基于EEMD的混合陶瓷球轴承故障双冲击特征提取  

Double-impulse feature extraction of faulty hybrid ceramic ball bearings based on EEMD

作　　者：孔佑炳 郭瑜[1] 伍星[1] 

机构地区：[1]昆明理工大学机电工程学院,昆明650500

出　　处：《振动与冲击》2016年第1期17-22,共6页Journal of Vibration and Shock

基　　金：国家自然科学基金(51365023)

摘　　要：疲劳剥落是导致滚动轴承失效的主要原因,当滚道出现剥落故障时滚动体在进入和退出剥落区时的加速度振动信号表现出不同特征:进入故障区时产生以较低频率成分为主的阶跃响应;退出剥落区则引起频带较宽的脉冲响应。有效分离这两类信号特征,对实现对混合陶瓷球轴承剥落区长度的测量有重要意义。提出一种基于总体经验模态分解(EEMD)的混合陶瓷球轴承剥落故障双冲击特征提取方法,该方法首先用AR模型对原始振动信号进行预白化处理,然后利用EEMD对白化后的振动信号进行去噪,并结合Hilbert包络提取算法实现对剥落故障混合陶瓷球轴承振动信号双冲击特征的有效分离提取。仿真及试验研究表明该方法能够有效地分离出混合陶瓷球轴承故障双冲击特征。Fatigue spalling is the most common cause of rolling bearing failure. When spalling failure occurs in a rolling ball bearing , the vibration acceleration signals have different features during rolling elements entering the spall area and leaving it. During rolling elements entering the spalling area, the signals are step responses, with mainly lower- frequency components, but during rolling elements leaving the spalling area, they are broader frequency impulse responses. The effective separation of the two features plays an important role in measuring the length of hybrid ceramic ball bearings＇ spalling area. Here, an envelope extraction method based on ensemble empirical mode decomposition （EEMD） was proposed for the double-impulse extraction of faulty hybrid ceramic ball bearings. With this approach, firstly the auto-regressive（AR） model was used to pre-whiten the original vibration signals of feauhy hybrid ceramic ball bearings ~ Then, the pre-whitened signals were denoised based on EEMD. Lastly, Hilbert envelope extraction method was employed to extract the double-impulse. Simulation and tests were conducted respectively to verify the validity of the proposed method.

关 键 词：包络分析 EEMD 混合陶瓷球轴承 双冲击 轴承故障 

分 类 号：TH133.33[机械工程—机械制造及自动化]