欢迎访问机床与液压官方网站!

咨询热线:020-32385312 32385313 RSS EMAIL-ALERT
基于小波奇异性检测技术的滚动轴承早期故障诊断研究
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

国家自然科学基金资助项目(11174299);广州航海学院科研基金资助项目(2011121303)


Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    轴承早期故障的检测与诊断是实现安全生产、预防恶性事故的有效手段。用高精度加速度传感器采集轴承振动信号,采用小波软阈值降噪法剔除测试过程的噪声,提高采集信号的信噪比。基于小波变换奇异值检测技术,探讨了提取淹没在噪声背景中的早期故障特征的方法,同时指出了传统傅里叶变换的不足。研究表明,该方法是有效的,所提取的故障特征频率与理论计算的故障特征频率基本相同。研究结果为轴承早期故障检测与诊断提供了新途径。

    Abstract:

    The diagnosis of incipient fault of rolling bearing is the effective measure to realize safety production and to avoid major accident. By using high precision accelerometer to collect the vibration signals of bearing, the wavelet soft threshold noise reduction method was used to eliminate noise so as to enhance signal noise ration (SNR) of collected signal. Based on wavelet singularity detection technology, the extraction of initial fault characteristics submerged in noise background method was discussed, at the same time the shortcomings of traditional Fourier transform were pointed out. Research shows that the method is effective, the extraction of fault feature frequency and the fault characteristic frequency from theoretical calculation are basically the same. Research results provide a new way for incipient fault detection and diagnosis of rolling bearing. 

    参考文献
    相似文献
    引证文献
引用本文

曾新红,白明,苏一丹,杨咪.基于小波奇异性检测技术的滚动轴承早期故障诊断研究[J].机床与液压,2015,43(3):185-188.
.[J]. Machine Tool & Hydraulics,2015,43(3):185-188

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2015-06-17
  • 出版日期: