基于强抗噪威格纳威利分析的滚动轴承故障诊断

王宏超; 杜文辽

doi:10.13224/j.cnki.jasp.2019.04.005

基于强抗噪威格纳威利分析的滚动轴承故障诊断

doi: 10.13224/j.cnki.jasp.2019.04.005

王宏超^1,2,
杜文辽^1,2

1.
郑州轻工业大学机电工程学院,郑州 450002
2.
郑州轻工业学院机电工程学院河南省机械装备智能制造重点实验室,郑州 450002

基金项目: 河南省教育厅人才项目(17HASTIT028)

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出版历程
- 收稿日期: 2018-04-08
- 刊出日期: 2019-04-28

Fault diagnosis of rolling bearing based on noise-resistant Wigner-Vile analysis

摘要

摘要: 为了解决威格纳威利谱(Wigner-Vile spectrum, WVS)时频分析方法对受强背景噪声影响下的滚动轴承冲击性故障信号特征提取难的问题，根据滚动轴承发生故障时呈现出的循环平稳特征，将基于2阶循环统计量的循环谱密度算法(cyclic spectral density, CSD)与WVS相结合，提出基于CSD的WVS分析方法，即循环谱密度威格纳威利谱(CSDWVS)时频分析方法。经仿真及实验验证，相对传统WVS分析方法，该方法能有效提取出强背景噪声影响下的滚动轴承内圈故障特征频率为51.9 Hz及外圈故障特征频率为32.1 Hz。
- 循环平稳 /
- 威格纳威利谱(WVS) /
- 故障诊断 /
- 循环谱密度(CSD) /
- 循环谱密度威格纳威利谱(CSDWVS)
Abstract: To solve the problem that the time-frequency analysis method Wigner-Vile spectrum (WVS) could not extract the fault feature effectively when the impulsion characteristic fault signal of rolling element bearing is buried by strong background noise, the cyclic spectral density Wigner-Vile spectrum (CSDWVS) time-frequency method was proposed based on the property of cyclostationarity of the bearing’ fault signal by combing the cyclic spectral density (CSD) based on second order cyclostationarity statistics with the WVS. Through the verification of simulation and test, the proposed method had the much more noise-resistant advantages than traditional WV method, and it could extract the inner race fault characteristic frequency of 51.9 Hz and the outer race fault characteristic frequency of 32.1 Hz correctly.
- cyclostationarity /
- Wigner-Vile spectrum(WVS) /
- fault diagnosis /
- cyclic spectral density(CSD) /
- cyclic spectral density Wigner-Vile spectrum (CSDWVS)

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参考文献(18)

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