Challenges in the industrial applications of fault diagnostic systems

Abstract

Process fault diagnosis (PFD) involves interpreting the current status of the plant given sensor readings and process knowledge. Early diagnosis of process faults while the plant is still operating in a controllable region can help avoid event progression and reduce the amount of productivity loss during an abnormal event. PFD forms the first step in abnormal situation management (ASM), which aims at timely detection, diagnosis and correction of abnormal conditions. However the problem of PFD is made considerably difficult by the scale and complexity of modern plants. We briefly outline the various challenges in the area of PFD and review the existing methods to tackle them. We argue that a hybrid blackboard-based framework utilizing collective problem solving is the most promising approach. The efforts of the ASM consortium in pursuing the implementation of the state-of-the-art technologies at plant sites are also described.