Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling

H Rauf, M Khalid, N Arshad - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Designing and deployment of state-of-the-art electric vehicles (EVs) in terms of low cost and
high driving range with appropriate reliability and security are identified as the key towards …

Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application

H Lv, J Chen, T Pan, T Zhang, Y Feng, S Liu - Measurement, 2022 - Elsevier
Attention Mechanism has become very popular in the field of mechanical fault diagnosis in
recent years and has become an important technique for scholars to study and apply. The …

An integrated multi-head dual sparse self-attention network for remaining useful life prediction

J Zhang, X Li, J Tian, H Luo, S Yin - Reliability Engineering & System Safety, 2023 - Elsevier
Committed to accident prevention, prediction of remaining useful life (RUL) plays a crucial
role in prognostics health management technology. Conventional convolutional neural …

A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings

Y Cao, Y Ding, M Jia, R Tian - Reliability Engineering & System Safety, 2021 - Elsevier
Remaining useful life (RUL) prediction has been a hotspot in the engineering field, which is
useful to avoid unexpected breakdowns and reduce maintenance costs of the system. Due …

Health status assessment and remaining useful life prediction of aero-engine based on BiGRU and MMoE

Y Zhang, Y Xin, Z Liu, M Chi, G Ma - Reliability Engineering & System …, 2022 - Elsevier
Prognostics and health management (PHM) is a critical work to ensure the reliable operation
of industrial equipment, in which health status (HS) assessment and remaining useful life …

A parallel hybrid neural network with integration of spatial and temporal features for remaining useful life prediction in prognostics

J Zhang, J Tian, M Li, JI Leon… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Prediction of remaining useful life (RUL) is an indispensable part of prognostics health
management (PHM) in complex systems. Considering the parallel integration of the spatial …

Dual-aspect self-attention based on transformer for remaining useful life prediction

Z Zhang, W Song, Q Li - IEEE Transactions on Instrumentation …, 2022 - ieeexplore.ieee.org
Remaining useful life (RUL) prediction is one of the key technologies of condition-based
maintenance (CBM), which is important to maintain the reliability and safety of industrial …

Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction

S Xiang, Y Qin, J Luo, H Pu, B Tang - Reliability Engineering & System …, 2021 - Elsevier
The prediction of aero-engine remaining useful life (RUL) is helpful for its operation and
maintenance. Aiming at the challenge that most neural networks (NNs), including long short …

Adaptive self-attention LSTM for RUL prediction of lithium-ion batteries

Z Wang, N Liu, C Chen, Y Guo - Information Sciences, 2023 - Elsevier
To achieve an accurate remaining useful life (RUL) prediction for lithium-ion batteries (LIBs),
this study proposes an adaptive self-attention long short-term memory (SA-LSTM) prediction …

Remaining useful life prediction of bearings by a new reinforced memory GRU network

J Zhou, Y Qin, D Chen, F Liu, Q Qian - Advanced Engineering Informatics, 2022 - Elsevier
The remaining useful life (RUL) prediction of bearings has great significance in the
predictive maintenance of mechanical equipment. Owing to the difficulty of collecting …