@inproceedings{896705a3db554f4d9740874584302730,
title = "Intelligent Fault Diagnosis for Multi-Device Systems Based on Rule Base and Knowledge Graph",
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 rulebased 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 = "fault diagnosis, knowledge graph, multi-device system, rule base",
author = "Huiyun Zhang and Diyin Tang and Zihang Wang",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 6th International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2025 ; Conference date: 21-11-2025 Through 23-11-2025",
year = "2025",
doi = "10.1109/ICSMD67131.2025.11365318",
language = "英语",
series = "ICSMD 2025 - International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICSMD 2025 - International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence",
address = "美国",
}