Name
Abstract | ||
|---|---|---|
The great success of deep neural network (DNN) in image field stimulates its application in fault detection and diagnose. However due to the limitation of system security, it is impossible to obtain complete fault data as the training database for neural network, so that it is challenging to identify a fault that never occurred before. In this paper, an ensemble approach is proposed to adapt to a ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/INDIN45523.2021.9557388 | 2021 IEEE 19th International Conference on Industrial Informatics (INDIN) |
Keywords | DocType | ISBN |
Training,Deep learning,Fault diagnosis,Databases,Fault detection,Neural networks,Time series analysis | Conference | 978-1-7281-4395-8 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dapeng Zhang | 1 | 3 | 3.41 |
| Zhiwei Gao | 2 | 796 | 61.68 |