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

Abstract

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.