Research of Fault Diagnosis Method of Multi Low Speed High-loaded Bearings Installed on Same Axis

Han Jiahua; Yan Wen; Cao Jinhua

doi:10.16578/j.issn.1004.2539.2018.04.032

您当前的位置：

首页 >

文章列表页 >

Research of Fault Diagnosis Method of Multi Low Speed High-loaded Bearings Installed on Same Axis

更新时间：2022-10-20

- Research of Fault Diagnosis Method of Multi Low Speed High-loaded Bearings Installed on Same Axis
- Vol. 42, Issue 4, Pages: 164-169(2018)
- 作者机构：
  
  1. 军械工程学院火炮工程系
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2018.04.032
  CLC：
扫描看全文
[1]韩嘉华,阎文,曹进华.多个低速重载轴承同轴安装状态下故障诊断方法研究[J].机械传动,2018,42(04):164-169.

Han Jiahua, Yan Wen, Cao Jinhua. Research of Fault Diagnosis Method of Multi Low Speed High-loaded Bearings Installed on Same Axis. [J]. 42(4):164-169(2018)
[1]韩嘉华,阎文,曹进华.多个低速重载轴承同轴安装状态下故障诊断方法研究[J].机械传动,2018,42(04):164-169. DOI： 10.16578/j.issn.1004.2539.2018.04.032.

Han Jiahua, Yan Wen, Cao Jinhua. Research of Fault Diagnosis Method of Multi Low Speed High-loaded Bearings Installed on Same Axis. [J]. 42(4):164-169(2018) DOI： 10.16578/j.issn.1004.2539.2018.04.032.

摘要

多个低速重载轴承同轴安装时,不同位置产生的故障脉冲会出现混叠耦合现象,导致故障信号难以诊断。提出基于角域特征量,将全矢谱技术和经验模态分解（Empirical mode decomposition,简称EMD）相结合,进行低速重载轴承故障信号的振源识别与诊断。首先,采用样条插值算法,进行角域重采样,将时域非平稳信号转化为角域伪平稳化信号,提取角域特征参量轴承接触转角,实现信号的振源识别;然后,运用全矢EMD进行信号分解与重构和同源信息融合;最后,对融合后重构信号进行倒角域分析,提取特征参量单圈接触次数,完成信号的故障类型诊断。通过实验分析验证,结果表明,基于角域特征量和全矢EMD的故障诊断方法能在一定程度上满足低速重载轴承故障信号诊断要求,具有一定的实用性。

Abstract

The multi low speed,high-loaded bearing installed on same axis,different locations of the bearing fault pulse will appear aliasing coupling phenomenon,resulting in fault signal identification difficult. In this regard,based on the characteristic of corner-domain and full vector empirical mode decomposition to identify and diagnose the vibration source of the low speed,high-loaded bearing fault signal is proposed. Firstly,the spline interpolation algorithm is used to transform the acquired time domain nonstationary signal into the angular pseudo-stationary signal to realize the angular area resampling,extract the contact angle of rotation of bearing,and the vibration source recognition is completed. Then,the signal is decomposed and reconstructed by EMD,the dual-channel full-spectrum technique is used to fuse the homologous information. Finally,the fault is identified by after chamfering domain analysis of the reconstructed signal,extract the characteristic parameters of contact times of per circle to complete the signal fault type diagnosis. The experimental results show that the fault diagnosis method based on characteristic of corner-domain and full vector EMD can satisfy the requirement of low speed,high-loaded fault signal diagnosis to a certain extent,and it has certain practicability.

关键词

混叠耦合角域特征量全矢EMD故障诊断

Keywords

Aliasing couplingCharacteristic of corner-domainFull vector empirical mode decompositionFault diagnosis

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Bearing Feature Extraction Method Based on the Time Subsequence

A Fault Feature Extraction Method of Rolling Bearings Based on Optimized VMD and UMAP

Research on Fault Diagnosis Method of Planetary Gearboxes Based on DPD-1DCNN

Review on Fault Diagnosis Technology for High-speed EMU Gearboxes

Research on Gear Early Wear Fault Diagnosis Based on the Sparse Attention Mechanism

Related Author

No data

Related Institution

School of Information Management, Wuxi Institute of Communications Technology

IOT Engineering College, Wuxi City College of Vocational Technology

State Key Laboratory of Traction Power, Southwest Jiaotong University

School of Rail Transportation, Wuyi University

College of Mechanical and Vehicle Engineering, Taiyuan University of Technology

⁰