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Research on Degradation State Recognition of Planetary Gear Based on Multiscale Information Dimension of SSD and CNN
Joint Authors
Luo, Chengming
Chen, Xihui
Peng, Liping
Cheng, Gang
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Planetary gear is the key part of the transmission system for large complex electromechanical equipment, and in general, a series of degradation states are undergone and evolved into a local fatal fault in its full life cycle.
So it is of great significance to recognize the degradation state of planetary gear for the purpose of maintenance repair, predicting development trend, and avoiding sudden fault.
This paper proposed a degradation state recognition method of planetary gear based on multiscale information dimension of singular spectrum decomposition (SSD) and convolutional neural network (CNN).
SSD can automatically realize the embedding dimension selection and component grouping segmentation, and the original vibration signal being nonlinear and nonstationary can be decomposed into a series of singular spectrum decomposition components (SSDCs), adaptively.
Then, the multiscale information dimension which combines multiscale analysis and fractal information dimension is proposed for quantifying and extracting the feature information contained in each SSDC.
Finally, CNN is used to achieve the effective recognition of the degradation state of planetary gear.
The experimental results show that the proposed method can accurately recognize the degradation state of planetary gear, and the overall recognition rate is up to 97.2%, of which the recognition rate of normal planetary gear reaches 100%.
American Psychological Association (APA)
Chen, Xihui& Peng, Liping& Cheng, Gang& Luo, Chengming. 2019. Research on Degradation State Recognition of Planetary Gear Based on Multiscale Information Dimension of SSD and CNN. Complexity،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1133052
Modern Language Association (MLA)
Chen, Xihui…[et al.]. Research on Degradation State Recognition of Planetary Gear Based on Multiscale Information Dimension of SSD and CNN. Complexity No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1133052
American Medical Association (AMA)
Chen, Xihui& Peng, Liping& Cheng, Gang& Luo, Chengming. Research on Degradation State Recognition of Planetary Gear Based on Multiscale Information Dimension of SSD and CNN. Complexity. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1133052
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133052