中国机械工程2018，Vol.29Issue(5)：585-590,6.DOI:10.3969/j.issn.1004-132X.2018.05.013
基于同步压缩小波变换的滚动轴承故障诊断
Fault Diagnosis for Rolling Bearings Based on Synchrosqueezing Wavelet Transform
刘义亚 1李可 2陈鹏1
作者信息
- 1. 江南大学江苏省食品先进制造装备技术重点实验室,无锡,214122
- 2. 江南大学机械工程学院,无锡,214122
- 折叠
摘要
Abstract
In order to overcome the difficulties of feature extraction of non-stationary faulty sig-nals in rolling bearing fault diagnosis,this paper proposed a fault feature extraction method by using the synchrosqueezing wavelet transform (SWT).Firstly,the measured vibration signals were pro-cessed with the continuous wavelet transform (CWT),and the wavelet transform coefficients were subj ected to synchrosqueezing transform (SST).Moreover,an adaptive threshold denoising technolo-gy was presented to cancel noises of the SST coefficients,and the effective signal data near the center of the frequency were extracted by integrating.Finally,the signal reconstruction was carried out by u-tilizing the extracted effective signals.The simulation and the equipment tests were designed to verify the effectiveness proposed methods herein.The test results show that SWT has a high signal extrac-tion accuracy and noise reduction capability.SWT also has higher time-frequency resolution,which may convert the fault signals into high-resolution time-frequency spectrum and make up for the lacks of CWT.关键词
故障诊断/同步压缩变换/故障信号提取/自适应阈值去噪Key words
fault diagnosis/synchrosqueezing transform/faulty signal extraction/adaptive threshold denoising分类
机械制造引用本文复制引用
刘义亚,李可,陈鹏..基于同步压缩小波变换的滚动轴承故障诊断[J].中国机械工程,2018,29(5):585-590,6.
