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Remaining Useful Life Estimation in Prognosis: An Uncertainty Propagation Problem
Author(s) -
Shankar Sankararaman,
Kai Goebel
Publication year - 2013
Publication title -
aiaa infotech@aerospace (i@a) conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2013-4901
Subject(s) - estimation , computer science , propagation of uncertainty , algorithm , engineering , systems engineering
The estimation of remaining useful life is significant in the context of prognostics and health monitoring, and the prediction of remaining useful life is essential for online operations and decision-making. However, it is challenging to accurately predict the remaining useful life in practical aerospace applications due to the presence of various uncertainties that affect prognostic calculations, and in turn, render the remaining useful life prediction uncertain. It is challenging to identify and characterize the various sources of uncertainty in prognosis, understand how each of these sources of uncertainty affect the uncertainty in the remaining useful life prediction, and thereby compute the overall uncertainty in the remaining useful life prediction. In order to achieve these goals, this paper proposes that the task of estimating the remaining useful life must be approached as an uncertainty propagation problem. In this context, uncertainty propagation methods which are available in the literature are reviewed, and their applicability to prognostics and health monitoring are discussed.

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