基于EEMD和小波包的机车轴箱轴承故障诊断方法

Fault Diagnosis Method for Axle Box Bearing of Locomotive Based on EEMD and Wavelet Packet

提出了一种基于聚合经验模态分解(ensemble empirieal mode decomposition,EEMD)和小波包的机车轴箱轴承故障诊断方法.首先对轴承振动信号进行小波包分解,分别对小波包分解得到的小波包系数进行阈值去噪处理,将降噪后剩余的小波包系数进行信号重构.然后再对重构后的信号进行EEMD,计算EEMD分解得到的IMF分量和原信号的互相关系数,最后对满足相关条件的IMF分量进行故障诊断分析.为了验证该方法的正确性,搭建了轴承试验平台,通过对轴承实测数据进行故障诊断分析,实验证明该组合诊断方法能克服单一信号处理方法的局限性并能初步诊断出轴承发生的故障.

A fault diagnosis method for axle box bearing of locomotive based on EEMD and wavelet packet is proposed. Firstly,the signal is denoised by wavelet packet,and the wavelet packet coef- ficients of wavelet packet decomposition are used for threshold denoising,then the wavelet packet coefficients after noise reduction are reconstructed. After that, EEMD is used to decompose the denoised signal and the cross-correlation coefficients are calculated. Finally, IMFs component whose correlation coefficient meets the relevant conditions is analyzed. In order to prove the valid- ity of the diagnosis method,a test-bed of bearing is built. The experimental results show that the method can overcome the limitation of the traditional method, effectively extract the fault charac- teristic information of the bearing and accurately determine the specific location of the hearing failure.