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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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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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A failure-efficient prediction of remaining useful life
Machine Learning. EngineeringPredicting the remaining useful life (RUL) is crucial for effective condition-based maintenance, enhancing cost-effectiveness, productivity, and safety by enabling timely maintenance interventions. A fundamental challenge in data-driven RUL prediction is
Sang Bin Moon +3 more
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Predictive maintenance programs for aircraft engines based on remaining useful life prediction. [PDF]
Sci RepAbstract The remaining useful life (RUL) and utilization strategy of an aero-engine are related to the flight safety of an aircraft, which directly affects the flight itself and the safety of the occupants. Aiming at the complexity of aero-engine condition monitoring data, an aero-engine predictive maintenance planning framework based ...
Xue F, Jin G, Tan L, Zhang C, Yu Y.
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Aircraft Engine Remaining Useful Life Prediction Using Machine Learning
Proceedings of the International Florida Artificial Intelligence Research Society ConferenceKnowing the Remaining Useful Life (RUL) of aircraft engines is of paramount importance in the aviation industry. RUL helps anticipate engine failures beforehand so that airlines can proactively schedule maintenance, optimize resource allocation, and ...
Michael Kimollo, Xudong Liu
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Multi-Condition Remaining Useful Life Prediction Based on Mixture of Encoders [PDF]
EntropyAccurate Remaining Useful Life (RUL) prediction is vital for effective prognostics in and the health management of industrial equipment, particularly under varying operational conditions.
Yang Liu, Bihe Xu, Yangli-ao Geng
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Remaining Useful Life Prediction of Rolling Bearings Based on CBAM-CNN-LSTM [PDF]
SensorsPredicting the Remaining Useful Life (RUL) is vital for ensuring the reliability and safety of equipment and components. This study introduces a novel method for predicting RUL that utilizes the Convolutional Block Attention Module (CBAM) to address the ...
Bo Sun +4 more
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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 ...
Shaashwat Agrawal +4 more
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Prediction of the Remaining Useful Life of Supercapacitors
Mathematical Problems in Engineering, 2022 As a new type of energy-storage device, supercapacitors are widely used in various energy storage fields because of their advantages such as fast charging and discharging, high power density, wide operating temperature range, and long cycle life. However, the degradation and failure of supercapacitors in large-scale applications will adversely affect ...
Zhenxiao Yi +5 more
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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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