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LIU Yabing, DU Yu. Fault diagnosis method for bearing of mine scraper conveyor based on spectral amplitude modulation[J]. Journal of Mine Automation, 2024, 50(S1): 126-129,186.
Citation: LIU Yabing, DU Yu. Fault diagnosis method for bearing of mine scraper conveyor based on spectral amplitude modulation[J]. Journal of Mine Automation, 2024, 50(S1): 126-129,186.
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Fault diagnosis method for bearing of mine scraper conveyor based on spectral amplitude modulation

  • Huayang New Material Technology Group Co., Ltd., Yangquan 045000, China

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  • Received Date: April 21, 2024
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    • References (18)
  • [1]
    朱伏平, 张又才, 杨方燕.基于全矢CEEMDAN能量矩和AMHSSA-SVM的滚动轴承故障诊断[J].机械设计, 2024, 41(2):81-87.
    [2]
    刘前进, 高丙朋, 宋振军, 等.基于参数优化变分模态分解的变速工况下轴承故障诊断[J].轴承, 2022(8):71-78.
    [3]
    张雪芹.多分量非平稳信号的时频分析方法研究[D].济南:山东大学, 2019.
    [4]
    郑小磊.基于增强的时频分析方法的变转速轴承故障诊断[J/OL].轴承:1-9[2024-03-07]. http://kns.cnki.net/kcms/detail/41.1148.TH.20231225.1542.002.html.
    [5]
    纪京生, 周莉, 马向阳.VMD结合小波包信息熵和GJO-SVM的电机轴承故障诊断[J].现代制造工程, 2024(2):128-136.
    [6]
    刘俊利, 缪炳荣, 张盈, 等.基于Morlet小波与CART决策树的滚动轴承故障诊断方法[J].机械强度, 2024, 46(1):1-8.
    [7]
    潘晓博, 葛鲲鹏, 钱孟浩, 等.基于改进联合分布适应的轴承智能故障诊断方法[J].机电工程, 2023, 40(9):1354-1362.
    [8]
    胡海彬, 刘仁鑫, 夏宇雯, 等.一种用离散多小波变换的可解释卷积神经网络在滚动轴承故障诊断中的应用[J/OL].机械科学与技术:1-10[2024-03-07]. https://doi.org/10.13433/j.cnki.1003-8728.20230365.
    [9]
    柳霞, 蒋淑霞, 张长伟, 等.时频特征降维和多层次聚类相结合的轴承故障诊断新方法[J].噪声与振动控制, 2023, 43(6):123-128.
    [10]
    王茂辉, 汤勇, 李海翔, 等.基于Morlet小波与尺度空间的滚动轴承故障诊断研究[J].机车电传动, 2021(3):132-139.
    [11]
    张春林, 吴允恒, 蔡克燊, 等.基于改进连续小波变换增强非凸正则项稀疏分解的滚动轴承变转速故障冲击特征提取方法[J/OL].机械工程学报:1-15[2024-03-07]. http://kns.cnki.net/kcms/detail/11.2187.TH.20240123.1116.010.html.
    [12]
    黄斯琪, 谭志银, 杨思国, 等.改进的傅里叶分解方法及其在滚动轴承故障诊断中的应用[J].振动与冲击, 2023, 42(12):178-186.
    [13]
    冯葛豪, 胥永刚, 孙国栋, 等.谱聚类傅里叶分解及其在轴承故障诊断中应用[J/OL].轴承:1-10[2024-03-07]. http://kns.cnki.net/kcms/detail/41.1148.th.20230923.0532.002.html.
    [14]
    郑直, 李显泽, 刘伟民, 等.基于log-SAM改进Autogram的滚动轴承故障诊断[J].现代制造工程, 2023(12):132-139.
    [15]
    姜祖华, 张坤, 杨苗蕊, 等.局部谱幅值调制及其滚动轴承故障诊断应用[J/OL].轴承:1-9[2024-03-07]. http://kns.cnki.net/kcms/detail/41.1148.TH.20231010.1104.002.html.
    [16]
    战欣, 刘卓娅.基于PSO-SES-BPNN算法的液压系统故障诊断模型[J].兵器装备工程学报, 2023, 44(4):172-178.
    [17]
    孙壮壮, 郑近德, 童靳于, 等.二维多尺度符号样本熵在滚动轴承故障诊断中的应用[J/OL].机械科学与技术:1-11[2024-03-07]. https://doi.org/10.13433/j.cnki.1003-8728.20230294.
    [18]
    卢太武, 马洪波, 王先芝, 等.时变工况下基于精细复合多尺度散度熵的旋转机械故障诊断方法[J].振动与冲击, 2023, 42(21):211-218.
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