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Extraction of transmission bearing fault characters based on EMD and fractal theory

机译:基于EMD和分形理论的变速箱轴承故障特征提取

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The vibration signal of transmission bearing is decomposed by empirical mode decomposition, and fractal dimensions of decomposed intrinsic mode functions are calculated to extract fault characters of transmission bearings of different conditions. The results show that empirical mode decomposition method is able to separate signals of different frequency bands effectively, and the fractal dimension of specific IMF component is able to reflect the technology state of transmission bearing sensitively, which can be selected as the characteristic parameters to diagnose transmission bearing fault. The combination of empirical mode decomposition and fractal dimension is an effective method of transmission bearing's fault character extraction.
机译:通过经验模态分解来分解变速箱轴承的振动信号,并计算分解后的本征函数的分形维数,以提取不同条件下变速箱轴承的故障特征。结果表明,经验模态分解方法能够有效分离不同频段的信号,特定IMF分量的分形维数能够敏感地反映出传输轴承的技术状态,可以作为诊断传输的特征参数。轴承故障。经验模态分解和分形维数相结合是传动轴承故障特征提取的有效方法。

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