Research on Data-Driven Fault Diagnosis of Aero-Engine Transmission Systems

In this brief paper, a data-based method on the fault diagnosis in aero-engine transmission systems is developed. Firstly, during the operation of splines, we acquire the acceleration vibration signal. We process the signal into time-frequency images using the short-time Fourier transform. Then, the...

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Bibliographic Details
Main Authors: Ma, Song, Yu, Xin-Meng, Sun, Tao, Zhao, Guang, Guo, Mei
Format: Conference Proceeding
Language:English
Subjects:
Aero-engines
artificial neural networks
Convolutional neural networks
Fault diagnosis
Fourier transforms
Neural networks
rotary machine
Splines (mathematics)
Time-frequency analysis
transmission systems
Vibrations
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Summary:In this brief paper, a data-based method on the fault diagnosis in aero-engine transmission systems is developed. Firstly, during the operation of splines, we acquire the acceleration vibration signal. We process the signal into time-frequency images using the short-time Fourier transform. Then, the improved convolutional neural network with channel attention is trained using time-frequency images of multiple fault signals. Finally, we implement fault prediction for spline wear and misalignment faults in aero-engine transmission systems. The result shows that the fault diagnosis using the proposed method has a high level of accuracy.
ISSN:2161-2927
DOI:10.23919/CCC58697.2023.10240229