• CN:11-2187/TH
  • ISSN:0577-6686

›› 2008, Vol. 44 ›› Issue (11): 160-165.

• 论文 • 上一篇    下一篇

滚动轴承故障信号的多尺度形态学分析

郝如江;卢文秀;褚福磊   

  1. 清华大学精密仪器与机械学系;石家庄铁道学院计算机与信息工程分院
  • 发布日期:2008-11-15

Multiscale Morphological Analysis on Fault Signals of Rolling Element Bearing

HAO Rujiang;LU Wenxiu;CHU Fulei   

  1. Department of Precision Instruments and Mechanology, Tsinghua University Computer and Information Engineering Department, Shijiazhuang Railway Institute
  • Published:2008-11-15

摘要: 数学形态分析是数字信号处理的一种非线性分析方法,滚动轴承故障信号是一种非线性非平稳信号。为了提取不同类型故障特征,利用多尺度形态学分析对滚动轴承故障振动信号建立一种不同于时频分析的信号特征描述方法。采用多尺度形态开运算得到故障信号的形态谱,定量反映了信号在不同尺度下的形态变化特征;由形态谱曲线计算形态谱熵,定量描述不同信号的形态特征。通过试验数据的分析以及与峭度和共振包络解调方法的对比,表明多尺度形态学分析方法计算效率高,特征描述准确简单,为轴承故障信号的分析、识别和分类提供了新的思路。

关键词: 故障, 滚动轴承, 形态谱, 形态谱熵

Abstract: The mathematical morphological analysis is a nonlinear analysis method of digital signal processing. The multiscale morphology analysis can describe the signals by layers depending on the varying structure elements. By morphological opening operation, a new method describing the rolling bearing faults characteristics is presented, which is not different from the time-frequency analysis. The mathematical morphological spectrum curves are created by multiscale morphological opening algorithm with varying flat structure elements, which could quantitatively show the different faults characteristics. The morphology spectrum entropies are gained by means of the morphology spectrum values according to the information theory, which quantitatively represented the shape characteristics. From the analysis of experimental data, it can be seen that the multiscale morphology method is a new idea for the faults extraction and classification of rotating machines.

Key words: Fault, Morphological spectrum, Morphological spectrum entropy, Rolling bearing

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