基于子频带谱峭度平均的快速谱峭度图算法改进

快速谱峭度图(Fast Kurtogram)算法具有能自适应选取共振解调频带并实现包络解调提取的优点,在滚动轴承包络分析中有广阔的应用前景,但其在实际应用中,若被采集信号中包含有较高峰值的脉冲干扰时,将可能导致谱峭度图的自适应共振带确定失效,最终导致无法获得包含有效滚动轴承的故障特征信息的包络信号。为解决快速谱峭度图算法的上述不稳定问题,本文提出了一种基于子频带谱峭度平均的改进快速谱峭度图算法,其可有效消除或削弱脉冲干扰成分对谱峭度图结果的影响,提高了共振解调频带确定的鲁棒性,实现了基于快速谱峭度图算法的滚动轴承故障特征准确提取。仿真和试验结果验证了本方法的有效性。

Improvement on Fast Kurtogram Algorithm by Sub-frequency-band Average

The fast kurtogram algorithm has the advantages of choosing resonance demodulation frequency band adaptively and realizing the envelope demodulation extraction and has broad application prospects in the rolling bearing envelope analysis. But in the fast kurtogram calculation, if there is a high peak pulse interference in the  vibration signal, the fast kurtogram calculation can not able to get the adaptive resonance frequency band, eventually the envelope extraction can not effective for rolling bearing fault characteristic information. In order to solve the problem of fast kurtogram algorithm with instability, an improvement fast kurtogram based on the average of sub-band spectral kurtosis has been presented in the paper. The method can effectively eliminate or weaken the influence of pulse interference on the result of fast kurtogram, and improve the robustness of the algorithm and the stability of the frequency band selection for resonant demodulation. The fast kurtogram based on the average of sub-band spectral kurtosis can extract the rolling bearing fault feature accurately. Simulation and experimental results verify the effectiveness of this method.