Expert diagnostic using qualitative data and rule-based inferential reasoning

Abstract

A diagnostic structure based on modular expert system architecture is presented in this paper. An illustrative example shows how expert knowledge is used to deduce fault situations. In this example, qualitative representation of numerical variables of process is used to interface expert knowledge and process variables. The goal is to use this new information to deduce abnormal situations that can not be differentiate from the normal evolution of process dynamics using only data available from process. The evolution of process variables and abstracted information are used as inputs for the reasoning modules.