mohyunho/N-CMAPSS_DL
N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)
This tool helps prognostics engineers and data scientists prepare NASA's N-CMAPSS turbofan engine degradation dataset for machine learning models. It takes raw HDF5 sensor data from simulated engine runs and transforms it into structured NumPy arrays, suitable for training models that predict remaining useful life (RUL). The output is time-windowed samples, ready for deep learning architectures.
106 stars. No commits in the last 6 months.
Use this if you are working with the N-CMAPSS turbofan engine dataset and need to efficiently prepare it for training machine learning or deep learning models, especially to predict how long an engine component will last.
Not ideal if you are not using the N-CMAPSS dataset or if you need to perform real-time data processing directly on streaming sensor data rather than pre-processing a static dataset.
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106
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Language
Jupyter Notebook
License
Apache-2.0
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Last pushed
Apr 13, 2023
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