Abstract:
Chemical processes are systems that include complicated networks of material, energy and signal flow. As time passes, the performance of chemical process equipment gradually degrades due to deterioration of process components. In addition, ambient disturbances endanger the process upsets. Both factors lead to values of process variables at variance with those expected under normal operating conditions. Early detection and diagnosis of process faults while the process is still operating in a controllable region can help avoid normal event progression and reduce productivity. Hence fault detection and diagnosis is an important problem with respect to safety and productivity in process engineering.
Over the last decade an extensive search has been carried out in the area of Intelligent Control. Emerging technologies such as Fuzzy Logic have received much attention in the control area. In recent years Fuzzy logic has emerged as a mathematical tool to deal with faults in the process at incipient stage. It also provides a frame work for an inference mechanism that allows for approximate human reasoning capabilities to be applied to knowledge based systems. This technique has been claimed to yield excellent results for some applications.
The distillation column is probably the most popular and important process studied in chemical engineering literature, it is usually controlled by conventional proportional integrative derivative (PID) controller. The project "Intelligent Control Application for Industrial Process Safety" proposes application of Fuzzy Logic in Fault detection and diagnosis for distillation column safety.
