基于VMD及广义分形维数矩阵的滚动轴承故障诊断

Bearing Fault Diagnosis Method Based on VMD and Generalized Fractal Dimension Matrix

提出基于变分模态分解及广义分形维数矩阵的滚动轴承故障诊断方法。对信号进行变分模态分解得到若干模态函数,根据不同权重因子计算得到每个模态函数的广义分形维数序列,排列构成广义分形维数矩阵,最后通过分析待测信号和各样本信号的广义分形维数矩阵的相关系数判断故障状态。实验结果表明该方法能精确、稳定提取故障特征,区分不同状态的信号。

A method of bearing fault diagnosis based on variational mode decomposition （VMD） and generalized fractal dimension was proposed. A number of mode functions were obtained through the decomposition to the signal by VMD method. Then the generalized fractal dimension of each mode functions were calculated according to the different weighting factors, and arranged to construct the generalized fractal dimension matrix. Finally, according to the correlation coefficient of the signals generalized fractal dimension matrix and the sample signals, the fault status could be diagnosed. The experiment results showed that the method could extract fault feature accurately and stably, and distinguish signals of different status and identify the faults with close frequency.