Bi-LSTM-Based Two-Stream Network for Machine Remaining Useful Life Prediction
Author:
Affiliation:
1. Agency for Science, Technology and Research (A*STAR), Institute for Infocomm Research, Singapore
2. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
Funder
Agency for Science, Technology and Research (A*STAR) under Career Development Award
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/9717300/09758765.pdf?arnumber=9758765
Reference38 articles.
1. KDnet-RUL: A Knowledge Distillation Framework to Compress Deep Neural Networks for Machine Remaining Useful Life Prediction
2. A Weighted Deep Domain Adaptation Method for Industrial Fault Prognostics According to Prior Distribution of Complex Working Conditions
3. A multimodal and hybrid deep neural network model for Remaining Useful Life estimation
4. Long short-term memory for machine remaining life prediction
5. Dimensionality Reduction by Learning an Invariant Mapping
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