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...

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Bibliographic Details

Published in:	Intelligent Systems with Applications
Main Authors:	Sayed Rafay Bin Shah, Gavneet Singh Chadha, Andreas Schwung, Steven X. Ding
Format:	Article
Language:	English
Published:	Elsevier 2021-07-01
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