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Remaining Useful Life Prognosis of Aircraft Brakes
International Journal of Prognostics and Health Management, 2022 We investigate the performance of three different data-driven prognostic methodologies towards the Remaining Useful Life estimation of commercial aircraft brakes being continuously monitored for wear.
Athanasios Oikonomou +4 more
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Bayesian Approach for Remaining Useful Life Prediction
Chemical Engineering Transactions, 2013 Prediction of the remaining useful life (RUL) of critical components is a non-trivial task for industrial applications. RUL can differ for similar components operating under the same conditions.
A. Mosallam, K. Medjaher, N. Zerhouni
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Genetically optimized prediction of remaining useful life [PDF]
Sustainable Computing: Informatics and Systems, 2021 The application of remaining useful life (RUL) prediction has taken great importance in terms of energy optimization, cost-effectiveness, and risk mitigation. The existing RUL prediction algorithms mostly constitute deep learning frameworks. In this paper, we implement LSTM and GRU models and compare the obtained results with a proposed genetically ...
Agrawal, Shaashwat +4 more
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Prediction of Aero-Engine Remaining Useful Life Combined with Fault Information
Machines, 2022 Since the fault information of an aero-engine is very important for the remaining useful life of an aero-engine, the paper proposes to combine the fault information for the remaining useful life prediction of an aero-engine.
Chao Wang, Zhangming Peng, Rong Liu
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Remaining-Useful-Life Prediction for Li-Ion Batteries
Energies, 2023 This paper aims to establish a predictive model for battery lifetime using data analysis. The procedure of model establishment is illustrated in detail, including the data pre-processing, modeling, and prediction.
Yeong-Hwa Chang +3 more
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Data-driven remaining useful life prediction based on domain adaptation [PDF]
PeerJ Computer Science, 2021 As an important part of prognostics and health management, remaining useful life (RUL) prediction can provide users and managers with system life information and improve the reliability of maintenance systems.
Bin cheng Wen +5 more
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Solid-State Lithium Battery Cycle Life Prediction Using Machine Learning
Applied Sciences, 2021 Battery lifetime prediction is a promising direction for the development of next-generation smart energy storage systems. However, complicated degradation mechanisms, different assembly processes, and various operation conditions of the batteries bring ...
Danpeng Cheng +9 more
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Remaining Useful Life Prediction Using Temporal Convolution with Attention
AI, 2021 Prognostic techniques attempt to predict the Remaining Useful Life (RUL) of a subsystem or a component. Such techniques often use sensor data which are periodically measured and recorded into a time series data set.
Wei Ming Tan, T. Hui Teo
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Contending Remaining Useful Life Algorithms
Annual Conference of the PHM Society, 2020 Operational readiness, reliability and safety are all enhanced through condition monitoring. That said, for many assets, there is still a need for a prognostic capability to calculate remaining useful life (RUL). RUL allows operation and maintenance personnel to better schedule assets, and logisticians to order long lead time part to help improve ...
Eric Bechhoefer, Marc Dube
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Remaining Useful Life Estimation Using Neural Ordinary Differential Equations
International Journal of Prognostics and Health Management, 2021 Data-driven machinery prognostics has seen increasing popularity recently, especially with the effectiveness of deep learning methods growing. However, deep learning methods lack useful properties such as the lack of uncertainty quantification of their ...
Marco Star, Kristoffer McKee
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