Knowledge-Based Fault Diagnosis of Technological Systems

Abstract

Fault diagnosis (FD) of man-made systems lies in the core of modern technology and attracts increasing attention by both theoreticians and practitioners. Actually, FD is one of the major concerns in industrial and other technological systems operation. In recent years a great deal of work has been done in the direction of designing systems (hardware and software) that are able to automatically diagnose the faults and malfunctions of an industrial process on the basis of observed data and symptoms. FD provides the prerequisites for fault tolerance, reliability and safety that are fundamental design features in any complex engineering system. Complex automatic industrial and other systems usually consist of hundreds of interdependent working parts which are individually subject to malfunction or failure. Total failure of these systems can present unacceptable economic loss or hazards to personnel or to the system itself. Hence, most modern systems involve: (i) a plan of maintenance which replaces worn parts before they malfunction or fail and (ii) a monitoring mechanism that detects a fault as it occurs, identifies the malfunction of a faulty component, and compensates for the fault of the component by substituting a configuration of redundant elements so that the system continues to operate satisfactorily. FD is actually this monitoring function and involves four subfunctions, namely detection, prediction, identification, and correction of faults during the on-line operation of the technological system at hand.