Name
Title | ||
|---|---|---|
Remaining useful life prediction of bearings under different working conditions using a deep feature disentanglement based transfer learning method |
Abstract | ||
|---|---|---|
1A deep feature disentanglement transfer learning network (DFDTLN) is proposed for RUL prediction.2Domain-invariant and domain-specific features are disentangled by a pair of joint learning autoencoders.3Transfer learning based on deep feature disentanglement has been effectively validated in the RUL prediction. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.ress.2021.108265 | Reliability Engineering & System Safety |
Keywords | DocType | Volume |
Remaining useful life prediction,Transfer learning,Deep feature disentanglement | Journal | 219 |
ISSN | Citations | PageRank |
0951-8320 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Hu | 1 | 0 | 0.34 |
| Yiming Guo | 2 | 0 | 0.34 |
| Liudong Gu | 3 | 1 | 1.64 |
| Yifan Zhou | 4 | 0 | 0.34 |
| Zhisheng Zhang | 5 | 8 | 6.85 |
| Zhiting Zhou | 6 | 0 | 0.34 |