Systematic Development of Automata Generated Languages for Fault Diagnosis in Continuous Chemical Processes

AbstractA SDG-based simulation procedure is presented in this study to qualitatively predict all possible effects of one or more fault propagating in a given process system. All possible state evolution behaviors are characterized with an automaton model. By selecting a set of on-line sensors, the corresponding diagnoser can be constructed and the diagnosability of every fault origin can be determined accordingly. Furthermore, it is also possible to construct a formal diagnostic language on the basis of this diagnoser. Every string (word) in the language is then encoded into an IF-THEN rule and, consequently, a comprehensive fuzzy inference system can be synthesized for on-line diagnosis. The feasibility of this approach is demonstrated with a simple example in this paper.