A Directed Acyclic Graph Network Combined With CNN and LSTM for Remaining Useful Life Prediction

A Directed Acyclic Graph Network Combined With CNN and LSTM for Remaining Useful Life Prediction

Accurate and timely prediction of remaining useful life (RUL) of a machine enables the machine to have an appropriate operation and maintenance decision. Data-driven RUL prediction methods are more attractive to researchers because they can be deployed quicker and cheaper compared to other approache...

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Bibliographic Details
Main Authors: Jialin Li, Xueyi Li, David He
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Remaining useful life prediction
long-short-term memory network
convolutional neural networks
turbofan engine
Online Access:https://ieeexplore.ieee.org/document/8723466/

Internet

https://ieeexplore.ieee.org/document/8723466/

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