On-line hazard aversion and fault diagnosis in chemical processes: the digraph+fault-tree method

A method for online hazard aversion and fault diagnosis in chemical processes is developed. The method uses a directed graph model of process operation and control. Fault trees developed from the directed graphs are combined with real-time data to provide online diagnosis for hazard aversion and fault detection. Both hardwired control and manual control are modeled. A single control loop illustrates the modeling technique and the diagnosis method. The method provides an advance alert to process problems and an identification of the problems´ causes, based on the available real-time data and prior rates of equipment malfunctions and process disturbances