Improving Distributed Diagnosis Through Structural Model Decomposition
Complex engineering systems require efficient fault diagnosis methodologies, but centralized ap- proaches do not scale well, and this motivates the development of distributed solutions. This work presents an event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, by using the structural model decompo- sition capabilities provided by Possible Conflicts. We develop a distributed diagnosis algorithm that uses residuals, computed by extending Possible Conflicts, to build local event-based diagnosers based on global diagnosability analysis that gen- erate globally correct local diagnosis results. The proposed approach is applied to a multi-tank sys- tem, and results demonstrate an improvement in the design of local diagnosers. Since local diag- nosers use only a subset of the residuals, and use subsystem models to compute residuals (instead of the global system model), the local diagnosers are more efficient than previously developed dis- tributed approaches.
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[ "026:00" ] |
| contactPoint |
{ "fn": "Miryam Strautkalns", "@type": "vcard:Contact", "hasEmail": "mailto:miryam.strautkalns@nasa.gov" } |
| description | Complex engineering systems require efficient fault diagnosis methodologies, but centralized ap- proaches do not scale well, and this motivates the development of distributed solutions. This work presents an event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, by using the structural model decompo- sition capabilities provided by Possible Conflicts. We develop a distributed diagnosis algorithm that uses residuals, computed by extending Possible Conflicts, to build local event-based diagnosers based on global diagnosability analysis that gen- erate globally correct local diagnosis results. The proposed approach is applied to a multi-tank sys- tem, and results demonstrate an improvement in the design of local diagnosers. Since local diag- nosers use only a subset of the residuals, and use subsystem models to compute residuals (instead of the global system model), the local diagnosers are more efficient than previously developed dis- tributed approaches. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "12-BregonEtAl-ImprovingDistribDiagnosis-DX2011.pdf", "format": "PDF", "mediaType": "application/pdf", "description": "12-BregonEtAl-ImprovingDistribDiagnosis-DX2011.pdf", "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/12-BregonEtAl-ImprovingDistribDiagnosis-DX2011.pdf" } ] |
| identifier | DASHLINK_816 |
| issued | 2013-07-29 |
| keyword |
[ "ames", "dashlink", "nasa" ] |
| landingPage | https://c3.nasa.gov/dashlink/resources/816/ |
| modified | 2025-03-31 |
| programCode |
[ "026:029" ] |
| publisher |
{ "name": "Dashlink", "@type": "org:Organization" } |
| title | Improving Distributed Diagnosis Through Structural Model Decomposition |
