基于经验模式分解和主元分析的滚动轴承故障诊断方法研究

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振动与冲击 ›› 2014, Vol. 33 ›› Issue (23) : 133-139.

论文

基于经验模式分解和主元分析的滚动轴承故障诊断方法研究

徐卓飞1 刘凯1 张海燕2 王丹1 张明龙2 吴欣阳2

作者信息 +

A Fault diagnosis method for Rolling Bearing based on Empirical Mode Decomposition and Principal Component Analysis

Xu Zhuofei1 LIU Kai1 Zhang Haiyan2 Wang Dan1 Zhang Minglong2 Wu Xinyang2

Author information +

文章历史 +

摘要

提出了一种融合经验模式分解和多元统计的轴承故障诊断新方法，主要包括基于信号Hilbert-Huang变换的特征提取和对故障特征集的主成分分析：首先运用EMD将振动信号分解成不同特征时间尺度的单分量固有模态函数，采取Hilbert-Huang变换获取分解信号的瞬时频率，计算基本模式分量与瞬时频率的统计特征集；之后对统计特征集进行主成分分析，大幅降低特征向量的维数，获取主元特征集；最后利用支持向量机，完成了对于滚动轴承常见三类故障的分类，并分析了振动信号时域频域的统计特征值与故障模式之间的联系。

Abstract

A new fault diagnosis method for rolling and bearing based on empirical mode decomposition and multivariate statistics is proposed. The Hilbert-Huang transform and principal component analysis are used in this method. The vibration signal is decomposed into the basic mode components with EMD and the instantaneous frequency of each component is obtained with a Hilbert-Huang transform. Then calculate the statistical characteristics of the instantaneous frequency and the time domain signal. Analyses the statistical characteristics with PCA in order to reduce the number of dimensions of the feature vector and get the principal component characteristics. Finally, complete the classification of three failure modes in rolling bearing and analyze the relationship between the statistical characteristics and failure modes.

导出引用

徐卓飞刘凯张海燕王丹张明龙吴欣阳. 基于经验模式分解和主元分析的滚动轴承故障诊断方法研究[J]. 振动与冲击, 2014, 33(23): 133-139

Xu Zhuofei LIU Kai Zhang Haiyan Wang Dan Zhang Minglong Wu Xinyang. A Fault diagnosis method for Rolling Bearing based on Empirical Mode Decomposition and Principal Component Analysis[J]. Journal of Vibration and Shock, 2014, 33(23): 133-139