MODEL-BASED DIAGNOSIS USING DIRECTED GRAP H

This paper describes our approach to propose a model-based fault diagn ostic method using a directed graph. The model is composed of three su b-models : a failure propagation model, a component model and a state transition model. a failure propagation model represents causal relati onship among process variables. Here, a pressure low variable. a tempe rature high variable, and others are represented as nodes, and their c ausalities are represented as links. A component model represents comp onents: and pans structure of the target process. Each faulty status ! pipe clogged, pump failure, and so on! is represented as a node. A sta te transition model is introduced to represent different process opera tion phase like ''start-up'' and ''steady state.'' Each state is repre sented as a node. and their phase transition is represented as a link, The basic concepts of diagnostic algorithms are as follows: (1) input information on abnormal process variables (2) find primal failure cau ses (3) filter the result. In this paper, model components. modeling m ethod, and diagnostic algorithm are described. The software environmen t for the models is also discussed.