基于共振解调和小波分析方法的轴承故障特征提取研究  

The extraction of fault feature of rolling bearing-based on resonance demodulation and wavelet analysis

作　　者：王子玉[1] 孔凡让[1] 

机构地区：[1]中国科学技术大学精密机械与精密仪器系,合肥230027

出　　处：《现代制造工程》2012年第1期117-121,共5页Modern Manufacturing Engineering

摘　　要：首先研究了共振解调和小波分析的基础理论,并结合两者应用于对轴承外圈和滚子的故障特征提取。该方法先从振动信号频谱中判断系统固有高频成分的大致范围,然后利用小波分解取出固有高频信号成分,再利用Hilbert变换做包络检波,最后对包络信号进行傅里叶频谱分析得出故障信号特征频率。对实际轴承故障数据的分析表明,该方法能有效地提取轴承的外圈故障特征,有一定的应用价值。但该方法不能清晰地提取出滚子故障特征,探讨了其内在原因,并提出了可能改进的措施。Introduce the method of resonance demodulation and multi-resolution analysis of wavelets. Combining both methods, try to extract fault feature of outer-ring and rollers of rolling bearings. First, estimate the natural frequencies of the system from frequency spectrum. Second, extract high frequency ingredients from initial signal, using wavelet decomposition. Third, using Hilbert transform,envelope the high frequency signal obtained form last step. Finally ,analyze the frequeney spectrum of the enveloped signal to detect the fault frequency. Experiments on fault roiling bearings show that, the method introduced can extract fault feature of outer-ring of rolling bearings efficiently, and show its application value. However, this method cannot extract fault feature of rollers distinctly. Analyze the internal reason of this, and put forward some possible methods of improvement.

关 键 词：共振解调 小波分析 HILBERT变换 故障特征 

分 类 号：TH16[机械工程—机械制造及自动化]