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Diagnostics & Prognostics Group Release New Prognostics Research Python Packages
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Diagnostics & Prognostics Group Release New Prognostics Research Python Packages

Researchers from the Intelligent Systems Division's Diagnostics & Prognostics group and the Prognostics Center of Excellence (PCoE) have released a pair of Python packages to assist in prognostics research. These packages provide modular, extendable tools for creating and simulating degradation (prognostics) models, performing systems health-state estimation and prediction, creating new systems health-state estimation and prediction algorithms, benchmarking prognostics performance, and visualizing results. These tools are intended to help researchers in industry, academia, and government build new models, algorithms, and software architectures for prognostics. Functionality is similar to the previously released MATLAB Prognostics Model, Algorithm, and Metrics Libraries, but these tools are in Python — responding to a trend towards Python in the Prognostics and Health Management (PHM) community — and apply the lessons learned since the creation of the MATLAB libraries. There are two parts to the PCoE's Python Prognostics Packages:

  1. Prognostics Models: Python modeling framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems. Available on pip (pip install prog_models) for Python 3.6-3.8 with source code and documentation.
  2. Prognostics Algorithms: Python framework for model-based prognostics of engineering systems. Available on pip (pip install prog_algs) for Python 3.6-3.8 with source code and documentation.

The packages will be updated with new features as work progresses.

BACKGROUND: The Diagnostics & Prognostics (D&P) group has a rich history of releasing software to the broader PHM community. Past released projects include the Generic Software Architecture for Prognostics (GSAP), the MATLAB Python Libraries, the Hybrid Diagnostics Engine (HyDE), and XPlaneConnect. In recent years, the PHM community has been moving towards Python as the primary development language. As a result, last October, the D&P Group started work on a set of Python prognostics research tools that eventually became the Python Prognostics Packages.

NASA PROGRAM FUNDING: Autonomous Systems and Operations (ASO) project (POC: Jeremy Frank), Human Exploration Operations Mission Directorate (HEOMD); and the System Wide Safety (SWS) project (POC: Wendy Okolo), Aeronautics Research Mission Directorate (ARMD)

TEAM: Matteo Corbetta, Chetan Kulkarni, and Chris Teubert

POINT OF CONTACT: Chris Teubert, christopher.a.teubert@nasa.gov

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