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An Integrated Framework for Model-Based Distributed Diagnosis and PrognosisDiagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detection, isolation and identification of faults, while prognosis consists of prediction of the remaining useful life of systems. This paper presents a novel integrated framework for model-based distributed diagnosis and prognosis, where system decomposition is used to enable the diagnosis and prognosis tasks to be performed in a distributed way. We show how different submodels can be automatically constructed to solve the local diagnosis and prognosis problems. We illustrate our approach using a simulated four-wheeled rover for different fault scenarios. Our experiments show that our approach correctly performs distributed fault diagnosis and prognosis in an efficient and robust manner.
Document ID
20130001690
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Bregon, Anibal (Valladolid Univ. Spain)
Daigle, Matthew J. (NASA Ames Research Center Moffett Field, CA, United States)
Roychoudhury, Indranil (Stinger Ghaffarian Technologies, Inc. (SGT, Inc.) Moffett Field, CA, United States)
Date Acquired
August 27, 2013
Publication Date
September 23, 2012
Subject Category
Quality Assurance And Reliability
Report/Patent Number
ARC-E-DAA-TN5739
Meeting Information
Meeting: Annual Conference of the Prognostics and Health
Location: Minneapolis, MN
Country: United States
Start Date: September 23, 2012
End Date: September 27, 2012
Funding Number(s)
CONTRACT_GRANT: MCI-TIN2009-11326
WBS: WBS 534723.02.05.01
CONTRACT_GRANT: NNA08CG83C
Distribution Limits
Public
Copyright
Public Use Permitted.

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