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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. Working with such problem, one needs to contend with many uncertainty sources such as system, model and sensory noise.
Mosallam, Ahmed +2 more
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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, Zhenzhen Liu, Hongfu Zuo
exaly +3 more sources
A remaining useful life prediction method based on PSR-former
Scientific Reports, 2022 AbstractThe non-linear and non-stationary vibration data generated by rotating machines can be used to analyze various fault conditions for predicting the remaining useful life(RUL). It offers great help to make prognostic and health management(PHM) develop.
Huang Zhang +6 more
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Aircraft Engine Remaining Useful Life Prediction Using Machine Learning
The International FLAIRS Conference ProceedingsKnowing 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 reduce the risk of downtime.In this work, we consider two problems in the prediction of RUL: a binary ...
Michael Kimollo, Xudong Liu
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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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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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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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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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Predicting the remaining useful life of rolling element bearings [PDF]
2018 IEEE International Conference on Industrial Technology (ICIT), 2018 Condition monitoring of rolling element bearings is of vital importance in order to keep the industrial wheels running. In wind industry this is especially important due to the challenges in practical maintenance. The paper presents an attempt to improve the capability of prediction of remaining useful life of rolling bearings. The approach is based on
Hooghoudt, Jan Otto +4 more
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