Multiple Damage Progression Paths in Model-based Prognostics
Description
Model-based prognostics approaches employ do- main knowledge about a system, its components, and how they fail through the use of physics-based models. Compo- nent wear is driven by several different degradation phenom- ena, each resulting in their own damage progression path, overlapping to contribute to the overall degradation of the component. We develop a model-based prognostics method- ology using particle filters, in which the problem of charac- terizing multiple damage progression paths is cast as a joint state-parameter estimation problem. The estimate is repre- sented as a probability distribution, allowing the prediction of end of life and remaining useful life within a probabilistic framework that supports uncertainty management. We also develop a novel variance control mechanism that maintains an uncertainty bound around the hidden parameters to limit the amount of estimation uncertainty and, consequently, reduce prediction uncertainty. We construct a detailed physics-based model of a centrifugal pump, to which we apply our model- based prognostics algorithms. We illustrate the operation of the prognostic solution with a number of simulation-based experiments and demonstrate the performance of the chosen approach when multiple damage mechanisms are active.
Resources
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Description |
Link |
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33 |
2011_IEEEAerospace_pump_paths.pdf |
https://c3.nasa.gov/dashlink/static/media/publication/2011_IEEEAerospace_pump_paths.pdf |