摘要
针对滚动轴承在实际工作条件下背景噪声过大且难以去除等问题,基于CEEMDAN分解与SVD对背景噪声进行过滤。经对比实验分析证明,文中提出的方法在强噪声背景下比现有的单一降噪方法更有效,可以应用于类似的滚动轴承故障信号分析当中。
Aiming at the problems of rolling bearing background noise being too large and difficult to remove under actual working conditions, this paper filters the background noise based on CEEMDAN decomposition and SVD. The comparative experimental analysis proves that the proposed method is more effective than the existing single noise reduction method under the background of strong noise, and can be applied to similar rolling bearing fault signal analysis.
作者
李明
徐壮壮
LI Ming;XU Zhuangzhuang(School of Electric Power,North China University of Water Resources and Electric Power,Zhengzhou 450000,China)
出处
《机械工程师》
2022年第1期63-65,共3页
Mechanical Engineer
