基于信号序列差分的EMD及其在轴承故障诊断中的应用
EMD Based on Signal Sequence Difference and Its Application in Bearing Fault Diagnosis
李宁1
作者信息
- 1. 中国铁路青藏集团有限公司机务部,青海 西宁 810000
- 折叠
摘要
随着现代数字信号处理技术的发展,在工程实践中实现了轴承在线状态监控和故障早期预警,预防了轴承故障突然发生.对信号序列进行差分运算降低原始信号序列不平稳性和随机性,利用经验模态分解对信号序列进行处理,提取出各阶频率较为单一的本征模态函数,再通过希尔伯特变换提取到轴承故障特征,从而验证了该方法的有效性.
Abstract
With the development of modern digital signal processing technology,on-line condition monitoring and fault early warning of mechanical equipment are realized in engineering practice which prevent the sudden failure of bearing.The article performs differential operation on the signal sequence to reduce the instability and randomness of the original signal sequence,and the empirical mode decomposition is used to decompose the signal sequence to extract the intrinsic mode functions with relatively single frequencies of each order,and then the bearing fault characteristics is extracted by Hilbert transform which verify the effectiveness of this method.
关键词
经验模态分解/差分/信号序列/希尔伯特变换/轴承故障诊断Key words
empirical modal decomposition/differential/signal sequence/Hilbert transform/bearing fault diagnosis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据