Investigation of uncertainty treatment capability of model-based and data-driven prognostic methods using simulated data

Piero Baraldi, Francesca Mangili and Enrico Zio

Reliability Engineering and System Safety, 2013, vol. 112, issue C, 94-108

Abstract: We look at different prognostic approaches and the way of quantifying confidence in equipment Remaining Useful Life (RUL) prediction. More specifically, we consider: (1) a particle filtering scheme, based on a physics-based model of the degradation process; (2) a bootstrapped ensemble of empirical models trained on a set of degradation observations measured on equipments similar to the one of interest; (3) a bootstrapped ensemble of empirical models trained on a sequence of past degradation observations from the equipment of interest only.

Keywords: Prognostics; Uncertainty; Particle filtering; Bootstrap ensemble; Turbine blade; Creep (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:112:y:2013:i:c:p:94-108

DOI: 10.1016/j.ress.2012.12.004

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