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

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

新疆大学机械工程学院，乌鲁木齐　830047

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
计量
- 文章访问数: 216
- HTML全文浏览量: 84
- PDF下载量: 24
- 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

Study on Adaptive MCKD Method for Noise Reduction by Reselection

School of Mechanical Engineering, Xinjiang University, Urumqi 830047, China

摘要

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。
- 最大相关峭度解卷积 /
- 峭度 /
- 小波方差 /
- 自适应 /
- 滚动轴承
Abstract: In order to solve the problem that the maximum correlation kurtosis deconvolution (MCKD) is unable to adaptively determine parameters due to its limited ability to specify periodic impact enhancement for bearing rolling element fault signals with weak response under strong noise interference, an improved MCKD fault diagnosis method was proposed in this paper. First, the high frequency component of fault response is obtained by wavelet multi-scale decomposition to make the impact component more prominent; then the optimal high-frequency component of fault signal is reselected by the maximum kurtosis criterion to reduce the noise interference; finally, the MCKD parameters are determined by wavelet variance adaptive. Bearing fault simulation and experimental data analysis show that this method can realize the fault diagnosis of bearing rolling element with weak response, and is suitable for the fault diagnosis of bearing inner and outer ringsunder strong noise interference.
- MCKD /
- kurtosis criterion /
- wavelet variance /
- self-adaption /
- rolling bearing

HTML全文

图 1 轴承故障诊断流程图

下载: 全尺寸图片幻灯片

图 2 故障仿真信号时域图和频域图

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图 3 仿真信号高频分量

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图 4 滤波信号包络谱

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图 5 试验平台

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图 6 滚动体故障原始信号时域图和频域图

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图 7 滚动体故障信号高频分量

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图 8 滚动体故障信号滤波后包络谱

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图 9 对比方法一、滤波包络

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图 10 对比方法二、滤波包络

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图 11 故障信号滤波包络

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表 1 仿真信号高频分量峭度

分量　 1 2 3 4 5

峭度K 2.90 3.15 3.62 3.58 4.58

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 mm 52 mm 9 0°

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表 3 滚动体故障信号高频分量峭度

分解层数 1 2 3 4 5

峭度K　 3.05 3.18 3.51 3.77 3.92

下载: 导出CSV

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