Improved Time-Frequency Representation for Non-stationary Vibrations of Slow Rotating Machinery

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Published Jun 29, 2022
Cédric Peeters Andreas Jakobsson Jérôme Antoni Jan Helsen

Abstract

The short-time Fourier transform (STFT) is a staple analysis tool for vibration signal processing due to it being a robust, non-parametric, and computationally efficient technique to analyze non-stationary signals. However, despite these beneficial properties, the STFT suffers from high variance, high sidelobes, and a low resolution. This paper investigates an alternative non-parametric method, namely the sliding-window iterative adaptive approach, to use for time-frequency representations of non-stationary vibrations. This method reduces the sidelobe levels and allows for high resolution estimates. The performance of the method is evaluated on both simulated and experimental vibration data of slow rotating machinery such as a multi-megawatt wind turbine gearbox. The results indicate significant benefits as compared to the STFT with regard to accuracy, readability, and versatility.

How to Cite

Peeters, C. ., Jakobsson, A. ., Antoni, J. ., & Helsen, J. . (2022). Improved Time-Frequency Representation for Non-stationary Vibrations of Slow Rotating Machinery. PHM Society European Conference, 7(1), 401–409. https://doi.org/10.36001/phme.2022.v7i1.3363
Abstract 130 | PDF Downloads 114

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Keywords

Signal processing, Short-time Fourier transform, Non-stationary signals, Non-parametric method, Wind turbine gearbox

Section
Technical Papers