Distributed Damage Estimation for Prognostics based on Structural Model Decomposition
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.
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| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[ "026:00" ] |
| contactPoint |
{ "fn": "Miryam Strautkalns", "@type": "vcard:Contact", "hasEmail": "mailto:miryam.strautkalns@nasa.gov" } |
| description | 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. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "13-DaigleEtAl-DistribDamageEstimation-PHM2011.pdf", "format": "PDF", "mediaType": "application/pdf", "description": "13-DaigleEtAl-DistribDamageEstimation-PHM2011.pdf", "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/13-DaigleEtAl-DistribDamageEstimation-PHM2011.pdf" } ] |
| identifier | DASHLINK_817 |
| issued | 2013-07-29 |
| keyword |
[ "ames", "dashlink", "nasa" ] |
| landingPage | https://c3.nasa.gov/dashlink/resources/817/ |
| modified | 2025-03-31 |
| programCode |
[ "026:029" ] |
| publisher |
{ "name": "Dashlink", "@type": "org:Organization" } |
| title | Distributed Damage Estimation for Prognostics based on Structural Model Decomposition |
