Metric: monotonicity, prognosability, and trendability

nasa / prog_algs

The Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems, and provides a set of algorithms for state estimation and prediction, including uncertainty propagation. The algorithms take as inputs prognostic models (from NASA's Prognostics Model Package), and perform estimation and prediction functions. The library allows 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.

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Metric: monotonicity, prognosability, and trendability #114

Closed teubert closed 2 years ago

teubert commented 2 years ago

add monotonicity, prognosability, and trendability metrics for a RUL Profile

See paper by J. Coble (https://www.papers.phmsociety.org/index.php/phmconf/article/view/1404)

D.o.D.

[ ] monotonicity, prognosability, and trendability metrics implemented as methods or properties for RUL profile
[ ] Add to example
[ ] Add to tutorial
[ ] Add tests
[ ] Add to release notes

teubert commented 2 years ago

Monotonicity split into separate issues. See #176, #177, #175

teubert commented 2 years ago

Prognosability and trend ability are more metrics on data - moved to prog_models