Abhijit-Bhumireddy99/RUL_Prediction
remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN), and Long Short Term Memory (LSTM) unit
This project helps maintenance managers and operations engineers predict when mechanical bearings are likely to fail. By analyzing raw vibration signals from equipment, it estimates the 'Remaining Useful Life' (RUL) for each bearing. This allows for proactive maintenance scheduling to prevent unexpected breakdowns.
201 stars. No commits in the last 6 months.
Use this if you need to predict the failure of mechanical bearings based on vibration data to optimize maintenance schedules and reduce downtime.
Not ideal if you're looking to predict failures for machine components other than bearings, or if you don't have access to vibration signal data.
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201
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20
Language
Jupyter Notebook
License
GPL-3.0
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Last pushed
Apr 06, 2024
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