Reliability theory and practice for unmanned aerial vehicles
L Xing, BW Johnson - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Due to rapid advancements on the Internet of Things (IoT), unmanned aerial vehicles
(UAVs), also known as drones, are transforming numerous military and civil application …
(UAVs), also known as drones, are transforming numerous military and civil application …
Condition-based maintenance—an extensive literature review
This paper presents an extensive literature review on the field of condition-based
maintenance (CBM). The paper encompasses over 4000 contributions, analysed through …
maintenance (CBM). The paper encompasses over 4000 contributions, analysed through …
Using deep learning-based approach to predict remaining useful life of rotating components
J Deutsch, D He - IEEE Transactions on Systems, Man, and …, 2017 - ieeexplore.ieee.org
In the age of Internet of Things and Industrial 4.0, prognostic and health management (PHM)
systems are used to collect massive real-time data from mechanical equipment. PHM big …
systems are used to collect massive real-time data from mechanical equipment. PHM big …
A health indicator extraction and optimization framework for lithium-ion battery degradation modeling and prognostics
Maximum releasable capacity and internal resistance are often used as the health indicators
(HIs) of a lithium-ion battery for degradation modeling and estimation of remaining useful life …
(HIs) of a lithium-ion battery for degradation modeling and estimation of remaining useful life …
[HTML][HTML] A condition-based maintenance policy for multi-component systems subject to stochastic and economic dependencies
Y Wang, X Li, J Chen, Y Liu - Reliability Engineering & System Safety, 2022 - Elsevier
Condition-based maintenance (CBM) optimization utilizing prognostic information and
methods for complex systems has attracted increasing attention. This paper presents a bi …
methods for complex systems has attracted increasing attention. This paper presents a bi …
Attention-based LSTM network for rotatory machine remaining useful life prediction
H Zhang, Q Zhang, S Shao, T Niu, X Yang - Ieee Access, 2020 - ieeexplore.ieee.org
As one of the key components in mechanical systems, rotatory machine plays a significant
role in safe and stable operation. Accurate prediction of the Remaining Useful Life (RUL) of …
role in safe and stable operation. Accurate prediction of the Remaining Useful Life (RUL) of …
A Bayesian deep learning RUL framework integrating epistemic and aleatoric uncertainties
Recent years have witnessed the prominent advancements of deep learning (DL) in the
arsenal of prognostics and health management. However, the prognostic uncertainty …
arsenal of prognostics and health management. However, the prognostic uncertainty …
Multi-level predictive maintenance for multi-component systems
In this paper, a novel predictive maintenance policy with multi-level decision-making is
proposed for multi-component system with complex structure. The main idea is to propose a …
proposed for multi-component system with complex structure. The main idea is to propose a …
A risk-averse remaining useful life estimation for predictive maintenance
Remaining useful life (RUL) prediction is an advanced technique for system maintenance
scheduling. Most of existing RUL prediction methods are only interested in the precision of …
scheduling. Most of existing RUL prediction methods are only interested in the precision of …
Predictive maintenance decision-making for variable faults with non-equivalent costs of fault severities
Predictive Maintenance is crucial for production systems as it helps maintaining the
reliability and availability of components/equipment as well as preventing unexpected …
reliability and availability of components/equipment as well as preventing unexpected …