Tang, X.; Chi, G.; Cui, L.; Ip, A.W.H.; Yung, K.L.; Xie, X. Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis. Sensors2023, 23, 5295.
Tang, X.; Chi, G.; Cui, L.; Ip, A.W.H.; Yung, K.L.; Xie, X. Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis. Sensors 2023, 23, 5295.
Tang, X.; Chi, G.; Cui, L.; Ip, A.W.H.; Yung, K.L.; Xie, X. Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis. Sensors2023, 23, 5295.
Tang, X.; Chi, G.; Cui, L.; Ip, A.W.H.; Yung, K.L.; Xie, X. Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis. Sensors 2023, 23, 5295.
Abstract
When an aircraft malfunctions, quickly and accurately identifying the faulty unit is essential for ensuring normal operation. Unfortunately, maintenance engineers often struggle to acquire the necessary fault-related knowledge due to poor management and utilization of aircraft fault documents. To address this issue, we introduce knowledge graph technology into the field of aircraft fault diagnosis, exploring its construction and application for effective knowledge management. Our work starts by analyzing the critical knowledge elements required for aircraft fault diagnosis and designing a schema layer for fault knowledge graphs. We then we then combine deep learning and heuristic rules to extract fault knowledge from both structured and unstructured data, enabling the construction of aircraft fault knowledge graphs. Finally, we develop a fault question-answering system based on fault knowledge graphs that can accurately give solutions to questions posed by maintenance engineers. Our practice demonstrates that knowledge graphs provide an effective means of managing aircraft fault knowledge, assisting engineers in locating fault reasons accurately and quickly.
Keywords
Aircraft fault diagnosis; knowledge graph; deep learning; fault knowledge extraction; question-answering system
Subject
Engineering, Safety, Risk, Reliability and Quality
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.