基于谐波小波包变换的齿轮箱包络解调分析

齿轮箱发生某些故障时所产生的非平稳信号具有多分量调制的特点，啮合分量及倍频受噪声干扰影响严重且相互交叠，信号频带较宽异常复杂，给故障诊断带来了很大的障碍。在研究谐波小波频段分解与Hibert解调分析的基础上，提出了基于谐波小波包变换的解调分析法的实现过程。该方法首先对预处理后的信号进行三次样条插值并作必要的频谱分析；然后结合频谱特征与齿轮箱故障特征频率的理论计算值，确定所需提取的特征啮合分量；继而确定谐波小波包分解层数与提取的频带带宽，再通过傅立叶变换及反变换得到相应的特征啮合分量；最后采用Hilbert算子对提取出的啮合分量进行包络解调分析。将该方法应用到实际齿轮箱的磨损及点蚀故障的诊断试验中，验证了该方法对任意频段调制信息的精确提取能力，为齿轮箱故障源及故障程度的准确定位提供了可靠的判断依据。

Corrlative technique for wavelet-domain impact energy and its application

Aiming at disadvantages of a general wavelet energy method,an improved correlative technique for wavelet-domain impact energy was proposed.With this method,AR modeling was used to remove periodic harmonic components from a vibration signal to be analyzed.Then using continuous wavelet transformation,the de-noised signal was decomposed into different wavelet scales.Teager energy operator was used to track the instantaneous energy of each wavelet coefficient.Based on the sensitivity of kurtosis and cyclostatistic to rotating machine impact signal,Teager energy series of wavelet coefficient were screened out and integrated in the scale domain.Finally,the occurring period of impact signals was extracted using the correlative algorithm.The results showed that the proposed method can extract occurring frequency of weak impact in strong noise background and decrease the rate of fault mis-discrimination for rotating machines.