Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis

Abstract

Fault diagnosis is crucial for repairing aircraft and ensuring their proper functioning. However, with the higher complexity of aircraft, some traditional diagnosis methods that rely on experience are becoming less effective. Therefore, this paper explores the construction and application of an aircraft fault knowledge graph to improve the efficiency of fault diagnosis for maintenance engineers. Firstly, this paper analyzes the knowledge elements required for aircraft fault diagnosis, and defines a schema layer of a fault knowledge graph. Secondly, with deep learning as the main method and heuristic rules as the auxiliary method, fault knowledge is extracted from structured and unstructured fault data, and a fault knowledge graph for a certain type of craft is constructed. Finally, a fault question-answering system based on a fault knowledge graph was developed, which can accurately answer questions from maintenance engineers. The practical implementation of our proposed methodology highlights how knowledge graphs provide an effective means of managing aircraft fault knowledge, ultimately assisting engineers in identifying fault roots accurately and quickly.

Fault Knowledge Graph Construction and Platform Development for Aircraft PHM

“…Additionally, Wu [ 29 ] utilized the BERT-BiLSTM-CRF algorithm for entity relationship extraction within the aero-engine lubrication system, subsequently constructing a fault knowledge graph for this system. Tang [ 30 ] employed deep learning as the primary method and heuristic rules as an auxiliary method to extract fault knowledge from both structured and unstructured fault data, leading to the construction of a fault knowledge graph for a specific type of process. Furthermore, Meng [ 31 , 32 ] presented a method for constructing a fault knowledge graph for aircraft power system health management and developed an intelligent Q&A system based on this knowledge graph, resulting in a significant enhancement of maintenance personnel’s troubleshooting abilities.…”

Application of Knowledge Graph Technology with Integrated Feature Data in Spacecraft Anomaly Detection

“…Since Google launched the knowledge graph-based search engine in 2012, the interest in constructing and applying domain-specific knowledge graphs across industries has grown significantly. Numerous studies have confirmed the substantial application value of knowledge graph technology in various industries like electric power equipment [19][20][21][22][23][24][25][26], network communication [27][28][29][30][31], and aerospace [32][33][34][35][36][37][38][39][40][41].…”