改进Hilbert-Huang变换在齿轮故障诊断中的应用
Application of improved Hilbert-Huang transform method in gear fault diagnosis
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摘要: 针对Hilbert-Huang变换中齿轮故障信号经验模式分解的第一阶固有模态函数通常为非单一信号分量以及经验模式分解产生虚假低频分量的问题, 提出一种改进Hilbert-Huang变换方法.首先在频谱中确定故障信息频率范围, 并依据该频率范围和二进小波分解的特点确定需提取的相应频带的二进小波系数, 然后采用相关系数筛选法剔除小波系数经验模式分解所产生的虚假分量, 最后通过局部瞬时能量提取故障特征, 实例表明改进的Hilbert-Huang变换可以有效的提取齿轮故障特征.
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关键词:
- 航空发动机 /
- 齿轮故障诊断 /
- 改进Hilbert-Huang变换 /
- 二进小波系数提取 /
- 相关系数筛选法
Abstract: The first intrinsic mode function(IMF) is generally a multi-component as the result of the abundant frequency component in gear fault signal.Pseudocomponents in low frequency may be produced in empirical mode decomposition(EMD).An improved Hilbert-Huang transform(HHT) method was proposed to overcome these two problems.Frequency span of fault information has been achieved in frequency spectrum, so corresponding binary wavelet coefficient of narrow-band signal could be extracted.The method of correlation coefficient screening was used to remove pseudocomponent in EMD of wavelet coefficient.Local instant energy was used to extract gear fault feature.It is demonstrated that improved HHT method could diagnose the gear fault effectively.
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