A Data-Driven-Based Framework for Battery Remaining Useful Life Prediction
IEEE Access, 2023 Electric vehicles are expected to dominate the vehicle fleet in the near future due to their zero emissions of pollutants, reduced fossil fuel reserves, comfort, and lightness.
Amal Ezzouhri +3 more
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Remaining Useful Life Prediction Based on Multi-Representation Domain Adaptation
Mathematics, 2022 All current deep learning-based prediction methods for remaining useful life (RUL) assume that training and testing data have similar distributions, but the existence of various operating conditions, failure modes, and noise lead to insufficient data ...
Yi Lyu +3 more
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Aero-Engine Remaining Useful Life Prediction Based on Bi-Discrepancy Network
Sensors, 2023 Most unsupervised domain adaptation (UDA) methods align feature distributions across different domains through adversarial learning. However, many of them require introducing an auxiliary domain alignment model, which incurs additional computational ...
Nachuan Liu +3 more
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LSTM-Based Broad Learning System for Remaining Useful Life Prediction
Mathematics, 2022 Prognostics and health management (PHM) are gradually being applied to production management processes as industrial production is gradually undergoing a transformation, turning into intelligent production and leading to increased demands on the ...
Xiaojia Wang +3 more
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Battery Remaining Useful Life Prediction with Inheritance Particle Filtering
Energies, 2019 Accurately forecasting a battery’s remaining useful life (RUL) plays an important role in the prognostics and health management of rechargeable batteries. An effective forecast is reported using a particle filter (PF), but it currently suffers from
Lin Li +3 more
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Remaining Useful Life Prediction of High-Frequency Swing Self-Lubricating Liner
Shock and Vibration, 2021 The remaining useful life (RUL) prediction of self-lubricating spherical plain bearings is essential for replacement decision-making and the reliability of high-end equipment. The high-frequency swing self-lubricating liner (HSLL) is the key component of
Xiuhong Hao +3 more
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An Explainable Artificial Intelligence Approach for Remaining Useful Life Prediction
Aerospace, 2023 Prognosis and health management depend on sufficient prior knowledge of the degradation process of critical components to predict the remaining useful life. This task is composed of two phases: learning and prediction.
Genane Youness, Adam Aalah
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Predicting Remaining Useful Life with Similarity-Based Priors [PDF]
, 2020 Prognostics is the area of research that is concerned with predicting the remaining useful life of machines and machine parts. The remaining useful life is the time during which a machine or part can be used, before it must be replaced or repaired.
Youri Soons +3 more
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Remaining Useful Life Prediction of Lithium-Ion Battery Using ICC-CNN-LSTM Methodology
Energies, 2023 In recent years, lithium-ion batteries have gained significant attention due to their crucial role in various applications, such as electric vehicles and renewable energy storage.
Catherine Rincón-Maya +4 more
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Remaining useful life prediction based on an integrated neural network
工程科学学报, 2020 Unexpected failures and unscheduled maintenance activities of mechanical systems might incur considerable waste of resources and high investment costs. Thus, in recent years, prognostics and health management (PHM) has received a lot of attention because
Yong-feng ZHANG, Zhi-qiang LU
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