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Markov Modeling of Component Fault Growth over a Derived Domain of Feasible Output Control Effort ModificationsThis paper introduces a novel Markov process formulation of stochastic fault growth modeling, in order to facilitate the development and analysis of prognostics-based control adaptation. A metric representing the relative deviation between the nominal output of a system and the net output that is actually enacted by an implemented prognostics-based control routine, will be used to define the action space of the formulated Markov process. The state space of the Markov process will be defined in terms of an abstracted metric representing the relative health remaining in each of the system s components. The proposed formulation of component fault dynamics will conveniently relate feasible system output performance modifications to predictions of future component health deterioration.
Document ID
20130014354
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Bole, Brian
(Georgia Inst. of Tech. Atlanta, GA, United States)
Goebel, Kai
(NASA Ames Research Center Moffett Field, CA, United States)
Vachtsevanos, George
(Georgia Inst. of Tech. Atlanta, GA, United States)
Date Acquired
August 27, 2013
Publication Date
September 27, 2012
Subject Category
Statistics And Probability
Report/Patent Number
ARC-E-DAA-TN7910
Meeting Information
Meeting: Annual Conference of the Prognostics and Health Management Society 2012
Location: Minneapolis, MN
Country: United States
Start Date: September 23, 2012
End Date: September 27, 2012
Sponsors: Prognostics and Health Management Society (PHM)
Funding Number(s)
CONTRACT_GRANT: NNX11AO50H
Distribution Limits
Public
Copyright
Public Use Permitted.
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