基于全矢Autogram的滚动轴承故障诊断方法

Full Vector Autogram Based Fault Diagnosis Method for Rolling Bearing

针对滚动轴承单通道信号信噪比较低、不能全面和准确表征故障特征等问题,提出了一种基于全矢谱和自相关谱峭度图的滚动轴承故障诊断方法。首先,计算互为垂直的两通道振动信号的自相关谱峭度图,得到信号中最佳频带的位置,并提取重构信号;其次,为了保证信号故障信息的全面性和获取精确故障特征信息,计算重构信号的全矢包络谱;最后,分析全矢包络谱中的故障特征进行故障诊断。通过分析仿真信号及实验数据,将所提方法与快速谱峭度和自相关谱峭度图等方法进行了对比,结果表明,所提故障诊断方法能够有效地提取滚动轴承的故障特征频率,提高故障诊断的精确性。

In this paper,a rolling bearing fault diagnosis method based on full vector spectrum and Autogram is proposed to solve the problems of low signal-to-noise ratio and the incompleteness and inaccuracy of single channel signal of rolling bearing.Firstly,the Autogram algorithm is used to obtain the optimal frequency band position in the signal,and the signal is reconstructed according to the selected frequency band to improve the signal-to-noise ratio.Secondly,The full vector spectrum technology is used to fuse the reconstructed signals to ensure the comprehensiveness of fault information.Finally,according to the fault characteristics in the full vector envelope spectrum,the fault diagnosis results are obtained.The proposed method is compared with the fast spectral kurtosis and the existing methods by simulation and experimental data of rolling bearing analysis.Tested results show that the proposed fault diagnosis method can effectively extract the fault feature frequency of rolling bearing and improve the accuracy of fault diagnosis.