JvdHoogen/paderborn_bearing
Package for preprocessing Paderborn Bearing dataset
This project helps mechanical engineers and data scientists working with machinery diagnostics easily access and prepare the Paderborn Bearing Dataset. It takes raw MATLAB files containing sensor readings from bearings with various fault conditions and outputs structured numerical arrays (for motor current, vibrations) and corresponding fault labels. The primary users are researchers or engineers developing machine learning models for predictive maintenance or fault detection in rotating machinery.
No commits in the last 6 months. Available on PyPI.
Use this if you need to quickly extract, preprocess, and prepare the Paderborn Bearing Dataset for analysis or model training, without manually handling the MATLAB files.
Not ideal if you are working with bearing datasets other than the Paderborn one, or if you prefer to manually extract and process data from MATLAB files.
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Language
Python
License
MIT
Category
Last pushed
Jul 09, 2025
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