基于大模型与知识图谱协同推理设备故障诊断系统及方法
The equipment fault diagnosis system, which uses large models and knowledge graphs for collaborative reasoning, enables multi-dimensional analysis and prediction of equipment faults. It solves the problem of passive response in equipment fault diagnosis in existing technologies and improves fault handling efficiency and equipment operation stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN RES INST FOR WATER TRANSPORT ENG M O T
- Filing Date
- 2026-04-24
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies lack intelligent analysis of potential equipment failures throughout their entire lifecycle, making it impossible to upgrade from passive response to proactive prevention in equipment fault diagnosis.
A fault diagnosis system based on large model and knowledge graph collaborative reasoning is adopted. Through the layered design of data layer, knowledge layer, model layer, application layer and digital twin simulation verification layer, combined with graph neural network and Bayesian fault prediction model, the system realizes multi-dimensional analysis and prediction of equipment faults.
It enables rapid location, accurate analysis, and early detection of potential equipment faults, improving fault handling efficiency and equipment operation stability, reducing operation and maintenance costs, and is suitable for high-frequency data monitoring scenarios in industrial production and large equipment.
Smart Images
Figure CN122087674B_ABST