Abstract
The fault diagnosis of early failure bearing can discover the potential danger in the mechanical equipment in time. It remains a great challenge due to the noise interference. Although many diagnosis methods have been proposed, the characteristics of signal have not yet been fully investigated, which leads to unsatisfactory diagnosis results. To solve this problem, a weak fault detection method with a two-stage key frequency focusing model is designed. Translation invariance in time domain and translation variance in frequency domain are systematically considered. The effectiveness is verified on four constructed datasets. The results show that the designed network has the best comprehensive performance comparing to the state-of-the-art methods. Copyright © 2021 ISA. Published by Elsevier Ltd. All rights reserved.
Original language | English |
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Pages (from-to) | 384-399 |
Journal | ISA Transactions |
Volume | 125 |
Early online date | Jun 2021 |
DOIs | |
Publication status | Published - Jun 2022 |
Citation
Gao, D., Zhu, Y., Kang, W., Fu, H., Yan, K., & Ren, Z. (2022). Weak fault detection with a two-stage key frequency focusing model. ISA transactions, 125, 384-399. doi: 10.1016/j.isatra.2021.06.014Keywords
- Weak-fault related features
- Frequency focusing
- Translation variance
- Translation invariance
- Fault diagnosis