Abstract
Sparse fast Fourier transform is a new spectrum analysis method based on signal sparse characteristics in recent years. Sparse fast Fourier transform can quickly and accurately process large data by identifying and discarding frequency signals that have no effect on the analysis results. In order to explore the practicality of Sparse fast Fourier transform in aero-engine vibration data analysis, this paper combines the actual flight test vibration data, and studies the sparse fast Fourier transform method and the traditional fast Fourier transform method in terms of spectral characteristics, running time, algorithm stability. By comparison, it can be found that the sparse fast Fourier transform algorithm can greatly improve the efficiency of vibration data analysis while ensuring accuracy.
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