A review on lifetime prediction of proton exchange membrane fuel cells system

Z Hua, Z Zheng, E Pahon, MC Péra, F Gao - Journal of Power Sources, 2022 - Elsevier
The proton exchange membrane fuel cells (PEMFC) system is a promising eco-friendly
power converter device in a wide range of applications, especially in the transportation area …

Machine learning for reliability engineering and safety applications: Review of current status and future opportunities

Z Xu, JH Saleh - Reliability Engineering & System Safety, 2021 - Elsevier
Abstract Machine learning (ML) pervades an increasing number of academic disciplines and
industries. Its impact is profound, and several fields have been fundamentally altered by it …

Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture

L Liu, X Song, Z Zhou - Reliability Engineering & System Safety, 2022 - Elsevier
Remaining useful life (RUL) estimation has been intensively studied, given its important role
in prognostics and health management (PHM) of industry. Recently, data-driven structures …

Machinery health prognostics: A systematic review from data acquisition to RUL prediction

Y Lei, N Li, L Guo, N Li, T Yan, J Lin - Mechanical systems and signal …, 2018 - Elsevier
Machinery prognostics is one of the major tasks in condition based maintenance (CBM),
which aims to predict the remaining useful life (RUL) of machinery based on condition …

Remaining useful life estimation in prognostics using deep convolution neural networks

X Li, Q Ding, JQ Sun - Reliability Engineering & System Safety, 2018 - Elsevier
Traditionally, system prognostics and health management (PHM) depends on sufficient prior
knowledge of critical components degradation process in order to predict the remaining …

Deep learning for prognostics and health management: State of the art, challenges, and opportunities

B Rezaeianjouybari, Y Shang - Measurement, 2020 - Elsevier
Improving the reliability of engineered systems is a crucial problem in many applications in
various engineering fields, such as aerospace, nuclear energy, and water declination …

Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction

X Li, W Zhang, Q Ding - Reliability engineering & system safety, 2019 - Elsevier
Accurate evaluation of machine degradation during long-time operation is of great
importance. With the rapid development of modern industries, physical model is becoming …

A novel deep learning method based on attention mechanism for bearing remaining useful life prediction

Y Chen, G Peng, Z Zhu, S Li - Applied Soft Computing, 2020 - Elsevier
Rolling bearing is a key component in rotation machine, whose remaining useful life (RUL)
prediction is an essential issue of constructing condition-based maintenance (CBM) system …

A review on prognostics and health management (PHM) methods of lithium-ion batteries

H Meng, YF Li - Renewable and Sustainable Energy Reviews, 2019 - Elsevier
Batteries are prevalent energy providers for modern systems. They can also be regarded as
storage units for renewable and sustainable energy. Failures of batteries can bring huge …

Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods

Z Zhang, X Si, C Hu, Y Lei - European Journal of Operational Research, 2018 - Elsevier
Degradation-based modeling methods have been recognized as an essential and effective
approach for lifetime and remaining useful life (RUL) estimations for various health …