Pinned Repositories
RESS-Paper-2022.09-Remaining-useful-life-prediction-by-TaFCN
The source code of paper: Trend attention fully convolutional network for remaining useful life estimation in the turbofan engine PHM of CMAPSS dataset. Signal selection, Attention mechanism, and Interpretability of deep learning are explored.
HIT-dataset
This is a dataset of inter-shaft bearing based on the vibration signal of rotors and casings, which comes from a aero-engine test with inter-shaft bearing fault. Due to the large size of the data set file, we uploaded the dataset to Google Drive with the link as: https://drive.google.com/drive/folders/1Km1Go4ilB_bI033SBJ7eJ0uCzbqEqbgt?usp=sharing
RUL_Inception-Attention
Remaining useful life prediction by Transformer-based Model
phm-rul-estimation
case study for remaining useful life estimation
Probabilistic_RUL_Prediction
Turbofan-engine-RUL-prediction
RUL prediction for C-MAPSS dataset, reproduction of this paper: https://personal.ntu.edu.sg/xlli/publication/RULAtt.pdf
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