摘要
数控机床的故障诊断技术可有效提高设备运行的可开性,噪音信号作为其故障诊断的输入之一,其去噪效果的优良为数控机床的故障诊断奠定了基础。基于此提出一种基于互补集合经验模态分解的噪音信号处理方法,通过对噪音信号分别使用小波包、CEEMD等四种方法处理,四种方法对噪音信号均有不同程度的去噪效果,对比结果显示互补集合经验模态分解方法的信噪比较高,均方误差较小,去噪效果较好。
The fault diagnosis technology of CNC machine tools can effectively improve the operation of the equipment,and the noise signal is one of the inputs of its fault diagnosis,and its excellent denoising effect has laid the foundation for the fault diagnosis of CNC machine tools.Based on this,proposes a noise signal processing method based on complementary ensemble empirical mode decomposition.By using wavelet packet,CEEMD and other four methods to process the noise signal,the four methods have different degrees of denoising effect on the noise signal.The comparison results show that the signal-to-noise ratio of the complementary ensemble empirical mode decomposition method is high,the mean square error is small,and the denoising effect is better.
作者
郭双双
田军委
张震
孙光宇
Guo Shuangshuang;Tian Junwei;Zhang Zhen;Sun Guangyu(School of Mechanical and Electrical Engineering,Xi'an Technological University,Xi'an 710021,China)
出处
《科学技术创新》
2022年第32期41-44,共4页
Scientific and Technological Innovation
关键词
互补集合经验模态分解
噪音信号
数控机床
complete ensemble empirical mode decomposition
noise signal
CNC machine tool
