Joint Knowledge Graph and Large Language Model for Fault Diagnosis and Its Application in Aviation Assembly-Reference-Cited by-同舟云学术

Joint Knowledge Graph and Large Language Model for Fault Diagnosis and Its Application in Aviation Assembly

Published:2024-06 Issue:6 Volume:20 Page:8160-8169
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

LIU Peifeng¹^ORCID,Qian Lu²^ORCID,Zhao Xingwei¹^ORCID,Tao Bo¹^ORCID

Affiliation:

1. State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Department of Mechanical, Huazhong University of Science and Technology, Wuhan, China

2. School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9424/10550081/10463190.pdf?arnumber=10463190

Reference30 articles.

1. Mobile-robotic machining for large complex components: A review study

2. A Robust Data-Driven Fault Detection Approach for Rolling Mills With Unknown Roll Eccentricity

3. The joint knowledge reasoning model based on knowledge representation learning for aviation assembly domain

4. A Survey on Knowledge Graphs: Representation, Acquisition, and Applications

5. Domain Knowledge-Based Deep-Broad Learning Framework for Fault Diagnosis

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