机械科学与技术2017，Vol.36Issue(11)：1695-1700,6.DOI:10.13433/j.cnki.1003-8728.2017.1110
遗传算法VMD参数优化与小波阈值轴承振动信号去噪分析
Denoising Analysis of Bearing Vibration Signal based on Genetic Algorithm and Wavelet Threshold VMD
摘要
Abstract
Aiming at the extraction of useful fault feature information from bearing vibration signal affected by the noise,the variational mode decomposition (VMD) and wavelet threshold denoising method based on genetic algorithm is proposed.The method firstly utilizes genetic algorithm selecting appropriate parameters of the VMD,then the noise signal is decomposed adaptively by VMD method,finally processing the modes of decomposition respectively by wavelet threshold method,restructuring the signal to get denoised signal.Experimental results on actual bearing signals show that the proposed method can obtain higher signal-to-noise ratio and lower mean square deviation compared with several common denoising methods.关键词
遗传算法/变分模态分解/小波阈值去噪Key words
genetic algorithm/variational mode decomposition/wavelet threshold denoising分类
机械制造引用本文复制引用
刘嘉敏,彭玲,刘军委,袁佳成..遗传算法VMD参数优化与小波阈值轴承振动信号去噪分析[J].机械科学与技术,2017,36(11):1695-1700,6.基金项目
中央高校基本科研业务费资助项目(1061120131207)与重庆市研究生科研创新项目(CYS14028)资助 （1061120131207）
