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Proceedings Paper

Model-based diagnosis of a carbon dioxide removal assembly
Author(s): David R. Throop; Ethan A. Scarl
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Paper Abstract

Model-based diagnosis (MBD) has been applied to a variety of mechanisms, but few of these have been in fluid flow domains. Important mechanism variables in these domains are continuous, and the mechanisms commonly contain complex recycle patterns. These properties violate some of the common assumptions for MBD. The CO2 removal assembly (CDRA) for the cabin atmosphere aboard NASA's Space Station Freedom is such a mechanism. Early work on diagnosing similar mechanisms showed that purely associative diagnostic systems could not adequately handle these mechanisms' frequent reconfigurations. This suggested a model-based approach and KATE was adapted to the domain. KATE is a constraint-based MBD shell. It has been successfully applied to liquid flow problems in handling liquid oxygen. However, that domain does not involve complex recycle streams, but the CDRA does. KATE had solved constraint sets by propagating parameter values through constraints; this method often fails on constraints sets which describe recycle systems. KATE was therefore extended to allow it to use external algebraic programs to solve its constraint sets. This paper describes the representational challenges involved in that extension, and describes adaptions which allowed KATE to work within the representational limitations imposed by those algebraic programs. It also presents preliminary results of the CDRA modeling.

Paper Details

Date Published: 1 March 1992
PDF: 11 pages
Proc. SPIE 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems, (1 March 1992); doi: 10.1117/12.56898
Show Author Affiliations
David R. Throop, Boeing Computer Services (United States)
Ethan A. Scarl, Boeing Computer Services (United States)

Published in SPIE Proceedings Vol. 1707:
Applications of Artificial Intelligence X: Knowledge-Based Systems
Gautam Biswas, Editor(s)

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