Fault diagnosis of rolling bearing based on improved Autogram

  • LIU Shangkun ,
  • ZHANG Wei ,
  • SUN Yuhao ,
  • KONG Degang ,
  • ZHAO Xiaoshun
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  • School of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071001, China

Received date: 2023-05-06

  Online published: 2024-03-15

Abstract

To address the problem of inaccurate selection of demodulation frequency band and difficulty in fault diagnosis that may arise when using the unbiased autocorrelation kurtosis index, the square envelope negentropy is introduced into Autogram, and an improved Autogram method using square envelope negentropy index is proposed to select the optimal demodulation frequency band. The square envelope negentropy is less affected by noise and can measure the impact of period signal. Firstly, the bearing vibration signal is decomposed into different frequency bands by maximum overlapping discrete wavelet packet transform. Then the square envelope negentropy of each frequency band is calculated, and the optimal frequency band which has the maximum square envelope negentropy value is selected. Finally, the bearing fault type is diagnosed by analyzing the square envelope spectrum of the optimal demodulation frequency band. The analysis results of fault bearing experimental signals by improved Autogram, Autogram, and fast kurtogram method showed that the improved Autogram method is more reasonable in the selecting demodulation frequency band, and more obvious in extracting fault frequency, and more accurately in diagnosing bearing faults.- DOI:10.3969/j.issn.1000-1565.2024.01.001基于改进Autogram的滚动轴承故障诊断刘尚坤,张伟,孙宇浩,孔德刚,赵晓顺(河北农业大学 机电工程学院,河北 保定 071001)摘 要:针对Autogram以无偏自相关峭度指标选取解调频带时易出现不准确、故障诊断困难的问题,将平方包络负熵引入Autogram中,结合平方包络负熵受噪声影响小且能衡量周期冲击成分的优点,提出一种采用平方包络负熵指标选取最优解调频带的改进Autogram方法.首先采用最大重叠离散小波包变换(MODWPT)对轴承振动信号进行频带分解,再计算每个频带信号的平方包络负熵,将平方包络负熵最大的频带作为最优解调频带,最后通过分析最优解调频带平方包络谱的频率成分来诊断轴承故障类型.将轴承故障实验信号分析结果与Autogram、快速谱峭度方法对比,结果表明,改进Autogram方法在解调频带的选取上更为合理,所提取的故障特征频率更明显,轴承故障诊断更准确.关键词:平方包络负熵;改进Autogram;最优解调频带;故障诊断中图分类号:TH133.33 文献标志码:A 文章编号:1000-1565(2024)01-0001-08Fault diagnosis of rolling bearing based on improved AutogramLIU Shangkun, ZHANG Wei, SUN Yuhao, KONG Degang, ZHAO Xiaoshun(School of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071001, China)Abstract: To address the problem of inaccurate selection of demodulation frequency band and difficulty in fault diagnosis that may arise when using the unbiased autocorrelation kurtosis index, the square envelope negentropy is introduced into Autogram, and an improved Autogram method using square envelope negentropy index is proposed to select the optimal demodulation frequency band. The square envelope negentropy is less affected by noise and can measure the impact of period signal. Firstly, the bearing vibration signal is decomposed into different frequency bands by maximum overlapping discrete wavelet packet transform. Then the square envelope negentropy of each frequency band is calculated, and the optimal frequency band which has the maximum square envelope negentropy value is selected. Finally, the bearing fault type is diagnosed by analyzing the square envelope spectrum of the optimal demodulation frequency band. The analysis results of fault bearing experimental signals by improved Autogram, Autogram, and fast kurtogram method showed that the improved Autogram method is more reasonable in the selecting demodulation frequency band, and more obvious in extracting fault frequency, and more accurately in diagnosing bearing faults.- 收稿日期:2023-05-06;修回日期:2023-09-20 基金项目:河北省重点研发计划项目(22327206D);保定市科技计划项目(2172P003);河北省省属高校基本科研业务费资助项目(KY202014);河北农业大学引进人才科研专项(YJ201814) 第一作者:刘尚坤(1979—),男,河北农业大学副教授,博士,主要从事机械设备状态监测与故障诊断方向研究.E-mail:lsk1213@163.com 通信作者:孔德刚(1986—),男,河北农业大学讲师,主要从事机械设计制造及故障诊断方向研究.E-mail:870714576@qq.com第1期刘尚坤等:基于改进Autogram的滚动轴承故障诊断

Cite this article

LIU Shangkun , ZHANG Wei , SUN Yuhao , KONG Degang , ZHAO Xiaoshun . Fault diagnosis of rolling bearing based on improved Autogram[J]. Journal of Hebei University(Natural Science Edition), 2024 , 44(1) : 1 -8 . DOI: 10.3969/j.issn.1000-1565.2024.01.001

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