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摘要:
针对小波阈值降噪不充分及经验模态分解(EMD)特征频率提取不明显的问题,提出一种基于麻雀搜索算法-改进小波阈值-EMD(SSA-IWT-EMD)的滚动轴承故障诊断方法。引入2个调节因子,提出一种IWT函数,克服了传统软硬阈值的缺点,并运用SSA对其各参数进行全局寻优,实现滚动轴承信号降噪。提出一种综合指标
P 对EMD产生的分量进行选取重构,突出信号的故障特征信息。采用包络谱分析实现轴承的故障诊断。仿真和实测结果验证了所提方法的有效性;同时与单一指标选取分量的方法及文献方法进行对比,说明了综合指标P 和所提方法具有更强的降噪能力及特征提取能力,包络谱幅值及倍频成分更明显,可以更好地实现对滚动轴承的故障诊断。Abstract:Wavelet threshold denoising is insufficient, and feature frequency extraction of empirical mode decomposition (EMD) is unclear. To address these issues, a fault diagnosis method of rolling bearings based on sparrow search algorithm - improved wavelet threshold-EMD (SSA-IWT-EMD) was proposed. Firstly, two adjustment factors were introduced, and an IWT function was presented to overcome the shortcomings of traditional soft and hard thresholds. The SSA was used to globally optimize the parameters of the IWT to reduce the noise of rolling bearing signals. Secondly, a comprehensive index
P was put forward to select and reconstruct the components generated by EMD, so as to highlight the fault feature information of the signals. Finally, the fault diagnosis of bearings was realized by envelope spectrum analysis. The simulation and experimental results verified the effectiveness of the proposed method. At the same time, the comparison with the single index component selection method and the literature method indicated that the comprehensive indexP and the method proposed in this paper had stronger denoising ability and feature extraction ability, and the envelope spectrum amplitude and frequency doubling component were more obvious, which could better realize the fault diagnosis of rolling bearings. -
表 1 仿真信号EMD分解分量参数
Table 1. Parameters of EMD components of simulation signal
分量 综合指标P 分量 综合指标P 分量 综合指标P IMF1 15.517 IMF4 4.091 IMF7 2.011 IMF2 7.913 IMF5 4.798 IMF8 2.067 IMF3 9.848 IMF6 1.888 IMF9 2.307 表 2 ER-6k轴承参数
Table 2. Parameters of ER-6k bearing
轴承节径/mm 滚珠直径/mm 滚动体个数/个 故障直径/mm 38.70 8 9 1.2 表 3 试验轴承信号1 EMD分解分量参数
Table 3. Parameters of EMD components of signal 1 of test bearing
分量 综合指标P 分量 综合指标P IMF1 3.410 IMF6 2.981 IMF2 3.614 IMF7 1.431 IMF3 4.319 IMF8 1.643 IMF4 2.644 IMF9 1.564 IMF5 2.245 IMF10 0.941 表 4 试验轴承信号2 EMD分解分量参数
Table 4. Parameters of EMD components of signal 2 of test bearing
分量 综合指标P 分量 综合指标P 分量 综合指标P IMF1 30.614 IMF4 4.906 IMF7 2.534 IMF2 21.787 IMF5 5.401 IMF8 2.407 IMF3 4.825 IMF6 3.149 IMF9 1.557 表 5 试验轴承信号2EMD分解分量峭度参数
Table 5. Kurtosis parameters of EMD components of signal 2 of test bearing
分量 峭度 分量 峭度 分量 峭度 IMF1 16.225 IMF4 16.772 IMF7 4.629 IMF2 14.114 IMF5 4.781 IMF8 2.686 IMF3 10.170 IMF6 5.954 IMF9 1.979 -
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