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Remaining Useful Life Prediction Using Temporal Convolution with Attention [PDF]
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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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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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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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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Remaining Useful Life Prediction Based on Deep Learning: A Survey [PDF]
SensorsRemaining useful life (RUL) is a metric of health state for essential equipment. It plays a significant role in health management. However, RUL is often random and unknown.
Fuhui Wu +3 more
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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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Rolling Bearing Remaining Useful Life Prediction Based on CNN-VAE-MBiLSTM [PDF]
SensorsEnsuring precise prediction of the remaining useful life (RUL) for bearings in rolling machinery is crucial for preventing sudden machine failures and optimizing equipment maintenance strategies.
Lei Yang +3 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 ...
Agrawal, Shaashwat +4 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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