A Highly Accurate Method for Forecasting Aero-Engine Vibration Levels Based on an Enhanced ConvNeXt Model

被引:0
|
作者
Kuang, Dian [1 ]
Zhan, Yuyou [2 ]
Tan, Yan [3 ]
Gou, Yi [2 ]
Wu, Wenqing [2 ]
机构
[1] Civil Aviat Flight Univ China, Engn Tech Training Ctr, Guanghan 618300, Peoples R China
[2] Civil Aviat Flight Univ China, Coll Aeronaut Engn, Guanghan 618300, Peoples R China
[3] Civil Aviat Flight Univ China, Aeroengine Ctr, Guanghan, Peoples R China
关键词
Vibrations; Aircraft propulsion; Atmospheric modeling; Predictive models; Forecasting; Aircraft; Turbines; Deep learning; Aero-engine; vibration; vibration forecast; data driven; deep learning; DUAL-ROTOR; FAULTS;
D O I
10.1109/ACCESS.2022.3225925
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Vibrations are like the heartbeat of an aero-engine. In order to better understand the pulse pattern of aero-engines, we must look deep into its nature. Instead of choosing mature themes for research such as bearing vibration fault diagnosis and fault classification, this paper creatively explores vibration forecast, a subject that is hardly ever brought up in the aero-engine field. Meanwhile, an enhanced ConvNeXt model using a sliding window mechanism, which is a highly accurate forecasting method, is proposed. On the basis of using real flight datasets gathered by aircraft acquisition systems, this powerful method can track and forecast the vibration of aero-engines very precisely in a specific condition. Due to the complexity of aero-engine vibration, our method uses the sliding window to add future information on non-target parameters in order to increase the prediction accuracy of the target parameters. In some cases, forecasted values are almost identical to true values. The application of this innovative method on various vibration parameters has also been tested, in addition to its applicability to various types of aero-engines being confirmed. Finally, experiments on noise immunity and several aero-engine states involving the transition state and the steady state are conducted to strengthen the plausibility and credibility of our theories.
引用
收藏
页码:126039 / 126051
页数:13
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