Multiple Hierarchical Reasoning in Uncertain Situations for Complex Device Fault Diagnosis

Abstract

An efficient diagnostic method is proposed for complex device fault diagnosis. In rule-based reasoning, an efficient retrieving strategy is crucial. The generic retrieving method is based on a diagnostic tree built according to the hierarchical decomposition of devices, but it is difficult to achieve such diagnostic tree for some complex devices. So a multiple hierarchical diagnosis method based on fault categories is proposed. And then, the retrieving priorities of rules in a certain diagnostic level are determined based on a fuzzy multi-attribute group decision-making method, which can more effectively work out the priority factors. Based on this diagnostic method, a fault diagnosis system for intelligent instruments was developed based on SQL2005 database. And comparison between two systems is presented to validate the diagnostic method.