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基于倒谱预白化和奇异值分解的滚动轴承故障特征提取方法

DOI: 10.13334/j.0258-8013.pcsee.2014.35.013, PP. 6355-6361

Keywords: 滚动轴承,倒谱编辑(CEP),信号预白化,奇异值分解(SVD),故障诊断

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Abstract:

为了有效提取轴承的故障特征,避免轴承损伤引起的冲击成分受到离散频率分量和强背景噪声的干扰,该文提出了一种新的基于倒谱编辑(cepstrumeditingprocedure,cep)信号预白化和奇异值分解(singularvaluedecomposition,SVD)的轴承故障特征提取方法。通过CEP预白化处理增强了轴承故障的冲击特性,去除复杂振动信号中的周期性频率成分,产生了只包含背景噪声和碰撞损伤引起的非平稳冲击成分的白化信号。构造预白化信号的Hankel矩阵,进行奇异值分解,通过差分谱理论选择表征故障冲击成分的奇异值进行矩阵重构恢复信号,去除强背景噪声的干扰,实现对故障特征的提取。试验结果表明,该方法较为理想地提取了轴承滚动体和内圈的故障特征,并且在提取效果和运算效率方面要优于基于小波-SVD差分谱故障特征提取方法。

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