尹怀彦, 张涛. 基于GA-VMD的滚动轴承故障特征信号提取方法[J]. 机械研究与应用, 2023, 36(5): 1-5. DOI: 10.16576/j.ISSN.1007-4414.2023.05.001
引用本文: 尹怀彦, 张涛. 基于GA-VMD的滚动轴承故障特征信号提取方法[J]. 机械研究与应用, 2023, 36(5): 1-5. DOI: 10.16576/j.ISSN.1007-4414.2023.05.001
YIN Huai-yan, ZHANG Tao. Fault Feature Signal Extraction Method of Rolling Bearing Based on GA-VMD[J]. Mechanical Research & Application, 2023, 36(5): 1-5. DOI: 10.16576/j.ISSN.1007-4414.2023.05.001
Citation: YIN Huai-yan, ZHANG Tao. Fault Feature Signal Extraction Method of Rolling Bearing Based on GA-VMD[J]. Mechanical Research & Application, 2023, 36(5): 1-5. DOI: 10.16576/j.ISSN.1007-4414.2023.05.001

基于GA-VMD的滚动轴承故障特征信号提取方法

Fault Feature Signal Extraction Method of Rolling Bearing Based on GA-VMD

  • 摘要: 针对轴承故障提取困难的问题, 该文建立了以包络熵和峭度为综合目标函数的变分模态分解(VMD)参数优化方法。用遗传算法对综合目标函数的最小值进行计算寻优, 获得最佳的模态分解个数和惩罚因子的值。利用遗传算法(GA)优化的VMD分解方法获得仿真信号和实测信号的本征模态函数(IMFs), 依据相关峭度值最大的方法选取IMF敏感分量, 并对其进行Hilbert包络谱分析。分析结果表明, 基于遗传算法优化的VMD分解方法能够有效提取故障特征信号。

     

    Abstract: To solve the problem of difficulty in bearing fault extraction, a VMD parameter optimization method with the envelope entropy and kurtosis as the comprehensive objective function is established in this paper. The genetic algorithm is used to compute the minimum value of the integrated objective function to obtain the optimal number of modal decompositions and the value of the penalty factor. The VMD method optimized by GA is used to obtain the IMFs of the simulated and measured signals, and the sensitive component of IMFs is selected based on the method with the maximum value of correlation kurtosis and then analyzed by Hilbert envelope spectrum. The results show that the VMD method based on genetic algorithm optimization can effectively extract the fault feature signals.

     

/

返回文章
返回