An end-to-end framework for remaining useful life prediction of rolling bearing based on feature pre-extraction mechanism and deep adaptive transformer model.
Nov 1, 2021 · An end-to-end framework for remaining useful life prediction of rolling bearing based on feature pre-extraction mechanism and deep adaptive ...
To solve this problem, a new remaining useful life prediction approach based on deep feature representation and long short-term memory neural network is ...
Nov 26, 2023 · Abstract—Accurate prediction of the Remaining Useful Life. (RUL) of rolling bearings is crucial in industrial production,.
The framework of RUL prediction for rolling bearing is established by integrating multi-domain mixed features and temporal convolutional network (TCN). The ...
A novel transformer-based DL model enhanced by position-sensitive ...
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May 2, 2024 · Accurate prediction of remaining useful life (RUL) for aircraft engines is essential for proactive maintenance and safety assurance.
May 8, 2024 · The proposed approach includes a CNN-VAE model and a MBiLSTM model. The CNN-VAE model performs well for automatically extracting low-dimensional ...
Feb 5, 2024 · In this paper, a novel framework for forecasting the RUL of bearings is put forward, which includes the construction of a health indicator with ...
An end-to-end framework for remaining useful life prediction of rolling bearing based on feature pre-extraction mechanism and deep adaptive transformer model.
An end-to-end framework for remaining useful life prediction of rolling bearing based on feature pre-extraction mechanism and deep adaptive transformer model.