Sparse representation-based classification for the planetary gearbox with improved KPCA and dictionary learning
A fault diagnosis method for the planetary gearbox according to sparse representation-based classification (SRC) has been presented in this paper. Considering the real-time performance and accuracy rate of the fault diagnosis, the proposed method has introduced the improved kernel principal componen...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-01-01
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| Series: | Systems Science & Control Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/21642583.2020.1777218 |