Volterra核函数法在轴承滚珠磨损中的特征提取及应用
发布时间：2018-07-31 14:56
【摘要】：针对滚动轴承滚珠磨损故障特征难以提取的问题,提出一种基于多脉冲激励法下的Volterra级数核的求解算法.该方法是一种非线性系统模型的"交叉"诊断法,利用轴承系统输入输出的采样信号,建立Volterra非线性辨识系统模型,并运用多脉冲激励Volterra低阶核求解算法,将得到的低阶核通过时域和频域进行对比来判断轴承当前所处的运行状态.该文以无心车床主轴轴承为例进行实验验证,并与传统的小波分析法对比得出:多脉冲激励法能够方便准确地提取轴承的故障特征,该方法对此类故障的诊断具有一定的借鉴意义.
[Abstract]:In order to solve the problem that the ball wear fault feature of rolling bearing is difficult to extract, a solution algorithm of Volterra series kernel based on multi-pulse excitation method is proposed. This method is a "cross" diagnosis method for nonlinear system model. The Volterra nonlinear identification system model is established by using the input and output sampling signals of the bearing system, and the low order kernel solution algorithm of multi-pulse excitation Volterra is used. The low order kernels are compared in time domain and frequency domain to determine the current operating state of the bearing. This paper takes the spindle bearing of the centerless lathe as an example, and compares it with the traditional wavelet analysis method. It is concluded that the multi-pulse excitation method can extract the fault characteristics of the bearing conveniently and accurately. This method can be used for reference in the diagnosis of this kind of fault.
【作者单位】： 西安建筑科技大学机电工程学院;
【基金】：国家自然科学基金青年科学基金(51105292)~~
【分类号】：TH133.33
本文编号：2155941
[Abstract]:In order to solve the problem that the ball wear fault feature of rolling bearing is difficult to extract, a solution algorithm of Volterra series kernel based on multi-pulse excitation method is proposed. This method is a "cross" diagnosis method for nonlinear system model. The Volterra nonlinear identification system model is established by using the input and output sampling signals of the bearing system, and the low order kernel solution algorithm of multi-pulse excitation Volterra is used. The low order kernels are compared in time domain and frequency domain to determine the current operating state of the bearing. This paper takes the spindle bearing of the centerless lathe as an example, and compares it with the traditional wavelet analysis method. It is concluded that the multi-pulse excitation method can extract the fault characteristics of the bearing conveniently and accurately. This method can be used for reference in the diagnosis of this kind of fault.
【作者单位】： 西安建筑科技大学机电工程学院;
【基金】：国家自然科学基金青年科学基金(51105292)~~
【分类号】：TH133.33
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