Fault diagnosis approach for bearing based on EMD and slice bi-spectrum
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摘要: 针对轴承故障诊断问题,提出一种基于经验模态分解(EMD,Empirical Mode Decomposition)与切片双谱分析相结合的新方法.将原始信号分解成不同尺度的固有模态函数(IMF,Intrinsic Mode Function),求取IMF分量的包络,计算其对角切片双谱,提取由于二次相位耦合产生的非线性特征,得到轴承的故障特征频率.通过对仿真信号进行分析,表明该方法克服了传统的基于EMD的包络功率谱方法不能抑制噪声的缺点,同时较传统高阶谱方法计算量更小.给出了6205-2RS JEM SKF轴承诊断实例,说明了该方法的可用性.Abstract: A new approach based on the empirical mode decomposition (EMD) and slice bi-spectrum was presented for fault diagnosis on roller bearings. Original signals were decomposed into a series of intrinsic mode functions (IMFs) of different scales. Envelopes of the IMFs were extracted and a diagonal slice bi-spectrum for the envelopes was computed to extract the non-linear feature deriving from the quadratic phase coupling, as well as the fault characteristic frequencies. An analysis on simulation signals shows that the drawback that traditional envelope spectrum methods based on EMD cannot inhibit the noise can be overcome by this approach. Meanwhile, its computation load is less than traditional high-order spectrum methods. A diagnosis instance of the bearing 6205-2RS JEM SKF was presented to show the feasibility of this approach.
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Key words:
- fault diagnosis /
- bearings /
- empirical mode decomposition /
- slice bi-spectrum
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