戴含芳,王衍学,李志星.基于元素分析的滚动轴承故障诊断[J].电子测量与仪器学报,2022,36(1):157-165
基于元素分析的滚动轴承故障诊断
Fault diagnosis of rolling bearings based on elemental analysis
  
DOI:
中文关键词:  旋转机械  元素分析  Morse 小波  故障特征提取  信号重建
英文关键词:rotating machinery  elemental analysis  Morse wavelet  fault feature extraction  signal reconstruction
基金项目:国家自然科学基金项目(51875032)、北京市百千万人才项目、西城区拔尖创新团队和北京建筑大学2021年度研究生创新项目资助
作者单位
戴含芳 1. 北京建筑大学机电与车辆工程学院,2. 北京建筑大学城市轨道交通车辆服役性能保障重点实验室 
王衍学 1. 北京建筑大学机电与车辆工程学院,2. 北京建筑大学城市轨道交通车辆服役性能保障重点实验室 
李志星 1. 北京建筑大学机电与车辆工程学院 
AuthorInstitution
Dai Hanfang 1. School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture,2. Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing University of Civil Engineering and Architecture 
Wang Yanxue 1. School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture,2. Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing University of Civil Engineering and Architecture 
Li Zhixing 1. School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture 
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中文摘要:
      针对现有信号降噪或重构方法无法完全去除噪声,且时频表示存在能量模糊问题,提出了一种利用元素分析进行滚动 轴承故障诊断的方法。 所提方法首先构造了元素模型来表征信号,然后对元素模型进行 Morse 小波变换,并从小波变换中计算 得出信号冲击点,从而得到信号的故障特征频率。 该方法还可以利用基于小波变换中时间或尺度平面内的少量孤点来重构信 号。 最后,采用一组仿真信号数据和两组实验数据来评估所提方法性能,并与其他信号重构方法和时频分析方法对比,结果表 明,所提方法对滚动轴承故障信号重建和识别的效果更好。
英文摘要:
      Given the existing signal denoising or reconstruction methods can not completely remove the noise, and the time-frequency representation has the problem of energy ambiguity, a method for rolling bearing fault diagnosis based on element analysis was proposed. Firstly, the proposed method constructs an elemental model to characterize the signal, then the Morse wavelet transform is applied to the elemental model and the impact point of the signal is calculated from the wavelet transform to obtain the characteristic defect frequency of the signal. Based on a small number of solitary points in the time or scale plane of the wavelet transform, the method is used to reconstruct the signal. In this paper, a set of simulated signal data and two sets of experimental data are used to estimate the performance of the method and compare it with other signal reconstruction methods and time-frequency analysis methods. The results demonstrate that the proposed method has a good performance in the identification and reconstruction of rolling bearing fault signals.
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