Prognostics Algorithms Python Package

The NASA PCoE Prognostic Algorithms Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems. The package provides an extendable set of algorithms for state estimation and prediction, including uncertainty propagation. The package also include metrics, visualization, and analysis tools needed to measure the prognostic performance. The algorithms use prognostic models (from NASA’s Prognostics Model Package) to perform estimation and prediction functions. The library enables the rapid development of prognostics solutions for given models of components and systems. Different algorithms can be easily swapped to do comparative studies and evaluations of different algorithms to select the best for the application at hand.

The Prognostics Models Package was developed by researchers of the NASA Prognostics Center of Excellence (PCoE).

If you are new to this package, see getting_started.html.

Citing this repository

Use the following to cite this repository:

@misc{2020_nasa_prog_model,

author = {Christopher Teubert and Chetan Kulkarni and Matteo Corbetta}, title = {Prognostics Algorithms Python Package}, month = Dec, year = 2020, version = {0.3.4}, url = {https://github.com/nasa/prog_algs} }

The corresponding reference should look like this:

  1. Teubert, C. Kulkarni, M. Corbetta Prognostics Algorithms Python Package, v0.2.0, Dec. 2020. URL https://github.com/nasa/prog_algs.

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