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 …
A systematic literature review on transfer learning for predictive maintenance in industry 4.0
The advent of Industry 4.0 has resulted in the widespread usage of novel paradigms and
digital technologies within industrial production and manufacturing systems. The objective of …
digital technologies within industrial production and manufacturing systems. The objective of …
A survey of transfer learning for machinery diagnostics and prognostics
In industrial manufacturing systems, failures of machines caused by faults in their key
components greatly influence operational safety and system reliability. Many data-driven …
components greatly influence operational safety and system reliability. Many data-driven …
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 …
A multi-channel decoupled deep neural network for tunnel boring machine torque and thrust prediction
Accurate prediction of thrust and torque plays a crucial role in the control parameters
optimization and intelligent tunneling of tunnel boring machines (TBMs). Currently …
optimization and intelligent tunneling of tunnel boring machines (TBMs). Currently …
Tensor representation-based transferability analytics and selective transfer learning of prognostic knowledge for remaining useful life prediction across machines
In recent years, deep transfer learning techniques have been successfully applied to solve
RUL prediction across different working conditions. However, for RUL prediction across …
RUL prediction across different working conditions. However, for RUL prediction across …
A cumulative descriptor enhanced ensemble deep neural networks method for remaining useful life prediction of cutting tools
X Mo, T Wang, Y Zhang, X Hu - Advanced Engineering Informatics, 2023 - Elsevier
Prognostics and health management (PHM) of turbine cutting tools, particularly the
remaining useful life (RUL) prediction is a Gordian technique to maintain the reliability and …
remaining useful life (RUL) prediction is a Gordian technique to maintain the reliability and …
A novel Brownian correlation metric prototypical network for rotating machinery fault diagnosis with few and zero shot learners
J Yang, C Wang - Advanced Engineering Informatics, 2022 - Elsevier
Due to the variability of working conditions and the scarcity of fault samples, the existing
diagnosis models still have a big gap under the condition of covering more practical …
diagnosis models still have a big gap under the condition of covering more practical …
Adaptive feature utilization with separate gating mechanism and global temporal convolutional network for remaining useful life prediction
Machinery remaining useful life (RUL) prediction plays a pivotal role in modern industrial
maintenance. Traditional methods entail the manual selection of useful features, which …
maintenance. Traditional methods entail the manual selection of useful features, which …
[HTML][HTML] Hybrid scheme through read-first-LSTM encoder-decoder and broad learning system for bearings degradation monitoring and remaining useful life estimation
Y Zhu, J Wu, X Liu, J Wu, K Chai, G Hao… - Advanced Engineering …, 2023 - Elsevier
This paper proposes a novel hybrid scheme through read-first-LSTM (RLSTM) encoder-
decoder and broad learning system (BLS) for bearings degradation monitoring and …
decoder and broad learning system (BLS) for bearings degradation monitoring and …