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复选降噪自适应型MCKD方法研究

张旭龙 姜宏 章翔峰 李军 申勇

张旭龙,姜宏,章翔峰, 等. 复选降噪自适应型MCKD方法研究[J]. 机械科学与技术,2022,41(12):1822-1828 doi: 10.13433/j.cnki.1003-8728.20200526
引用本文: 张旭龙,姜宏,章翔峰, 等. 复选降噪自适应型MCKD方法研究[J]. 机械科学与技术,2022,41(12):1822-1828 doi: 10.13433/j.cnki.1003-8728.20200526
ZHANG Xulong, JIANG Hong, ZHANG Xiangfeng, LI Jun, SHEN Yong. Study on Adaptive MCKD Method for Noise Reduction by Reselection[J]. Mechanical Science and Technology for Aerospace Engineering, 2022, 41(12): 1822-1828. doi: 10.13433/j.cnki.1003-8728.20200526
Citation: ZHANG Xulong, JIANG Hong, ZHANG Xiangfeng, LI Jun, SHEN Yong. Study on Adaptive MCKD Method for Noise Reduction by Reselection[J]. Mechanical Science and Technology for Aerospace Engineering, 2022, 41(12): 1822-1828. doi: 10.13433/j.cnki.1003-8728.20200526

复选降噪自适应型MCKD方法研究

doi: 10.13433/j.cnki.1003-8728.20200526
基金项目: 国家自然科学基金项目(51765061)
详细信息
    作者简介:

    张旭龙(1996−),硕士研究生,研究方向为设备状态监测与故障诊断方面的研究,1357463213@qq.com

    通讯作者:

    姜宏,教授,博士生导师,onlyxjjh@xju.edu.cn

  • 中图分类号: TK83

Study on Adaptive MCKD Method for Noise Reduction by Reselection

  • 摘要: 针对强噪声干扰下,最大相关峭度解卷积(Maximum correlation kurtosis deconvolution,MCKD)对于弱响应轴承滚动体故障信号指定周期冲击增强和辨识能力有限,无法自适应确定参数的问题,提出一种改进MCKD故障诊断方法。首先利用小波多尺度分解得到故障响应高频分量使冲击成份更加凸显;然后以峭度值最大准则复选出最优故障信号高频分量,降低噪音的干扰;最后结合小波方差自适应确定MCKD参数。轴承故障仿真、实验数据分析结果表明,该方法能够实现弱响应的轴承滚动体故障诊断,同时适用轴承内外圈故障诊断。
  • 图  1  轴承故障诊断流程图

    图  2  故障仿真信号时域图和频域图

    图  3  仿真信号高频分量

    图  4  滤波信号包络谱

    图  5  试验平台

    图  6  滚动体故障原始信号时域图和频域图

    图  7  滚动体故障信号高频分量

    图  8  滚动体故障信号滤波后包络谱

    图  9  对比方法一、滤波包络

    图  10  对比方法二、滤波包络

    图  11  故障信号滤波包络

    表  1  仿真信号高频分量峭度

    分量 12345
    峭度K2.903.153.623.584.58
    下载: 导出CSV

    表  2  轴承参数

    内圈直径外圈直径滚动体个数接触角
    25 mm52 mm9
    下载: 导出CSV

    表  3  滚动体故障信号高频分量峭度

    分解层数12345
    峭度K 3.053.183.513.773.92
    下载: 导出CSV
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  • 被引次数: 0
出版历程
  • 收稿日期:  2020-12-06
  • 网络出版日期:  2023-02-16
  • 刊出日期:  2022-12-05

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