Paper-Reproduce: (Sensors-MDPI) Remaining Useful Life Prediction Method for Bearings Based on LSTM with Uncertainty Quantification
- "PHM" is raw data. Data detail information can be obtained in *.
- "Remaining Useful Life Prediction Method for Bearings Based on LSTM with Uncertainty Quantification.pdf" is the paper I reproduce.
- "lstm_rul.ipynb" is all the code.
- "data" is the temporary variables.
- Read data amd generate our dataset.
- Generate time and frequency domain features from sampled data.
- Calculate correlation, monotonicity and robust to make feature selection.
- Build LSTM Model and analyse results.
If you have any problem, you can send an email [email protected] or make an issue directly. We can discuss together.