The kurtogram is a spectral analysis tool used to detect non-stationarities in a signal. It can be effectively used to determine the optimal filter for bearing fault feature extraction from a blurred vibration signal, since the transients of the bearing fault-induced signal can be regarded as non-stationary. However, the effectiveness of the kurtogram is diminished when the signal is collected from a bearing operating under time-varying speed conditions. There is a need to improve the performance of the kurtogram under time-varying speed conditions. In this paper, a short-time kurtogram method is proposed for bearing fault feature extraction under time-varying speed conditions. The performance of the short-time kurtogram is examined with experimental data. The results demonstrate that the short-time kurtogram can effectively be used to extract bearing fault features under time-varying speed conditions.

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