{"@type": "dcat:Dataset", "accessLevel": "public", "accrualPeriodicity": "irregular", "bureauCode": ["026:00"], "contactPoint": {"@type": "vcard:Contact", "fn": "Miryam Strautkalns", "hasEmail": "mailto:miryam.strautkalns@nasa.gov"}, "description": "This paper presents a distributed Bayesian fault diagnosis scheme for physical systems. Our diagnoser design is based on a procedure for factoring the global system bond graph (BG) into a set of structurally observable bond graph fac- tors (BG-Fs). Each BG-F is systematically translated into a corresponding DBN Factor (DBN-F), which is then used in its corresponding local diagnoser for quantitative fault detec- tion, isolation, and identification. By construction, the ran- dom variables in each DBN-F are conditionally independent of the random variables in all other DBN-Fs, given a subset of communicated measurements considered as system inputs. Each DBN-F and BG-F pair is used to derive a local diag- noser that generates globally correct diagnosis results by lo- cal analysis. Together, the local diagnosers diagnose all single faults of interest in the system. We demonstrate on an electri- cal system how our distributed diagnosis scheme is compu- tationally more efficient than its centralized counterpart, but without compromising the accuracy of the diagnosis results.", "distribution": [{"@type": "dcat:Distribution", "description": "2010_ICBGM_DistrDiagDactoredBGs.pdf", "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/2010_ICBGM_DistrDiagDactoredBGs.pdf", "format": "PDF", "mediaType": "application/pdf", "title": "2010_ICBGM_DistrDiagDactoredBGs.pdf"}], "identifier": "DASHLINK_805", "issued": "2013-07-23", "keyword": ["ames", "dashlink", "nasa"], "landingPage": "https://c3.nasa.gov/dashlink/resources/805/", "modified": "2025-03-31", "programCode": ["026:029"], "publisher": {"@type": "org:Organization", "name": "Dashlink"}, "title": "Distributed Diagnosis in Uncertain Environments Using Dynamic Bayesian Networks"}