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–a review on the statistical data driven approaches

XS Si, W Wang, CH Hu, DH Zhou - European journal of operational …, 2011 - Elsevier
Remaining useful life (RUL) is the useful life left on an asset at a particular time of operation.
Its estimation is central to condition based maintenance and prognostics and health …

Remaining life prediction of lithium-ion batteries based on health management: A review

K Song, D Hu, Y Tong, X Yue - Journal of Energy Storage, 2023 - Elsevier
Lithium-ion battery remaining useful life (RUL) is an essential technology for battery
management, safety assurance and predictive maintenance, which has attracted the …

Deep feature extraction in lifetime prognostics of lithium-ion batteries: Advances, challenges and perspectives

C Li, H Zhang, P Ding, S Yang, Y Bai - Renewable and Sustainable Energy …, 2023 - Elsevier
The wide application of lithium-ion batteries makes their lifecycle prognosis a challenging
and hot topic in the battery management research field. Feature extraction is a key step for …

A data-driven predictive prognostic model for lithium-ion batteries based on a deep learning algorithm

P Khumprom, N Yodo - Energies, 2019 - mdpi.com
Prognostic and health management (PHM) can ensure that a lithium-ion battery is working
safely and reliably. The main approach of PHM evaluation of the battery is to determine the …

Artificial intelligence in prognostics and health management of engineering systems

S Ochella, M Shafiee, F Dinmohammadi - Engineering Applications of …, 2022 - Elsevier
Prognostics and health management (PHM) has become a crucial aspect of the
management of engineering systems and structures, where sensor hardware and decision …

Cloud-enabled prognosis for manufacturing

R Gao, L Wang, R Teti, D Dornfeld, S Kumara, M Mori… - CIRP annals, 2015 - Elsevier
Advanced manufacturing depends on the timely acquisition, distribution, and utilization of
information from machines and processes across spatial boundaries. These activities can …

A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation

XS Si, W Wang, CH Hu, MY Chen, DH Zhou - Mechanical Systems and …, 2013 - Elsevier
Remaining useful life estimation (RUL) is an essential part in prognostics and health
management. This paper addresses the problem of estimating the RUL from the observed …

Transfer learning with deep recurrent neural networks for remaining useful life estimation

A Zhang, H Wang, S Li, Y Cui, Z Liu, G Yang, J Hu - Applied Sciences, 2018 - mdpi.com
Prognostics, such as remaining useful life (RUL) prediction, is a crucial task in condition-
based maintenance. A major challenge in data-driven prognostics is the difficulty of …

Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries

T Raoofi, M Yildiz - Journal of Energy Storage, 2023 - Elsevier
The battery-powered propulsion system is introduced in the literature as a suitable solution
for the CO 2 emission challenge induced by aviation. However, because of design and …