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PHMD: An easy data access tool for prognosis and health management datasets
David Solís-Martín, Juan Galán-Páez, Joaquín Borrego-Díaz
This work introduces a comprehensive open-source Python library designed for seamless access and handling of Prognostics and Health Management (PHM) datasets. The library currently supports 59 datasets from diverse domains, and has been developed to simplify, datasets search, retrieval, load, and preprocessing while standardizing data formats for easy integration in machine learning workflows. With built-in metadata handling and task-specific experiment settings for diagnosis, prognosis, and detection, users can efficiently prepare and analyze data without needing to manage raw file formats or directories. Available through GitHub and PyPI, the library provides a robust foundation for PHM research and application, offering useful resources to boost the projects of practitioners and researchers alike.
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