Diagnosing Multiple Faults using Multiple Context Spaces


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 4, No. 1, pp. 137-148, Jan. 1997
10.3745/KIPSTE.1997.4.1.137,   PDF Download:

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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Cite this article
[IEEE Style]
L. G. Sung and K. K. Hee, "Diagnosing Multiple Faults using Multiple Context Spaces," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 4, no. 1, pp. 137-148, 1997. DOI: 10.3745/KIPSTE.1997.4.1.137.

[ACM Style]
Lee Gye Sung and Kwon Kyung Hee. 1997. Diagnosing Multiple Faults using Multiple Context Spaces. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 4, 1, (1997), 137-148. DOI: 10.3745/KIPSTE.1997.4.1.137.