machine-failure-prediction-ml

This project focuses on predictive maintenance using machine learning and AI to detect machine failures from vibration data. The primary goal is to analyze vibration signals from main journal bearings in internal combustion engines under diverse climatic and varying operating conditions. By leveraging this data, we aim to reduce downtime and enable data-driven, transparent maintenance decisions.

Installation

To set up the project, clone the repository and install the required dependencies:

pip install -r requirements.txt

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Used dataset

link: https://www.sciencedirect.com/science/article/pii/S2352340924011764

To start

If you want to use already parsed data, refer to the analyze-parsed-data notebook for investigations.

If you need to get new datasource, create parser under data-parser directory.