Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

Matthew Daigle, Anibal Bregon, and Indranil Roychoudhury
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_11_029.pdf640.15 KBAugust 18, 2011 - 2:06pm

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components that include how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Publication Year: 
2011
Publication Volume: 
2
Publication Control Number: 
029
Submission Keywords: 
model-based prognostics
distributed prognostics
particle filters
centrifugal pump
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
Modeling and simulation
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