Sequential Network with Residual Neural Network for Rotatory Machine Remaining Useful Life Prediction Using Deep Transfer Learning

Siyu Shao
Siyu Shao
Tianlin Niu
Tianlin Niu
Haibin Ding
Haibin Ding

Shock and Vibration, pp. 1-16, 2020.

Cited by: 0|Bibtex|Views2|DOI:https://doi.org/10.1155/2020/8888627
Other Links: academic.microsoft.com

Abstract:

Deep learning has a strong feature learning ability, which has proved its effectiveness in fault prediction and remaining useful life prediction of rotatory machine. However, training a deep network from scratch requires a large amount of training data and is time-consuming. In the practical model training process, it is difficult for the...More

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