Results 11 to 20 of about 530,506 (256)
A DLSTM-Network-Based Approach for Mechanical Remaining Useful Life Prediction
Sensors, 2022 Remaining useful life prediction is one of the essential processes for machine system prognostics and health management. Although there are many new approaches based on deep learning for remaining useful life prediction emerging in recent years, these ...
Yan Liu +5 more
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Remaining Useful Life Prediction Under Imperfect Prior Degradation Information
IEEE Access, 2020 The remaining useful life (RUL) prediction is the core of equipment maintenance and decision-making. Accurate RUL prediction can make effective maintenance before the failure occurs to reduce the probability of equipment failure.
Wan Changhao +4 more
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Cross-Domain Remaining Useful Life Prediction Based on Adversarial Training
Machines, 2022 Remaining useful life prediction can assess the time to failure of degradation systems. Currently, numerous neural network-based prediction methods have been proposed by researchers.
Yuhang Duan +3 more
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Prediction of Tool Remaining Useful Life Based on NHPP-WPHM
Mathematics, 2023 A tool remaining useful life prediction method based on a non-homogeneous Poisson process and Weibull proportional hazard model (WPHM) is proposed, taking into account the grinding repair of machine tools during operation.
Yingzhi Zhang +4 more
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Automated Machine Learning for Remaining Useful Life Predictions
2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2023 Being able to predict the remaining useful life (RUL) of an engineering system is an important task in prognostics and health management. Recently, data-driven approaches to RUL predictions are becoming prevalent over model-based approaches since no underlying physical knowledge of the engineering system is required.
Marc-André Zöller +4 more
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Remaining useful life prediction for equipment based on RF-BiLSTM
AIP Advances, 2022 The prediction technology of remaining useful life has received a lot attention to ensure the reliability and stability of complex mechanical equipment. Due to the large-scale, non-linear, and high-dimensional characteristics of monitoring data, machine ...
Zhiqiang Wu +8 more
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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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