摘要
为了更有效地对轴承故障进行监测和诊断,提出了一种基于同步压缩-交叉小波变换的滚动轴承故障特征增强方法。该方法首先将信号分成长度相等的两路信号,然后分别进行同步压缩小波变换,并将得到的同步压缩小波系数作为交叉小波变换的输入,进而获得交叉小波尺度谱,实现轴承故障特征频率的增强。将该方法应用于滚动轴承的故障诊断,与连续小波变换、交叉小波变换和同步压缩小波变换方法相比,所提方法可有效提取轴承在时频域内的细节特征,使轴承特征频率在时频域上的可读性增强,进而实现轴承故障的精确可靠诊断。
In order to more effectively monitor and diagnose bearing faults, an enhanced fault diagnosis method was proposed based on synchrosqueezing-cross wavelet transform（SXWT）. First, this method segmented the signal into two sub-signals with the same length. Then, using the synchrosqueezing wavelet transform（SWT） deals with the two sub-signals respectively, so as to obtain synchrosqueezing wavelet transform coefficients to be used as the input of cross wavelet transform（XWT）. Finally, the obtained cross wavelet scale spectrum was used to extract the characteristic frequency information, thus achieving the enhanced fault diagnosis of bearings. The method is applied to the bearing fault diagnosis. Compared with continuous wavelet transform（CWT）, XWT and SWT, the proposed method can effectively extract the detail characteristics of bearing signal in the time-frequency domain to enhance the readability of the bearing characteristics frequency in the time-frequency domain, and realize accurate and reliable diagnosis of the bearings faults.
出处
《计量学报》
CSCD
北大核心
2018年第2期237-241,共5页
Acta Metrologica Sinica
基金
国家自然科学基金(51505415)
河北省自然科学基金(F2016203421
F2017203142)
河北省高等学校科学技术研究重点项目(ZD20131080)
关键词
计量学
滚动轴承
同步压缩小波
交叉小波
故障诊断
metrology
rolling bearing
synchrosqueezing wavelet transform
cross wavelet transform
fault diagnosis
