Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
[HTML][HTML] Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods
C Ferreira, G Gonçalves - Journal of Manufacturing Systems, 2022 - Elsevier
Abstract Approaches such as Cyber-Physical Systems (CPS), Internet of Things (IoT),
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …
Federated learning for machinery fault diagnosis with dynamic validation and self-supervision
Intelligent data-driven machinery fault diagnosis methods have been successfully and
popularly developed in the past years. While promising diagnostic performance has been …
popularly developed in the past years. While promising diagnostic performance has been …
Bayesian transfer learning with active querying for intelligent cross-machine fault prognosis under limited data
Most existing deep learning (DL)-based health prognostic methods assume that the training
and testing datasets are from identical machines operating under similar conditions …
and testing datasets are from identical machines operating under similar conditions …
Challenges and opportunities of AI-enabled monitoring, diagnosis & prognosis: A review
Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …
prognosis, and health management, occupies an increasingly important position in reducing …
Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions
Intelligent data-driven system prognostic methods have been popularly developed in the
recent years. Despite the promising results, most approaches assume the training and …
recent years. Despite the promising results, most approaches assume the training and …
[HTML][HTML] Variational encoding approach for interpretable assessment of remaining useful life estimation
A new method for evaluating aircraft engine monitoring data is proposed. Commonly,
prognostics and health management systems use knowledge of the degradation processes …
prognostics and health management systems use knowledge of the degradation processes …
Data privacy preserving federated transfer learning in machinery fault diagnostics using prior distributions
Federated learning has been receiving increasing attention in the recent years, which
improves model performance with data privacy among different clients. The intelligent fault …
improves model performance with data privacy among different clients. The intelligent fault …
Gated dual attention unit neural networks for remaining useful life prediction of rolling bearings
In the mechatronic system, rolling bearing is a frequently used mechanical part, and its
failure may result in serious accident and major economic loss. Therefore, the remaining …
failure may result in serious accident and major economic loss. Therefore, the remaining …
Bearing remaining useful life prediction using self-adaptive graph convolutional networks with self-attention mechanism
Y Wei, D Wu, J Terpenny - Mechanical Systems and Signal Processing, 2023 - Elsevier
Bearings are commonly used to reduce friction between moving parts. Bearings may fail due
to lubrication failure, contamination, corrosion, and fatigue. To prevent bearing failures, it is …
to lubrication failure, contamination, corrosion, and fatigue. To prevent bearing failures, it is …