基于局部均值分解和切片双谱的滚动轴承故障诊断研究

唐贵基;王晓龙

振动与冲击 ›› 2013, Vol. 32 ›› Issue (24) : 83-88.

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PDF(2870 KB)
振动与冲击 ›› 2013, Vol. 32 ›› Issue (24) : 83-88.
论文

基于局部均值分解和切片双谱的滚动轴承故障诊断研究

  • 唐贵基,王晓龙
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Research on Fault Diagnosis for Roller Bearings Based on Local Mean Decomposition and Slice Bispectrum

  • Tang Guiji,Wang Xiaolong
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摘要

针对滚动轴承故障诊断问题,提出一种结合局部均值分解(LMD)和切片双谱的诊断新方法。首先利用LMD算法对故障信号进行自适应分解,分解后获得一组位于不同频带的乘积函数(PF)分量,然后利用本文提出的峭度准则对分解结果进行筛选,筛选出峭度值最大的PF分量,并对其包络信号做切片双谱分析,从而提取出故障特征频率信息。为加快分解速度、减少分解运算量,本文对LMD算法中的循环迭代结束条件做出改进,并利用模拟信号验证了LMD算法的信号分解能力以及切片双谱的噪声抑制和非二次相位耦合谐波剔除能力。最后,运用提出的诊断方法对实测轴承内圈、外圈故障振动信号进行分析,诊断效果良好,证明该方法具有一定的可靠性。

Abstract

To effectively extract the fault features of roller bearings, a new method based on Local Mean Decomposition and slice bispectrum are proposed. Original fault signals were decomposed into a series of product function components of different frequency bands, filter the decomposition results by proposed kurtosis criteria, then select PF component whose kurtosis value is the maximum, the fault type could be judged by analysis the slice bispectrum which is computed for the envelope signal of the product function component. In order to reduce the amount of computation and accelerate the decomposition rate, the stopping conditions of local mean decomposition was improved, then the decomposed capacity of LMD and capabilities of noise suppression and eliminate the non-quadratic phase coupling harmonic components of slice bispectrum were verified by simulation signal .Bearing inner ring and outer ring fault signals were analysis by this diagnostic method and the results show that this method has a certain degree of reliability.


关键词

局部均值分解 / 峭度准则 / 切片双谱 / 滚动轴承

Key words

local mean decomposition / kurtosis criteria / slice bispectrum / roller bearings

引用本文

导出引用
唐贵基;王晓龙. 基于局部均值分解和切片双谱的滚动轴承故障诊断研究[J]. 振动与冲击, 2013, 32(24): 83-88
Tang Guiji;Wang Xiaolong. Research on Fault Diagnosis for Roller Bearings Based on Local Mean Decomposition and Slice Bispectrum[J]. Journal of Vibration and Shock, 2013, 32(24): 83-88

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