Combining DBN and FCM for Fault Diagnosis of Roller Element Bearings without Using Data Labels
Joint Authors
Tsui, Kwok L.
Wang, Dong
Xu, Fan
Fang, Yan jun
Liang, Jia qi
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-04
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Because deep belief networks (DBNs) in deep learning have a powerful ability to extract useful information from the raw data without prior knowledge, DBNs are used to extract the useful feature from the roller bearings vibration signals.
Unlike classification methods, the clustering method can classify the different fault types without data label.
Therefore, a method based on deep belief networks (DBNs) in deep learning (DL) and fuzzy C-means (FCM) clustering algorithm for roller bearings fault diagnosis without a data label is presented in this paper.
Firstly, the roller bearings vibration signals are extracted by using DBN, and then principal component analysis (PCA) is used to reduce the dimension of the vibration signal features.
Secondly, the first two principal components (PCs) are selected as the input of fuzzy C-means (FCM) for roller bearings fault identification.
Finally, the experimental results show that the fault diagnosis of the method presented is better than that of other combination models, such as variation mode decomposition- (VMD-) singular value decomposition- (SVD-) FCM, and ensemble empirical mode decomposition- (EEMD-) fuzzy entropy- (FE-) PCA-FCM.
American Psychological Association (APA)
Xu, Fan& Fang, Yan jun& Wang, Dong& Liang, Jia qi& Tsui, Kwok L.. 2018. Combining DBN and FCM for Fault Diagnosis of Roller Element Bearings without Using Data Labels. Shock and Vibration،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1215162
Modern Language Association (MLA)
Xu, Fan…[et al.]. Combining DBN and FCM for Fault Diagnosis of Roller Element Bearings without Using Data Labels. Shock and Vibration No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1215162
American Medical Association (AMA)
Xu, Fan& Fang, Yan jun& Wang, Dong& Liang, Jia qi& Tsui, Kwok L.. Combining DBN and FCM for Fault Diagnosis of Roller Element Bearings without Using Data Labels. Shock and Vibration. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1215162
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1215162