Ontology Construction of Fault Diagnosis Knowledge Graph for Civil Aircraft Maintenance

Maintenance of civil aircraft systems is crucial for ensuring air travel safety. However, managing a large volume of maintenance data can lead to inefficiencies in operation support work. Knowledge graphs are utilized to visualize maintenance manuals and historical fault diagnosis records. Therefore, this paper presents a novel ontology construction approach for fault diagnosis knowledge graphs in civil aircraft maintenance, focusing on event domain, fault domain, and product domain. The ontology construction process follows the “ontology seven-step method.” Finally, several applications, including information retrieval, intelligent question answering, and optimal route recommendation, are implemented using this knowledge graph.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1109/phm-beijing63284.2024.10874688
Primary Topic
Advanced Computational Techniques and Applications
Type
article
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Ontology Construction of Fault Diagnosis Knowledge Graph for Civil Aircraft Maintenance

Ke Sun, Qingqian Zhou, Huanchun Peng, Yuanxiang Li et al.
Advanced Computational Techniques and Applications
article

Ontology Construction of Fault Diagnosis Knowledge Graph for Civil Aircraft Maintenance

Ke Sun, Qingqian Zhou, Huanchun Peng, Yuanxiang Li, Yini Zhang, Weidong Yang
article en

Abstract

Maintenance of civil aircraft systems is crucial for ensuring air travel safety. However, managing a large volume of maintenance data can lead to inefficiencies in operation support work. Knowledge graphs are utilized to visualize maintenance manuals and historical fault diagnosis records. Therefore, this paper presents a novel ontology construction approach for fault diagnosis knowledge graphs in civil aircraft maintenance, focusing on event domain, fault domain, and product domain. The ontology construction process follows the “ontology seven-step method.” Finally, several applications, including information retrieval, intelligent question answering, and optimal route recommendation, are implemented using this knowledge graph.

Commercial Aircraft Corporation of China (China) (CN), Shanghai Jiao Tong University (CN), Fudan University (CN), Nanjing University of Aeronautics and Astronautics (CN)
Openalex Percentile: Top 75%
Advanced Computational Techniques and Applications
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