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基于EMD阈值降噪的轴承故障诊断研究
Research of Bearing Fault Diagnosis Based on EMD Threshold Denoising
【摘要】 针对滚动轴承故障诊断提出了EMD阈值降噪法。通过振动传感器获得的轴承振动信号,利用经验模态方法将信号分解为多个IMF分量。因振动信号中含有的噪声主要表现在高频段,所以对IMF分量中的高频分量进行小波阈值降噪,并与IMF分量中低频分量进行重构,实现了振动信号的降噪,有利于轴承故障的判断。
【Abstract】 In this paper EMD threshold denoising method is researched. The bearing vibration signals obtained through the sensor are decomposed for multiple IMF components using empirical mode. The IMF components of the high frequency component are wavelet threshold denoising,because the vibration signal noise is mainly manifested in the high frequency band. And then IMF components through denoising are reconstructed with other noise to achieve denoising purpose and bearing fault diagnosis.
【基金】 山东省自然基金项目(ZR2013FM005)
- 【文献出处】 煤矿机械 ,Coal Mine Machinery , 编辑部邮箱 ,2014年03期
- 【分类号】TN911.7
- 【被引频次】1
- 【下载频次】120