A Data-based Expert System for Aero-Engine Gas Path Fault Diagnosis

被引:1
|
作者
Sun, Ang [1 ]
Guo, Di [2 ]
Wang, Rui [1 ]
机构
[1] Dalian Univ Technol, Sch Aeronaut & Astronaut, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
基金
中国国家自然科学基金;
关键词
Aero-engine; Wavelet Transform; LSTM Timeseries Prediction; Rough Set Attribute Reduction;
D O I
10.1109/CCDC52312.2021.9601806
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In response to the daily maintenance and repair requirements of domestic military aviation engines, a data-based expert system for aero-engine gas path fault diagnosis is proposed. The system is dedicated to the unified management and processing of flight data of various types of domestic engines. In addition to the basic functions of the general aero-engine condition monitoring system, the system has also done in-depth research on issues such as aero-engine parameter denoising, aero-engine parameter prediction, and automatic acquisition of expert knowledge base. Additionally, wavelet domain denoising, LSTM network prediction and rough set attribute reduction are investigated and applied in the proposed system. Finally, the normalized real flight data is applied to simulation verification, and good denizations and prediction results are obtained.
引用
收藏
页码:2917 / 2922
页数:6
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