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Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

Metadata Updated: December 6, 2023

Model-based prognostics approaches capture system knowl- edge in the form of physics-based models of components that include how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decom- position approach adapted from the diagnosis community, called possible conflicts, in order to both improve the com- putational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state esti- mate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation- based experiments to demonstrate the approach.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Metadata Created Date November 12, 2020
Metadata Updated Date December 6, 2023
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date December 6, 2023
Publisher Dashlink
Identifier DASHLINK_817
Data First Published 2013-07-29
Data Last Modified 2020-01-29
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Harvest Object Id 865d945a-ac13-4730-9825-cea74fdb14b9
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL
Program Code 026:029
Source Datajson Identifier True
Source Hash 05b1db7a91a2a67d3fb2f9be037ff3b4f80477d256fd76d8a76bc313faa13920
Source Schema Version 1.1

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