基于蝙蝠算法优化VMD参数的滚动轴承复合故障分离方法

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摘要针对强背景噪声干扰下的滚动轴承复合故障特征难以提取且变分模态分解(VMD)中参数需要提前确定的问题，提出一种基于蝙蝠算法优化VMD参数的滚动轴承复合故障分离方法。首先，提出一种新的复合影响指数，将其与现有指标进行比较，结果表明所提指标对故障信号的敏感性提高了29.6%。然后，将最小平均复合影响指数作为目标函数，利用蝙蝠算法自适应搜索VMD的最优参数进行变分模态分解。最后，对分解后的模态分量进行包络解调分析，通过包络谱判断轴承的故障类型。仿真及实验结果表明，该方法能够从噪声干扰下的复合故障信号中有效分离出单一故障信息，实现轴承故障类型的确定，从而验证了该方法的有效性。
关键词：蝙蝠算法；变分模态分解；复合影响指数；复合故障

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	张伟1
	2
	李军霞1
	2
	陈维望1
	2

关键词 ：蝙蝠算法, 变分模态分解, 复合影响指数, 复合故障

Abstract：Aiming at the problems that the composite fault feature information of rolling bearing under the interference of strong background noise is extracted difficultly, and the parameters in the variational modal decomposition (VMD) need to be determined in advance, a composite fault separation method for rolling bearing based on VMD optimized by bat algorithm is proposed. First, a new comprehensive impact index is proposed and compared with existing indicators, The results show that it have increased by 29.6% to the sensitivity of the fault signal. Then, proposing the minimum average comprehensive influence index as the objective function, the bat algorithm is used to adaptively search the optimal parameters of VMD, and the signal is decomposed by VMD. Finally, the decomposed modal components are subjected to envelope demodulation analysis, and the fault type of the bearing is judged through the envelope spectrum. The simulation and experimental results show that the method can effectively separate the information of a single fault from the composite fault signal under noise interference, and determine the type of bearing fault, thus the effectiveness of the method is verified.
Key words: bat algorithm; variational modal decomposition; composite impact index; compound fault diagnosis

Key words： bat algorithm variational modal decomposition composite impact index compound fault diagnosis

收稿日期: 2021-07-08 出版日期: 2022-10-28

引用本文:

张伟1,2，李军霞1,2，陈维望1,2. 基于蝙蝠算法优化VMD参数的滚动轴承复合故障分离方法[J]. 振动与冲击, 2022, 41(20): 133-141.
ZHANG Wei1,2，LI Junxia1,2，CHEN Weiwang1,2. A compound fault feature separation method of rolling bearings based on VMD optimized by the bat algorithm. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(20): 133-141.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2022/V41/I20/133

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