摘要
提出了基于 EMD(Em pirical Mode Decom position)和 AR模型的滚动轴承故障诊断方法。该方法用 EMD将滚动轴承振动信号分解成若干个平稳的 IMF(Intrinsic Mode Function)分量 ,对每一个 IMF分量建立 AR模型 ,以模型的自回归参数和残差的方差作为特征向量建立 Mahalanobis距离判别函数 ,进而判断滚动轴承的工作状态和故障类型。实验结果分析表明 ,该方法能有效地应用于滚动轴承的故障诊断。
A fault diagnosis approach for roller bearing based on EMD (Empirical Mode Decomposition) method and AR model is proposed. The EMD method is used to decompose the vibration signal of a roller bearing into a number of intrinsic mode function components and then the AR model of each IMF component is established. The auto-regressive parameters and the variance of remnant are regarded as the feature vectors. The distance criterion function is used to identify the condition and fault pattern of roller bearings. Practical examples show that the proposed approach can be applied to the roller bearing fault diagnosis effectively.
出处
《振动工程学报》
EI
CSCD
北大核心
2004年第3期332-335,共4页
Journal of Vibration Engineering
基金
国家自然科学基金资助项目 (编号 :5 0 2 75 0 5 0 )
高等学校博士点专项科研基金资助项目 (编号 :2 0 0 2 0 5 32 0 2 4 )
