Design and Implementation of IT Health Diagnosis System Based on Knowledge Graph and Artificial Intelligence Technology

This paper proposes a knowledge modeling and analysis method of IT equipment health management based on knowledge graph. The ontology framework of maintenance knowledge map is constructed according to entity relationship model. Then this paper integrated knowledge graph, text classification, Bayesian network and other technologies applied to IT equipment fault knowledge management, fault location, fault diagnosis reasoning. At the same time, based on the actual maintenance work order data of IT enterprises, good practice results have been obtained from the aspects of statistical analysis and correlation analysis. The relational database (RDB) data is converted into Resource Description Framework (RDF) quadruple for storage. Visual analysis and management of knowledge graph are realized. This study shows that the integrated approach provides effective guidance for IT equipment fault knowledge management and diagnosis practice. The research results of this paper can provide decision support for maintenance personnel and management personnel to carry out equipment health management.