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基于全矢局部均值分解的齿轮故障诊断方法研究
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国家自然科学基金(50675209);河南省高等学校青年骨干教师资助项目(2010GGJS020);河南省教育厅自然科学研究计划(2010B460014)


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    摘要:

    针对齿轮故障信号大多数是难分解的多分量的调幅-调频信号的问题,提出一种新的信号处理方法——全矢局部均值分解(FVLMD)方法。局部均值分解(LMD)可将多分量信号自适应地分解为多个单分量信号;全矢谱技术可以解决单通道信号不完整的问题。运用信息融合技术,将信号LMD分解得到的PF(Product Function)分量进行全矢谱融合分析,这样既可以将信号彻底分解,又可以保证其完整性。齿轮故障信号验证了该方法的有效可行性。

    Abstract:

    Aimed at the problem of most of the gear fault signals are the multicomponent AMFM signals which are very difficult to decompose, a new signal processing method of the full vector of local mean decomposition (FVLMD) was proposed. A multicomponent signal was adaptively decomposed into a complex of series of singlecomponent signals by using the local mean decomposition (LMD). The problem which singlechannel signal was usually not complete was solved by the full vector spectrum technology. By using the information fusion technology, the PF (Product Function) component decomposed by LMD was fused with analysis by the full vector spectrum. So the signals can not only be decomposed completely, but also their integrity can be ensured. Its effectiveness and feasibility are verified through the gear fault signals.

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苏文芳,李凌均,韩捷,石帅锋.基于全矢局部均值分解的齿轮故障诊断方法研究[J].机床与液压,2015,43(3):182-184.
.[J]. Machine Tool & Hydraulics,2015,43(3):182-184

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  • 在线发布日期: 2015-06-17
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