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基于cICA的旋转机械变速过程滚动轴承故障特征提取

吴川辉 郭瑜 梁瑜

吴川辉, 郭瑜, 梁瑜. 基于cICA的旋转机械变速过程滚动轴承故障特征提取[J]. 机械科学与技术, 2013, 32(8): 1176-1181.
引用本文: 吴川辉, 郭瑜, 梁瑜. 基于cICA的旋转机械变速过程滚动轴承故障特征提取[J]. 机械科学与技术, 2013, 32(8): 1176-1181.
Wu Chuanhui, Guo Yu, Liang Yu. Extracting Fault Features of R olling Bearing During Speed Variation Based on cICA[J]. Mechanical Science and Technology for Aerospace Engineering, 2013, 32(8): 1176-1181.
Citation: Wu Chuanhui, Guo Yu, Liang Yu. Extracting Fault Features of R olling Bearing During Speed Variation Based on cICA[J]. Mechanical Science and Technology for Aerospace Engineering, 2013, 32(8): 1176-1181.

基于cICA的旋转机械变速过程滚动轴承故障特征提取

基金项目: 

教育部留学回国人员科研启动基金项目(教外司留[2009]1590号)资助

详细信息
    作者简介:

    吴川辉(1987-),硕士研究生,研究方向为旋转机械故障诊断和虚拟仪器设计,km-bruce@163.com;郭瑜(联系人),教授,博士,kmgary@163.com

    吴川辉(1987-),硕士研究生,研究方向为旋转机械故障诊断和虚拟仪器设计,km-bruce@163.com;郭瑜(联系人),教授,博士,kmgary@163.com

Extracting Fault Features of R olling Bearing During Speed Variation Based on cICA

  • 摘要: 在ICA基础上发展起来的约束独立分量分析(cICA)方法,可根据一定的先验知识生成参考信号以提取选定的独立分量,解决了原ICA算法的次序不确定性问题。将cICA用于滚动轴承故障诊断,能够根据被监测滚动轴承的特征频率等先验信息建立参考信号并实现对其故障振动特征信号的提取。本文将该方法与针对旋转机械变速过程的阶比跟踪技术和滚动轴承包络分析技术相结合,提出了基于cICA的旋转机械变速工作过程滚动轴承早期故障分析方法。该方法首先通过包络提取技术在共振带获得包含故障信息的包络信号,再通过阶比分析中的等角度采样将包络信号转换到角域,在角域建立参考信号,并用cICA实现旋转机械变速过程下滚动轴承故障对应冲击性信号成分的有效提取。仿真和测试试验表明,所提出方法适合于旋转机械升降速等变速过程中的滚动轴承初期故障特征信息提取。
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  • 收稿日期:  2012-06-25

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