A Model-Based Approach to On-Line Process Disturbance Management: The Models.

Abstract

A methodology is proposed which can be used to design real-time expert systems for on-line process disturbance management. This methodology encompasses diverse functional aspects that are required for an effective process disturbance management: 1) intelligent process monitoring and alarming, 2) on-line sensor data validation and sensor conflict resolution, 3) on-line hardware failure diagnosis, and 4) real-time corrective measure synthesis. Accomplishment of these functions is made possible through the integrated application of the various models, goal- tree success-tree, process monitor tree, sensor failure diagnosis, and hardware failure diagnosis models. This paper presents and discusses the various models along with the overall algorithm of the methodology. The application of the methodology to a target process, a typical main feedwater system of a nuclear power plant which employs a complex control mechanism, will be presented in a companion paper.