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。
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-compo- nent 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 vec- tor spectrum. So the signals can not only be decomposed completely, but also their integrity can be ensured. Its effectiveness and feasi- bility are verified through the gear fault signals.
出处
《机床与液压》
北大核心
2015年第3期182-184,共3页
Machine Tool & Hydraulics
基金
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)
关键词
全矢谱
局部均值分解
全矢局部均值分解
齿轮故障诊断
Full vector spectrum
Local mean decomposition
Full vector of local mean decomposition
Gear fault diagnosis