Aug 21, 2024 · This paper presents novel approaches that alleviate the existing dependence of most prognostics procedures on Remaining Useful Life (RUL) labelled data for ...
Oct 15, 2024 · The results of the experiments reveal that the DSCNAttnPINN can accurately predict RUL and outperforms certain current data-driven prognostics ...
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How to predict remaining useful lifetime rul?
Additionally, effective RUL prediction can enhance decision-making processes, improve resource allocation, and reduce maintenance costs. In recent years, deep ...
Aug 22, 2024 · ... Remaining Useful Life prediction based on physics-informed data augmentation". Ever wondered how to accomplish prognostics in the absence of ...
Remaining useful life (RUL) prediction, known as 'prognostics', has long been recognized as one of the key technologies in prognostics and health management ...
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This paper aims to facilitate the selection of an appropriate physics-informed machine learning method for predicting long-term degradation in lithium-ion ...
Oct 22, 2024 · This work investigates combining physics-based modeling and machine learning to retain high diagnostic accuracy while mitigating the need to ...
Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions.
An online lifetime estimate can usually be performed following one of three paths: a physics-based model, a data-driven model, or a hybrid model of both [3,4].
This work explores an approach for estimating both epistemic and heteroscedastic aleatoric uncertainties that emerge in RUL prediction deep neural networks.