Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
