A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network
Joint Authors
Wang, Zhijian
Cai, Wenan
Zhou, Jie
Du, Wenhua
Wang, Jingtai
He, Gaofeng
Zheng, Likang
Han, Xiaofeng
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-06-20
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
In the era of big data, data-driven methods mainly based on deep learning have been widely used in the field of intelligent fault diagnosis.
Traditional neural networks tend to be more subjective when classifying fault time-frequency graphs, such as pooling layer, and ignore the location relationship of features.
The newly proposed neural network named capsules network takes into account the size and location of the image.
Inspired by this, capsules network combined with the Xception module (XCN) is applied in intelligent fault diagnosis, so as to improve the classification accuracy of intelligent fault diagnosis.
Firstly, the fault time-frequency graphs are obtained by wavelet time-frequency analysis.
Then the time-frequency graphs data which are adjusted the pixel size are input into XCN for training.
In order to accelerate the learning rate, the parameters which have bigger change are punished by cost function in the process of training.
After the operation of dynamic routing, the length of the capsule is used to classify the types of faults and get the classification of loss.
Then the longest capsule is used to reconstruct fault time-frequency graphs which are used to measure the reconstruction of loss.
In order to determine the convergence condition, the three losses are combined through the weight coefficient.
Finally, the proposed model and the traditional methods are, respectively, trained and tested under laboratory conditions and actual wind turbine gearbox conditions to verify the classification ability and reliable ability.
American Psychological Association (APA)
Wang, Zhijian& Zheng, Likang& Du, Wenhua& Cai, Wenan& Zhou, Jie& Wang, Jingtai…[et al.]. 2019. A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network. Complexity،Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1132590
Modern Language Association (MLA)
Wang, Zhijian…[et al.]. A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network. Complexity No. 2019 (2019), pp.1-17.
https://search.emarefa.net/detail/BIM-1132590
American Medical Association (AMA)
Wang, Zhijian& Zheng, Likang& Du, Wenhua& Cai, Wenan& Zhou, Jie& Wang, Jingtai…[et al.]. A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network. Complexity. 2019. Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1132590
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132590