Rolling-Element Bearing Fault Data Automatic Clustering Based on Wavelet and Deep Neural Network
Joint Authors
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-04
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
A method based on wavelet and deep neural network for rolling-element bearing fault data automatic clustering is proposed.
The method can achieve intelligent signal classification without human knowledge.
The time-domain vibration signals are decomposed by wavelet packet transform (WPT) to obtain eigenvectors that characterize fault types.
By using the eigenvectors, a dataset in which samples are labeled randomly is configured.
The dataset is roughly classified by the distance-based clustering method.
A fine classification process based on deep neural network is followed to achieve accurate classification.
The entire process is automatically completed, which can effectively overcome the shortcomings such as low work efficiency, high implementation cost, and large classification error caused by individual participation.
The proposed method is tested with the bearing data provided by the Case Western Reserve University (CWRU) Bearing Data Center.
The testing results show that the proposed method has good performance in automatic clustering of rolling-element bearings fault data.
American Psychological Association (APA)
Yang, Yanli& Fu, Peiying. 2018. Rolling-Element Bearing Fault Data Automatic Clustering Based on Wavelet and Deep Neural Network. Shock and Vibration،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1215159
Modern Language Association (MLA)
Yang, Yanli& Fu, Peiying. Rolling-Element Bearing Fault Data Automatic Clustering Based on Wavelet and Deep Neural Network. Shock and Vibration No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1215159
American Medical Association (AMA)
Yang, Yanli& Fu, Peiying. Rolling-Element Bearing Fault Data Automatic Clustering Based on Wavelet and Deep Neural Network. Shock and Vibration. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1215159
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1215159