PMC model fault analysis and artificial intelligence

Author

Prasad, Vinod B.

Author_Institution

Dept. of Electr. & Comput. Eng. Technol., Bradley Univ., Peoria, IL, USA

fYear

1989

fDate

14-16 Aug 1989

Firstpage

51

Abstract

If a system is composed of n independent processors, and if each processor tests a subset of other processors, it is possible to diagnose t of these processors which are permanently faulty. Using the concept of automated reasoning and making use of 2^t-1 subgraphs, it is shown that it is possible to identify the faulty and nonfaulty sets of processors. For a system designed for fault diagnosis, one has to find the number of subgraphs of the system based on the PMC model and write down the complete set of axioms. These axioms and the set of support will be good enough for the unique determination of the faulty and nonfaulty sets of processors

Keywords

artificial intelligence; fault tolerant computing; multiprocessing systems; PMC model; artificial intelligence; automated reasoning; fault diagnosis; faulty sets; independent processors; nonfaulty sets; subgraphs; Artificial intelligence; Assembly; Computer architecture; Failure analysis; Fault diagnosis; Information analysis; Logic testing; Power system modeling; Sufficient conditions; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1989., Proceedings of the 32nd Midwest Symposium on

Conference_Location

Champaign, IL

Type

conf

DOI

10.1109/MWSCAS.1989.101792

Filename

101792