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Fault diagnosis for rolling bearing based on improved enhanced kurtogram method

机译:基于改进型增强型图谱法的滚动轴承故障诊断

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In order to extract the fault features of rolling bearing effectively, a new improved enhanced kurtogram method is proposed. Improved enhanced kurtogram is calculated based on harmonic wavelet packet composition and the node whose kurtosis value is maximum is selected after calculating the improved enhanced kurtogram of the original fault signal, then reconstruct the signal through the harmonic wavelet packet coefficient of the optimal node, the rolling bearing fault type could be judged by analyzing the envelope spectrum of the reconstructed signal. The comparison of the proposed method with the original kurtogram method and the enhanced kurtogram method are conducted to analyze the experimental signal of rolling bearing. The results show that the new method proposed in this paper could select the resonance frequency band precisely and could be applied effectively on fault diagnosis for rolling bearing.
机译:为了有效地提取滚动轴承的故障特征,提出了一种新的改进的增强型峰度图方法。根据谐波小波包组成计算​​改进的增强型峰图,计算原始故障信号的改进的增强型峰图后,选择峰度值最大的节点,然后通过最优节点的谐波小波包系数重构信号,滚动可以通过分析重构信号的包络谱来判断轴承的故障类型。将所提出的方法与原始峰度图方法和增强型峰度图方法进行了比较,以分析滚动轴承的实验信号。结果表明,本文提出的新方法能够精确选择共振频段,可有效地应用于滚动轴承的故障诊断。

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