基于经验模态分解停止准则的振动筛轴承故障诊断
Fault Diagnosis of Vibrating Screen Bearing Based on Empirical Modal Decomposition Stopping Criterion
刘港 1熊继芬1
作者信息
- 1. 广西机电职业技术学院交通工程学院,广西 南宁 520007
- 折叠
摘要
在数控振动筛运行速度大幅增加对轴承的运行稳定性提出了更高的要求,分析其故障信号并及时诊断是关键.为了弥补经验模态分解EMD方法依然有着模态混叠、包络过度以及包络不足等问题,筛分引入分解停止准则对其迭代计算进行加强,设计了一种基于经验模态分解停止准则的轴承故障诊断方法.通过仿真信号分析得到,该方法得到较少的本征模态函数(IMF)和均方根差(RMSE)数值,在算法时间层面具有优势性.所提方式在噪声较大的环境下对于分解信号有着较强的鲁棒性.
Abstract
In the numerical control vibrating screen running speed greatly increased on the bearing operation stability puts forward higher requirements,the analysis of its fault signal and timely diagnosis is the key.In order to make up for the empirical modal decomposition EMD method still has the problems of modal overlapping,excessive envelope and insufficient envelope,the screen introduces the decomposition stopping criterion to strengthen its iterative calculation,and designs a bearing fault diagnosis method based on the empirical modal decomposition stopping criterion.It is obtained through simulation signal analysis that the method obtains fewer IMF and RMSE values,which is advantageous at the algorithmic time level.The proposed method is robust to decomposition of signals in noisy environments.
关键词
轴承/经验模态分解/筛分停止准则/故障诊断/鲁棒性Key words
bearings/empirical modal decomposition/screening stopping criterion/fault diagnosis/robustness引用本文复制引用
出版年
2024
NETL
NSTL
万方数据