Applying model-based diagnostics to space power distribution

Todd M. Quinn; Richard F. Schlegelmilch

doi:10.1117/12.169395

1 March 1994 Applying model-based diagnostics to space power distribution

Todd M. Quinn, Richard F. Schlegelmilch

Proceedings Volume 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry; (1994) https://doi.org/10.1117/12.169395
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems which perform model-based diagnosis. A model-based diagnostic expert system for a Space Station Freedom electrical power distribution testbed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems, such as the testbed, as well. The expert system was developed using Marple and Lucid Common Lisp running on Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This paper describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.

Citation Download Citation

Todd M. Quinn and Richard F. Schlegelmilch "Applying model-based diagnostics to space power distribution", Proc. SPIE 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry, (1 March 1994); https://doi.org/10.1117/12.169395

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