Intelligent Diagnosis Method of Data Center Precision Air Conditioning Fault Based on Knowledge Graph

Abstract

This study first digitizes, rules and structures complex unstructured data such as massive historical operation and maintenance data and fault judgment experience of operation and maintenance engineering based on semi-automatic entity extraction method; annotate the association or indirect relationship between 63,724 types of faults among triads by means of decision trees. Bayesian algorithm is used to further explore the relationship between triples, the realizes knowledge fusion, knowledge reasoning and knowledge update, and completes knowledge graph construction; combines with fault intelligent diagnosis method, realizes fault prediction, fast discovery, locates fault, type and business impact reasoning, and provides solutions to assist decision making.