Volterra理论在滚动轴承内圈故障程度特征定量提取的研究

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振动与冲击 ›› 2018, Vol. 37 ›› Issue (9) : 173-179.

论文

王海涛，王琨，史丽晨

作者信息 +

Quantitative extraction of rolling bearings’ inner race fault level based on Volterra theory

WANG Haitao WANG Kun SHI Lichen

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文章历史 +

摘要

针对滚动轴承内圈不同损伤程度的特征提取问题，提出一种基于Volterra核函数理论和双谱分析相结合的故障特征定量提取方法。该方法首先利用系统输入输出振动信号确定Volterra模型；其次通过改进的多脉冲激励法对模型的Volterra核函数进行求解，并利用广义频率响应函数(GFRF)进行模型辨识；最后利用双谱及其切片谱图手段，分离并且量化提取二阶核函数中由于相位耦合所隐含的故障程度特征信息。利用滚动轴承试验台采集数据，对此分析方法进行实验验证，并与包络谱分析进行了对比。结果表明：在无明显冲击振动的情况下，利用双谱切片方法可以直观地对Volterra二阶核函数进行量化表述，并且能够有效地将正常轴承和不同损伤程度的内圈故障轴承进行区分。

Abstract

To extract effectively features of different damage levels on rolling bearings’ inner race, a method of quantitative fault feature extraction based on the combination of Volterra kernel function theory and bi-spectral analysis was proposed. Firstly, input signals and output ones of a system were used to determine a Volterra model. Secondly, Volterra kernel function of the model was solved with the improved multi-pulse excitation method. The model was identified using the generalized frequency response function (GFRF). Finally, using the means of bi-spectrum and its slices, the information of damage level features implied in the second order kernel function due to phase coupling was separated, quantized and extracted. A rolling bearing test table was used to collect faulty bearings’ data to verify the proposed analysis method. The results were compared with those using the envelope spectral analysis method. The results showed that the bi-spectral slice method can be used to intuitively and quantitatively express the information implied in Volterra second order kernel function when there are not obvious shock vibration, and effectively distinguish normal bearings and faulty bearings with different inner race damage levels.

导出引用

王海涛，王琨，史丽晨. Volterra理论在滚动轴承内圈故障程度特征定量提取的研究[J]. 振动与冲击, 2018, 37(9): 173-179

WANG Haitao WANG Kun SHI Lichen. Quantitative extraction of rolling bearings’ inner race fault level based on Volterra theory[J]. Journal of Vibration and Shock, 2018, 37(9): 173-179

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