A Distributed Approach to System-Level Prognostics

Matthew Daigle, Anibal Bregon, and Indranil Roychoudhury
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_12_101.pdf607.37 KBSeptember 20, 2012 - 2:32pm

Prognostics, which deals with predicting remaining useful life of components, subsystems, and systems, is a key technology for systems health management that leads to improved safety and reliability with reduced costs. The prognostics problem is often approached from a component-centric view. However, in most cases, it is not specifically component lifetimes that are important, but, rather, the lifetimes of the systems in which these components reside. The system-level prognostics problem can be quite difficult due to the increased scale and scope of the prognostics problem and the relative lack of scalability and efficiency of typical prognostics approaches. In order to address these issues, we develop a distributed solution to the system-level prognostics problem, based on the concept of structural model decomposition. The system model is decomposed into independent submodels. Independent local prognostics subproblems are then formed based on these local submodels, resulting in a scalable, efficient, and flexible distributed approach to the system-level prognostics problem. We provide a formulation of the system-level prognostics problem and demonstrate the approach on a four-wheeled rover simulation testbed. The results show that the system-level prognostics problem can be accurately and efficiently solved in a distributed fashion.

Publication Year: 
2012
Publication Volume: 
3
Publication Control Number: 
101
Page Count: 
12
Submission Keywords: 
model-based prognostics
distributed prognostics
system-level prognostics
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
Submitted by: 
  
 
 
 

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