System-level Prognostics for the National Airspace

Matthew Daigle, Shankar Sankararaman, and Indranil Roychoudhury
Submission Type: 
Full Paper
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phmc_16_052.pdf2.97 MBAugust 26, 2016 - 1:41pm

In the National Airspace System (NAS), safety is assured through a set of rules, regulations, and procedures to respond to unsafe events. However, safety stands to benefit immensely from the introduction of tools and methodologies from Prognostics and Health Management (PHM). PHM will enable the NAS to stochastically predict unsafe states within the NAS, enabling a proactive preventative response strategy, as opposed to a reactive mitigative one. However, current PHM methods are limited and do not directly apply to the NAS for several reasons: they typically apply only to the component level, are implemented in a centralized manner, and are focused only on predicting remaining useful life. In this paper, we extend the model-based prognostics approach to PHM in order to provide a framework that can be applied to the NAS. We offer a system-level approach that supports distributed implementation, and provide algorithms to predict the probability of an unsafe state, either at a specific time or within a time interval, and to predict the time of an unsafe state. Experimental results in simulation demonstrate the new approach.

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Submission Keywords: 
system-level prognostics
Challenges in Prognostics
flight safety
aleatory uncertainty
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
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