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遗传算法VMD参数优化与小波阈值轴承振动信号去噪分析

刘嘉敏 彭玲 刘军委 袁佳成

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. doi: 10.13433/j.cnki.1003-8728.2017.1110
引用本文: 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. doi: 10.13433/j.cnki.1003-8728.2017.1110
Liu Jiamin, Peng Ling, Liu Junwei, Yuan Jiacheng. Denoising Analysis of Bearing Vibration Signal based on Genetic Algorithm and Wavelet Threshold VMD[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(11): 1695-1700. doi: 10.13433/j.cnki.1003-8728.2017.1110
Citation: Liu Jiamin, Peng Ling, Liu Junwei, Yuan Jiacheng. Denoising Analysis of Bearing Vibration Signal based on Genetic Algorithm and Wavelet Threshold VMD[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(11): 1695-1700. 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

doi: 10.13433/j.cnki.1003-8728.2017.1110
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

详细信息
    作者简介:

    刘嘉敏(1973-),副教授,博士,研究方向为信号和模式识别,liujm@cpu.edu.cn

Denoising Analysis of Bearing Vibration Signal based on Genetic Algorithm and Wavelet Threshold VMD

  • 摘要: 针对轴承振动信号夹杂的噪声极大地影响有用信息的提取,提出了基于遗传算法的变分模态分解(Variational mode decomposition,VMD)与小波阈值去噪方法。该方法首先利用遗传算法选择合适的VMD参数,然后用VMD方法对含噪声的信号进行自适应分解,最后对分解的模态分别进行小波阈值处理后重构信号,得到去噪后的信号。对实际轴承信号的分析结果表明,该方法与常用的去噪方法相比,能够得到更高的信噪比和更低的均方差。
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出版历程
  • 收稿日期:  2016-07-30
  • 刊出日期:  2017-11-05

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