Diagnostic tree design with model-based reasoning

Abstract

A reasoning procedure using quantitative models of connectivity and function has been developed to generate automatically multibranched diagnostic trees which can isolate faults within feedback loops and in the presence of multiple faults. The authors describe how the model-based reasoning system is used to generate automatically diagnostic trees that can have variable degrees of branching, from binary to ternary (nodes with high, OK, and low branches) to n-ary trees. With branching degrees at or above ternary, these trees are capable of fault isolating within loops and can in fact isolate multiple faults. The trees can utilize much of the information content in quantitative measurements to make efficient and accurate diagnoses not possible with the binary tree. Both efficiency and accuracy of diagnosis increase with the branching factor of the tree. Automated tree generation provides effective automated diagnostics to applications requiring low-cost hardware and fast response time.<>