Multiple fault diagnosis using multiple context spaces

Gyesung Lee; Gautam Biswas

doi:10.1117/12.21057

1 January 1990 Multiple fault diagnosis using multiple context spaces

Gyesung Lee, Gautam Biswas

Author Affiliations +

Proceedings Volume 1293, Applications of Artificial Intelligence VIII; (1990) https://doi.org/10.1117/12.21057
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

Diagnostic problem solving is a major application area of knowledge-based system research. However, most of the current approaches, both heuristic and model-based, are designed to identify single faults, and do not generalize easily to multiple fault diagnosis without exhibiting exponential behavior in the amount of computation required. In this paper, we employ a decomposition approach based on system configuration to generate an efficient algorithm for multiple fault diagnosis. The basic idea of the algorithm is to reduce the inherent combinatorial explosion that occurs in generating multiple faults by partitioning the circuit into groups that correspond to output measurement points. Rules are developed for combining candidates from individual groups, and forming consistent sets of minimal candidates.

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Gyesung Lee and Gautam Biswas "Multiple fault diagnosis using multiple context spaces", Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); https://doi.org/10.1117/12.21057

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