A Sequence-to-Sequence Approach for Remaining Useful Lifetime Estimation Using Attention-augmented Bidirectional LSTM

A Sequence-to-Sequence Approach for Remaining Useful Lifetime Estimation Using Attention-augmented Bidirectional LSTM

We propose a novel sequence-to-sequence prediction approach for the estimation of the remaining useful lifetime (RUL) of technical components. The approach is based on deep recurrent neural network structures, namely bidirectional Long Short Term Memory (LSTM) networks, which we augment with an atte...

Full description

Bibliographic Details
Main Authors: Sayed Rafay Bin Shah, Gavneet Singh Chadha, Andreas Schwung, Steven X. Ding
Format: Article
Language:English
Published: Elsevier 2021-07-01
Series:Intelligent Systems with Applications
Subjects:
Remaining useful lifetime estimation
Encoder-decoder networks
Bidirectional long-short term memory
Attention mechanism
Online Access:http://www.sciencedirect.com/science/article/pii/S2667305321000387

Internet

http://www.sciencedirect.com/science/article/pii/S2667305321000387

Similar Items