Intelligent Fault Diagnosis for Multi-Device Systems Based on Rule Base and Knowledge Graph

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.