PHMD: An easy data access tool for prognosis and health management datasets

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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Publication Details

Journal
SoftwareX
Published
2025-01-22
DOI
https://doi.org/10.1016/j.softx.2025.102039
Citations
5
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
3.41

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article

PHMD: An easy data access tool for prognosis and health management datasets

Juan Galán‐Paez, Joaquín Borrego‐Díaz, David Solis‐Martín
5 citations
SoftwareX
Advanced Battery Technologies Research
3.41
article

PHMD: An easy data access tool for prognosis and health management datasets

Juan Galán‐Paez, Joaquín Borrego‐Díaz, David Solis‐Martín
article en
5 citations

Abstract

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.

SoftwareXVol. 29
Universidad de Sevilla (ES)
Agencia Estatal de Investigación
Openalex Percentile: Top 9%
Advanced Battery Technologies Research
3.41
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