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EMD与cICA方法在多级齿轮传动微弱故障特征提取中的应用

冷军发 牛振华 荆双喜 王志阳

冷军发, 牛振华, 荆双喜, 王志阳. EMD与cICA方法在多级齿轮传动微弱故障特征提取中的应用[J]. 机械科学与技术, 2017, 36(7): 1029-1034. doi: 10.13433/j.cnki.1003-8728.2017.0708
引用本文: 冷军发, 牛振华, 荆双喜, 王志阳. EMD与cICA方法在多级齿轮传动微弱故障特征提取中的应用[J]. 机械科学与技术, 2017, 36(7): 1029-1034. doi: 10.13433/j.cnki.1003-8728.2017.0708
Leng Junfa, Niu Zhenhua, Jing Shuangxi, Wang Zhiyang. Weak Fault Feature Extraction of Multi-stage Gear Transmission based on EMD and Cica[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(7): 1029-1034. doi: 10.13433/j.cnki.1003-8728.2017.0708
Citation: Leng Junfa, Niu Zhenhua, Jing Shuangxi, Wang Zhiyang. Weak Fault Feature Extraction of Multi-stage Gear Transmission based on EMD and Cica[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(7): 1029-1034. doi: 10.13433/j.cnki.1003-8728.2017.0708

EMD与cICA方法在多级齿轮传动微弱故障特征提取中的应用

doi: 10.13433/j.cnki.1003-8728.2017.0708
基金项目: 

国家自然科学基金项目(U1304523)与河南理工大学博士基金项目(B2017-28)资助

详细信息
    作者简介:

    冷军发(1974-),副教授,博士研究生,研究方向为机械振动及故障诊断,lengjf@hpu.edu.cn

Weak Fault Feature Extraction of Multi-stage Gear Transmission based on EMD and Cica

  • 摘要: 为提取多级齿轮传动单通道测量信号中隐含的微弱低频故障特征信息,提出了一种基于经验模态分解(Empirical mode decomposition,EMD)与约束独立分量分析(Constrained independent component analysis,cICA)相结合的故障特征提取方法。首先对实测的齿轮箱单通道测量信号进行EMD分解;然后计算各个本征模态函数(Intrinsic mode function,IMF)的峭度及其与原信号的互相关系数,并选择合适的IMFs分量与原信号组成新的虚拟观测向量;最后,通过构建合适的参考信号进行cICA分析,提取出了理想的微弱低频故障特征。通过多级齿轮传动中的低速级断齿故障特征提取试验分析,验证了该方法的有效性和适用性。
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出版历程
  • 收稿日期:  2016-01-06
  • 刊出日期:  2017-07-05

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