Diagnostic Algorithms Based on Multilevel Flow Models

Human error is a common source of accidents in complex plants. We believe that many human errors really are caused by lack of intelligence in the instrumentation and control systems, putting the operators in situations, which humans realistically cannot be expected to cope with. Through history, several computer-based algorithms have been proposed and used for automated sensor fault detection, alarm analysis, and fault diagnosis, to support human operators. The main problem with such algorithms is that they demand a large effort to build, validate, and especially rebuild when the plant is changed. We propose the use of algorithms based on Multilevel Flow Models (MFM), which are graphical models of goal