Formulating Event-Based Critical Observations in Diagnostic Problems

Abstract

We claim that in scenarios involving a human operator with responsibility over systems being monitored by diagnoser, presenting said operator with a concise set of observations capturing the essence of a failure improves the operator’s understanding of the diagnosis. We take this in the context of Discrete Event Systems and demonstrate how the idea can be applied to systems utilising event-based observations, which can contain implicit information. We introduce the notion of an abstracted event stream, called a sub-observation, that makes the implicit information explicit for the operator and allows a diagnoser to arrive at the same diagnosis. We call the most abstract of these the critical observation. We provide relevant definitions, properties, and a procedure for computing the critical observation in a diagnosis problem