Abstract
This paper described a fault diagnosis expert system based on Possible Cause and Effect Graph methodology which is an enhanced Signed Digraph approach. This expert system incorporated Bayesian belief theorem and explanation capacity. Causal relationships in single loop and cascade controllers were remodeled to suit the implementation. In dealing with recycle loops between process variables, a knowledge-base containing roles was employed to “break” the cyclic loop dynamically. During the diagnosis phase, the system dynamically modifies the causal network and adjusts the conditional probability using all available plant information and other processing techniques such as data reconciliation. This expert system has been implemented successfully on a pilot scale distillation column, with very promising results.
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