A fuzzy diagnosis method in process systems with feedback control loops

By considering the fault propagation behaviors in process systems with control loops, a fuzzy-logic based fault diagnosis strategy has been developed in the present work. The proposed fault diagnosis methods can be implemented in two stages. In the off-line preparation stage, the potential causes of a system hazard are identified by deterrnining the minimal cut sets of a fault tree. The occurrence order of observable fault symptoms is derived frorn the system digraph and then encoded into a set of IF-THEN rules. In the next on-line diagnosis stage, the occurrence indices of the top event and also the fault origins are computed in a fuzzy inference system based on real-time measurement data. Simulation studies have been carried out to demonstrate the feasibility of the proposed approach.