Robust diagnostic system: structural redundancy approach

Amit Misra; Janos Sztipanovitz; James Ray Carnes

doi:10.1117/12.169399

1 March 1994 Robust diagnostic system: structural redundancy approach

Amit Misra, Janos Sztipanovitz, James Ray Carnes

Proceedings Volume 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry; (1994) https://doi.org/10.1117/12.169399
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

We have developed and field tested a real-time robust diagnostic system, which uses hierarchical, multiple-aspect models of plants. The models include the functional structure, timed failure propagation graphs, physical component structure, and component failure modes. The diagnostic reasoning applies structural and temporal constraints for the generation and validation of fault hypotheses using the `predictor-corrector' principle. The diagnosis is generated in real time, amid an evolving alarm scenario, and uses progressive deepening control strategy. The robust diagnostic system has been tested and demonstrated using ECLSS models obtained from the Boeing Company.

Citation Download Citation

Amit Misra, Janos Sztipanovitz, and James Ray Carnes "Robust diagnostic system: structural redundancy approach", Proc. SPIE 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry, (1 March 1994); https://doi.org/10.1117/12.169399

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