An Integrated Framework for Model-Based Distributed Diagnosis and Prognosis

Anibal Bregon, Matthew Daigle, and Indranil Roychoudhury
Submission Type: 
Full Paper
Supporting Agencies (optional): 
University of Valladolid; NASA Ames
AttachmentSizeTimestamp
phmc_12_137.pdf1.01 MBSeptember 20, 2012 - 3:42pm

Diagnosis 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.

Publication Year: 
2012
Publication Volume: 
3
Publication Control Number: 
137
Submission Keywords: 
distributed diagnosis; distributed prognosis; model decomposition
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
Submitted by: 
  
 
 
 

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