A Review of Knowledge Graph-based Research Methods for Fault Diagnosis of Special Vehicles

Chuanchao Su, Peng Hou, Feng Liu*, Xiaojian Yi

*Corresponding author for this work

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

Abstract

Fault diagnosis of special vehicles is crucial in ensuring their reliability and safety. Traditional fault diagnosis methods mainly include analytical model-based methods, signal-based methods, and knowledge-based methods. In contrast, knowledge-based methods are more suitable for the fault diagnosis of special vehicles due to their advantages in dealing with complex environments. This paper reviews knowledge-based fault diagnosis methods for special vehicles and their applications, and analyzes the challenges faced by traditional methods in practical applications. To overcome these challenges, a new idea of applying knowledge graph technology to the fault diagnosis of special vehicles is proposed. This paper also discusses the key technologies, challenges, and opportunities in knowledge graph construction, and introduces the recommended diagnosis methods based on knowledge graphs and their related challenges. Finally, based on the challenges faced by current research, this paper provides an outlook on future research directions, and points out the potential development trends and research focus areas based on knowledge graph technology in the field of special vehicle fault diagnosis.

Original languageEnglish
Title of host publication2024 6th International Conference on System Reliability and Safety Engineering, SRSE 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages272-281
Number of pages10
ISBN (Electronic)9798350356083
DOIs
Publication statusPublished - 2024
Event6th International Conference on System Reliability and Safety Engineering, SRSE 2024 - Hangzhou, China
Duration: 11 Oct 202414 Oct 2024

Publication series

Name2024 6th International Conference on System Reliability and Safety Engineering, SRSE 2024

Conference

Conference6th International Conference on System Reliability and Safety Engineering, SRSE 2024
Country/TerritoryChina
CityHangzhou
Period11/10/2414/10/24

Keywords

  • fault diagnosis
  • knowledge graph
  • recommendation methods
  • special vehicles

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