Neural networks applied for the identification and fault diagnosis of process valves and actuators

This paper is concerned with the instrumentation and technology of fault detection and isolation (FDI) in process valves and actuators. A classification of faults in process valves and actuators is followed by a brief review of EDI techniques. Artificial neural networks (ANNs) are classified and introduced as an effective way of modelling valves and actuators, which are severely nonlinear components. Experimental results obtained from tests conducted on a double acting, twin piston rack-and-pinion actuator, are presented.