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

Peizheng Huang, Shulin Liu, Kuan Zhang, Tao Xu, Xiaojian Yi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2022 4th International Conference on System Reliability and Safety Engineering, SRSE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages207-213
Number of pages7
ISBN (Electronic)9781665473880
DOIs
Publication statusPublished - 2022
Event4th International Conference on System Reliability and Safety Engineering, SRSE 2022 - Guangzhou, China
Duration: 15 Dec 202218 Dec 2022

Publication series

Name2022 4th International Conference on System Reliability and Safety Engineering, SRSE 2022

Conference

Conference4th International Conference on System Reliability and Safety Engineering, SRSE 2022
Country/TerritoryChina
CityGuangzhou
Period15/12/2218/12/22

Keywords

  • anomaly detection
  • application
  • fault diagnosis
  • knowledge graph

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