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。本文提出了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。
Abstract
Fatigue spalling is the most common cause of rolling bearing failure. The acceleration signals resulting from the entry of the rolling element into the spall and exit from it show the different natures when spalling failure occur in rolling ball bearing. The entry into the fault could be described as a step response, with mainly more releative low-frequency components, while the exit from the fault could excite a broader frequency impulse response as the the ball strikes the trailing edge of the fault. The effective separation of the two events plays an important role in measuring the size of the hybrid ceramic ball bearing faults. An envelope extraction based on ensemble empirical mode decomposition (EEMD) is proposed in the paper for the double impulses extraction of faulty hybrid ceramic ball bearing. In the proposed approach, the auto-regressive(AR) model is utilized to pre-whiten the raw vibration signal of the hybrid ceramic ball bearing faults at first. Then, the pre-whitened signal is filtered using a filter based on EEMD. Lastly, the Hilbert base envelope extraction is employed to extract the double impulses. Simulation and test experiments 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
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Key words
Envelope analysis /
EEMD /
Hybrid Ceramic Ball Bearing /
Double Impulses /
Bear Fault
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