- Abstract:
-
Fault Identification is a search for possible behaviours that would explain the observed behaviour of a physical system. During this search different possible models are considered and information about the interaction between possible behaviours is derived. Much of this potentially useful information is generally ignored in conventional pure symbolic approaches to fault diagnosis, however. A novel approach is presented in this paper that exploits uncertain information on the behavioural description of system components to identify possible fault behaviours in physical systems. The work utilises the standard conflict recognition technique developed in the framework of the General Diagnostic Engine (GDE) to support diagnostic inference through the production of both rewarding and penalising evidence. In particular Markow matrices are derived from the given evidence, thereby enabling the use of Markov Chains to implement the diagnostic process. This work has resulted in a technique, which maximises the use of derived information, for identifying candidates for multiple faults that is demonstrated to be very effective.
- Copyright:
- 2004 by The University of Edinburgh. All Rights Reserved
- Links To Paper
- No links available
- Bibtex format
- @Misc{EDI-INF-RR-0203,
- author = {
Finlay Smith
and Qiang Shen
},
- title = {Fault Identification through the Combination of Symbolic Conflict Recognition and Markov Chain-aided Belief Revision},
- year = 2004,
- month = {Mar},
- }
|