一种基于非线性流形的滚动轴承复合故障诊断方法  

A Method of Combine Fault Diagnosis for Roller Bearings based on Nonlinear Manifold

作　　者：赵洪杰[1] 潘紫微[1] 叶金杰[1] 罗文[2] 

机构地区：[1]安徽工业大学机械工程学院,安徽马鞍山243002 [2]马鞍山钢铁股份有限公司设备部,安徽马鞍山243003

出　　处：《机械传动》2012年第7期89-91,110,共4页Journal of Mechanical Transmission

摘　　要：针对滚动轴承振动信号的非平稳以及非线性特点,提出了一种基于非线性流形的滚动轴承复合故障诊断方法。该方法首先提取振动信号的时域指标和小波包频带分解能量所构成的频域指标,组成原始特征空间,采用基于判别准则的邻域因子优化选择算法,运用基于局部切空间排列算法的非线性降维算法对原始特征空间进行学习,极大地保留了信号中内在的整体几何结构信息,从而提取出振动信号最优的敏感故障特征。试验结果表明,与经典的线性降维方法相比,该方法的聚类效果更好。A combine fault diagnosis approach for roller bearing based on nonlinear manifold is proposed accord- ing to the fact that vibration signal of roller bearing is non - stationary and time - variation. After constructing the orig- inal feature space with the performance index of the vibration signal in time domain and frequency band energy decom- position using wavelet packets, according to optimal selection algorithm of neighborhood factor based on discriminate criterion, adopting a nonlinear dimensionality reduction algorithms based on local tangent space alignment algorithm to the original feature space, the whole geometry structure information embeded into the signal is hugely reserved so that the optimal sensitive fault feature of the vibration signal can be acquired. The experimental results show that the pro- posed method has better classification performance than the traditional linear dimensionality reduction method.

关 键 词：非线性流形 滚动轴承 复合故障 局部切空间排列算法 

分 类 号：TH133.33[机械工程—机械制造及自动化]