基于迭代增强变分模态提取的滚动轴承复合故障诊断

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摘要针对变分模态提取对多分量复合故障提取能力不足，且存在中心频率和平衡因子两个超参数优化等问题，提出了一种迭代增强变分模态提取(Iterative enhanced variational mode extraction, IEVME)的滚动轴承复合故障诊断新方法。首先，提出引入中心频率趋势收敛现象优化VME的初始中心频率，使其能自适应寻找合适的初始中心频率进行提取并加入新的收敛准则对信号进行迭代提取的迭代变分模态提取方法(Iterative variational mode extraction, IVME)；然后，通过优化IVME的平衡因子得到多个分量信号，再利用图拉普拉斯能量指数选取最优分量进行重构；接着，为全面提取复合故障信号中的主要周期，提出了结合加强运算减去运算的增强最小噪声幅值解卷积(Enhanced minimum noise amplitude deconvolution, EMNAD)方法，以降低噪声并增强相对较弱的周期信号；最后，通过融合平方包络谱实现对滚动轴承的复合故障诊断。将所提方法应用到滚动轴承复合故障诊断中，通过仿真和实例信号验证所提IEVME方法的有效性和鲁棒性，并将所提方法与现有多种方法进行对比，结果表明所提IEVME方法准确性更高，效果更优。

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	张家军 1
	马萍 1
	张海 2
	张宏立 1

关键词 ：滚动轴承, 迭代增强变分模态提取, 增强最小噪声幅值解卷积, 复合故障诊断

Abstract：To solve the problem of insufficient extraction capacity of variational mode extraction for multi-component composite faults and the existence of two hyperparameter optimizations of center frequency and balance factor, an iterative enhanced variational mode extraction (IEVM) method for composite fault diagnosis of rolling bearing was proposed. Firstly, an iterative variational mode extraction method (IVME) was proposed to optimize the initial center frequency of VME by introducing the convergence phenomenon of center frequency trend, so that it can find an appropriate initial center frequency to extract and add a new convergence criterion to extract the signal iteratively; Then, a plurality of component signals were obtained by optimizing the balance factor of IVME, and the optimal component was selected for reconstruction by means of the Graph-Laplace energy index; Secondly, in order to extract the main period in the composite fault signal, an enhanced minimum noise amplitude deconvolution (EMNAD) method was proposed, which combines enhanced algorithm subtraction to reduce the noise and enhance the relatively weak periodic signal; Finally, the composite fault diagnosis of rolling bearing was realized by fusion of square envelope spectrum. The proposed method was applied to the composite fault diagnosis of rolling bearing, and the effectiveness and robustness of the proposed IEVME method have been verified by simulation and example signals. The proposed method was compared with the existing multiple methods, and the results show that the proposed IEVME method has higher accuracy and better effect.

Key words： rolling bearing iterative enhanced variational mode extraction enhanced minimum noise amplitude deconvolution composite fault diagnosis

收稿日期: 2023-07-17 出版日期: 2024-04-15

引用本文:

张家军 1，马萍 1，张海 2，张宏立 1. 基于迭代增强变分模态提取的滚动轴承复合故障诊断[J]. 振动与冲击, 2024, 43(7): 255-265.
ZHANG Jiajun1, MA Ping1, ZHANG Hai2, ZHANG Hongli1. Composite fault diagnosis of rolling bearing based on iterative enhanced variational mode extraction. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(7): 255-265.

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http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2024/V43/I7/255

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