are constructed.
•: Guess negentropy measurements are constructed.
•: Spherical cubature integration is introduced to solve the state space models.
•: The proposed Bayesian inference method is convergent.

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