A new method based on stochastic process models for machine remaining useful life prediction

Y Lei, N Li, J Lin - IEEE Transactions on Instrumentation and …, 2016 - ieeexplore.ieee.org
Remaining useful life (RUL) prediction is a key process in condition-based maintenance for
machines. It contributes to reducing risks and maintenance costs and increasing the …

Remaining useful life prediction by fusing expert knowledge and condition monitoring information

T Xiahou, Z Zeng, Y Liu - IEEE Transactions on Industrial …, 2020 - ieeexplore.ieee.org
In this article, we develop a mixture of Gaussians-evidential hidden Markov model (MoG-
EHMM) to fuse expert knowledge and condition monitoring information for remaining useful …

Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries

D Wang, Y Zhao, F Yang, KL Tsui - Mechanical Systems and Signal …, 2017 - Elsevier
Brownian motion with adaptive drift has attracted much attention in prognostics because its
first hitting time is highly relevant to remaining useful life prediction and it follows the inverse …

A remaining useful life prognosis of turbofan engine using temporal and spatial feature fusion

C Peng, Y Chen, Q Chen, Z Tang, L Li, W Gui - Sensors, 2021 - mdpi.com
The prognosis of the remaining useful life (RUL) of turbofan engine provides an important
basis for predictive maintenance and remanufacturing, and plays a major role in reducing …

An adaptive prognostic approach via nonlinear degradation modeling: Application to battery data

XS Si - IEEE Transactions on Industrial Electronics, 2015 - ieeexplore.ieee.org
Remaining useful life (RUL) estimation via degradation modeling is considered as one of
the most central components in prognostics and health management. Current RUL …

Degradation modeling and remaining useful life prediction of aircraft engines using ensemble learning

Z Li, K Goebel, D Wu - Journal of Engineering for …, 2019 - asmedigitalcollection.asme.org
Degradation modeling and prediction of remaining useful life (RUL) are crucial to
prognostics and health management of aircraft engines. While model-based methods have …

[HTML][HTML] Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences

M Kraus, S Feuerriegel - Decision Support Systems, 2019 - Elsevier
Predicting the remaining useful life of machinery, infrastructure, or other equipment can
facilitate preemptive maintenance decisions, whereby a failure is prevented through timely …