Attention-Based LSTM Network for Rotatory Machine Remaining Useful Life Prediction

Attention-Based LSTM Network for Rotatory Machine Remaining Useful Life Prediction

As one of the key components in mechanical systems, rotatory machine plays a significant role in safe and stable operation. Accurate prediction of the Remaining Useful Life (RUL) of rotatory machine contributes to realization of intelligent operation and maintenance for mechanical manufacturing. In...

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Bibliographic Details
Main Authors: Hao Zhang, Qiang Zhang, Siyu Shao, Tianlin Niu, Xinyu Yang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Rotatory machine
deep learning
long short-term memory
attention mechanism
remaining useful life
Online Access:https://ieeexplore.ieee.org/document/9143075/

Internet

https://ieeexplore.ieee.org/document/9143075/

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