Markov Modeling of Component Fault Growth Over A Derived Domain of Feasible Output Control Effort Modifications

Metadata Updated: May 2, 2019

This paper introduces a novel Markov process formulation of stochastic fault growth modeling, in order to facilitate the development and analysis of prognostics-based control adap- tation. A metric representing the relative deviation between the nominal output of a system and the net output that is ac- tually enacted by an implemented prognostics-based control routine, will be used to define the action space of the formu- lated Markov process. The state space of the Markov pro- cess will be defined in terms of an abstracted metric repre- senting the relative health remaining in each of the system’s components. The proposed formulation of component fault dynamics will conveniently relate feasible system output per- formance modifications to predictions of future component health deterioration.

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Public: This dataset is intended for public access and use. License: U.S. Government Work

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Metadata Created Date August 1, 2018
Metadata Updated Date May 2, 2019
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date August 1, 2018
Metadata Updated Date May 2, 2019
Publisher Dashlink
Unique Identifier DASHLINK_690
Miryam Strautkalns
Maintainer Email
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Datagov Dedupe Retained 20190501230127
Harvest Object Id 80eee818-b616-4b00-a89b-9d4dcc719e49
Harvest Source Id 39e4ad2a-47ca-4507-8258-852babd0fd99
Harvest Source Title NASA Data.json
Data First Published 2013-04-12
Homepage URL
Data Last Modified 2018-07-19
Program Code 026:029
Source Datajson Identifier True
Source Hash 757b1d0f8a2f7cb1a74d2e5053fcddc846e39e19
Source Schema Version 1.1

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