基于变分模态分解和1.5维谱的轴承早期故障诊断方法

Incipient bearing fault diagnosis based on VMD and 1.5-dimension spectrum

提出了基于变分模态分解(VMD)和1.5维谱的滚动轴承早期故障诊断方法。利用VMD方法处理故障信号时,需要预先设置分解所得本征模态函数(IMF)分量的个数,且为了便于后续分析,需要从所得结果中筛选出最佳信号分量,为此提出一种分量峭度图方法来同时解决这2个问题。首先,设置IMF分量个数最大值,计算相应的分量峭度图;接着,根据分量峭度图对原故障信号进行VMD处理,并选定最佳IMF分量;然后,对最佳IMF分量做进一步包络解调运算,并计算包络信号的1.5维谱;最后,通过分析1.5维谱中幅值突出的频率成分可实现故障类型的准确判定。模拟信号及实测信号分析结果表明,所提的基于VMD和1.5维谱的诊断方法能够有效提取出轴承早期故障信号中的微弱特征信息,实现轴承早期故障的准确判别。

A method based on VMD（Variational Mode Decomposition） and 1.5-dimension spectrum is proposed for diagnosing the incipient fault of rolling bearing. The number of IMFs（Intrinsic Mode Functions） should be set in advance for processing the fault signals by VMD and the best IMF should be selected from the obtained results for facilitating the following analysis. A method of kurtosis diagram is thus proposed：the maximum number of IMF is set and the IFM kurtosis diagram is calculated;the original fault signals are processed by VMD based on different IMF numbers;the best IMF is selected and then processed by the envelope demodulation;the 1.5-dimension spectrum of the demodulated envelope signals are calculated;the fault type is detected by analyzing the frequency components with obvious amplitude in the calculated 1.5- dimension spectrum. The results of analysis for simulative signals and measured signals show that,the proposed diagnosis method can effectively extract the weak characteristic information from the incipient fault signals of bearing and diagnose the incipient fault of roiling bearing exactly.