Overview of the Application of Knowledge Graph in Anomaly Detection and Fault Diagnosis

Knowledge graph is a branch of artificial intelligence, which uses graph model to describe the relationship between knowledge and things. Using the technology of knowledge extraction, knowledge fusion and knowledge processing in knowledge graph, a large-scale knowledge base with semantic and open knowledge can be established quickly for a specific domain. Knowledge graph has gradually become an important means of knowledge management and application in various fields. This paper reviews the development history of knowledge graphs, introduces key technologies of knowledge graphs, and the application, rules and characteristics of knowledge graphs in anomaly detection and fault diagnosis. Furthermore, this paper summarizes the application of knowledge graph technology in anomaly detection and fault diagnosis in various industries, analyzes the applicability of knowledge graph in the field of anomaly detection and fault diagnosis, discusses the challenges faced in the application process, and proposes future development trends.