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基于Morlet小波变换的信号去噪及在轴承状态监测中的应用

马伦 康建设 赵春宇 吕雷

马伦, 康建设, 赵春宇, 吕雷. 基于Morlet小波变换的信号去噪及在轴承状态监测中的应用[J]. 机械科学与技术, 2014, 33(9): 1345-1349. doi: 10.13433/j.cnki.1003-8728.2014.0913
引用本文: 马伦, 康建设, 赵春宇, 吕雷. 基于Morlet小波变换的信号去噪及在轴承状态监测中的应用[J]. 机械科学与技术, 2014, 33(9): 1345-1349. doi: 10.13433/j.cnki.1003-8728.2014.0913
Ma Lun, Kang Jianshe, Zhao Chunyu, L�Lei. Morlet Wavelet Transform-based Signal De-noising and its Application in Bearing Condition Monitoring[J]. Mechanical Science and Technology for Aerospace Engineering, 2014, 33(9): 1345-1349. doi: 10.13433/j.cnki.1003-8728.2014.0913
Citation: Ma Lun, Kang Jianshe, Zhao Chunyu, L�Lei. Morlet Wavelet Transform-based Signal De-noising and its Application in Bearing Condition Monitoring[J]. Mechanical Science and Technology for Aerospace Engineering, 2014, 33(9): 1345-1349. doi: 10.13433/j.cnki.1003-8728.2014.0913

基于Morlet小波变换的信号去噪及在轴承状态监测中的应用

doi: 10.13433/j.cnki.1003-8728.2014.0913
详细信息
    作者简介:

    马伦(1985-),博士研究生,研究方向为维修工程理论与应用和故障预测与健康管理,malun018@163.com;康建设(联系人),教授,博士,博士生导师,zc_lcy@yahoo.cn

    马伦(1985-),博士研究生,研究方向为维修工程理论与应用和故障预测与健康管理,malun018@163.com;康建设(联系人),教授,博士,博士生导师,zc_lcy@yahoo.cn

Morlet Wavelet Transform-based Signal De-noising and its Application in Bearing Condition Monitoring

  • 摘要: 为在强噪声背景下利用振动信号中隐含的冲击特征成分来反映轴承性能退化趋势,提出一种基于Morlet小波变换和时域特征参数提取相结合的轴承状态监测方法。通过引入谱峭度评估Morlet小波滤波的去噪效果,再从信号滤波结果构建的组合信息中提取时域特征参数。对轴承全寿命数据的应用结果表明,特征参数的变化趋势能够监测轴承状态的劣化过程,伴随的早期故障检测可以提高轴承使用的安全性。
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  • 收稿日期:  2013-03-30

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