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Intelligent Fault Diagnosis for Multi-Device Systems Based on Rule Base and Knowledge Graph
ID：112 View Protection：ATTENDEE Updated Time：2025-11-10 15:36:39 Hits：100 Poster Presentation

Start Time：Pending（Asia/Shanghai）

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Abstract
In response to the complexities inherent in fault diagnosis for aerospace electromechanical multi-device systems, this paper proposes an intelligent diagnostic framework that integrates knowledge extraction, graph databases, and rule-based reasoning. The framework employs a large language model (LLM)-based knowledge extraction method to construct a fault rule knowledge graph and enable efficient inference. Experimental results demonstrate that the proposed approach significantly enhances both the accuracy and interpretability of fault diagnosis.
 
Keywords
knowledge graph, multi-device system, rule base, fault diagnosis.
Speaker
Zhang huiyun
Master Beihang university

Submission Author
Zhang huiyun Beihang university
Diyin Tang Beihang University (Beijing University of Aeronautics and Astronautics)
Wang Zihang Beihang university
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Important Date

  • Conference Date

    Nov 21

    2025

    to

    Nov 23

    2025

  • Oct 20 2025

    Draft paper submission deadline

  • Dec 08 2025

    Registration deadline

Sponsored By
IEEE Instrumentation and Measurement Society
South China University of Technology
Organized By
South China University of Technology
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