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Intelligent Auxiliary Fault Diagnosis for Aircraft Using Knowledge Graph by Xilang Tang; Bin Hu; Jianhao Wang; Chuang Wu; Sohail M. Noman is a book available to read on EtoBox.

What is Intelligent Auxiliary Fault Diagnosis for Aircraft Using Knowledge Graph about?

This paper proposes a new intelligent auxiliary diagnosis method based on knowledge graph which helps grass-roots maintenance engineers to quickly and accurately locate the fault unit of aircraft. Firstly, aircraft fault knowledge graph is extracted from fault text data by using machine learning. Secondly, knowledge representation learning method is used to mapping fault knowledge graph into dense low-dimensional real-value vectors. Finally, the fault knowledge related to fault phenomena is extracted by the method of cosine similarity. ## Introduction Nowadays, fault diagnosis of aircraft becomes more and more difficult since the function and structure of aircraft are becoming more and more complex. Therefore, the "intelligent auxiliary diagnosis system" can generate diagnosis strategy and guide the maintenance engineers to take appropriate test steps to quickly and accurately locate the fault unit. To construct the intelligent auxiliary diagnosis system, the basic knowledge base, including aircraft hierarchical structure, function and connection relationship of units, observable signal parameters, potential fault risk, available test means and so on, is necessary [1]. By using kno

Author

Xilang Tang; Bin Hu; Jianhao Wang; Chuang Wu; Sohail M. Noman

Publisher

Springer Singapore Pte. Limited; Springer

Published

2022

Language

EN

ISBN

9789811697340

Subjects

Engineering, Stem