内禀模态特征能量法在滚动轴承故障模式识别中的应用

针对滚动轴承振动信号和状态信息非线性映射关系，提出一种基于内禀模态函数（IMF）特征能量的轴承特征向量提取方法，并与支持向量机（SVM)相结合实现轴承的故障识别。该方法对滚动轴承振动信号进行经验模态分解（EMD）得到若干能反映轴承故障信息的IMF分量，选取包含主要信息的IMF能量作为振动信号的特征向量，并将其输入到SVM分类器中实现轴承故障模式识别。对滚动轴承的正常状态、外圈故障、内圈故障和滚动体故障进行仿真试验，结果表明，该方法能够有效、准确地识别轴承故障。

Application of Intrinsic Mode Function Feature Energy Method in Fault Pattern Recognition of Rolling Bearing

For nonlinear mapping relationship between vibration signal and state information in rolling bearing,a bear-ing feature vector extraction based on intrinsic mode function(IMF)feature energy in combination with support vector machine(SVM)is proposed for fault pattern recognition of bearing.The vibration signal of rolling bearing is decomposed into some IMF reflected bearing fault information by empirical mode decomposition(EMD),the energies including major information IMF are taken as eigenvectors.They are i...