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Qualitative Event-based Diagnosis with Possible Conflicts: Case Study on the Third International Diagnostic Competition
We describe two model-based diagnosis algo- rithms entered into the Third International Diag- nostic Competition. We focus on the first diag- nostic problem of the industrial track of the com- petition in which a diagnosis algorithm must de- tect, isolate, and identify faults in an electrical power distribution testbed in order to provide cor- rect abort recommendations. Both diagnosis al- gorithms are based on a qualitative event-based fault isolation framework augmented with model- based fault identification. Although based on a common framework, the fundamental difference between the two algorithms is that one is based on a global model for residual generation, fault iso- lation, and fault identification, whereas the other uses a set of minimal submodels computed using Possible Conflicts. We describe, compare, and contrast the two algorithms in terms of practical implementation and their diagnosis results.
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 | We describe two model-based diagnosis algo- rithms entered into the Third International Diag- nostic Competition. We focus on the first diag- nostic problem of the industrial track of the com- petition in which a diagnosis algorithm must de- tect, isolate, and identify faults in an electrical power distribution testbed in order to provide cor- rect abort recommendations. Both diagnosis al- gorithms are based on a qualitative event-based fault isolation framework augmented with model- based fault identification. Although based on a common framework, the fundamental difference between the two algorithms is that one is based on a global model for residual generation, fault iso- lation, and fault identification, whereas the other uses a set of minimal submodels computed using Possible Conflicts. We describe, compare, and contrast the two algorithms in terms of practical implementation and their diagnosis results. |
| distribution |
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{
"@type": "dcat:Distribution",
"title": "11-DaigleEtAl-QED-DXC11.pdf",
"format": "PDF",
"mediaType": "application/pdf",
"description": "11-DaigleEtAl-QED-DXC11.pdf",
"downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/11-DaigleEtAl-QED-DXC11.pdf"
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|
| identifier | DASHLINK_815 |
| issued | 2013-07-29 |
| keyword |
[
"ames",
"dashlink",
"nasa"
]
|
| landingPage | https://c3.nasa.gov/dashlink/resources/815/ |
| modified | 2025-04-01 |
| programCode |
[
"026:029"
]
|
| publisher |
{
"name": "Dashlink",
"@type": "org:Organization"
}
|
| title | Qualitative Event-based Diagnosis with Possible Conflicts: Case Study on the Third International Diagnostic Competition |
