Incipient fault information determination for rolling element bearing based on synchronous averaging reassigned wavelet scalogram
Incipient fault information determination for rolling element bearing based on synchronous averaging reassigned wavelet scalogram
复制标题
基于同步平均重构小波尺度图的滚动轴承早期故障信息判定
DOI：
10.1016/j.measurement.2014.12.032
复制
发表时间：
2015-04
期刊：
影响因子：
5.6
通讯作者：
Xuefeng Zhang
中科院分区：
文献类型：
--
作者：
Hongkun Li;Fujian Xu;Hongyi Liu;Xuefeng Zhang
由于旋转机械的早期故障信号微弱且受噪声干扰，其特征信息的提取和早期故障的分类比较困难。提出了一种基于时频分析的同步平均重分配小波尺度图（SARWS）提取滚动轴承早期冲击信息的新方法。首先对多周期信号进行连续小波变换;然后，利用小波尺度图的时域信息，得到振动信号各工作周期的时频分布。第三，重新分配小波尺度图（RWS）的每个工作周期的REB可以计算。最后，将同步平均技术应用于RWS中，有效地降低了噪声干扰，识别出了微弱的故障信息。用仿真信号和旋转机械振动台采集的真实的振动信号对该方法进行了验证。分析结果表明，该方法对REB早期弱故障分类是有效的。
As incipient fault of rotating machinery is weak and interfered by noise, it is difficult for characteristic information determination and incipient classification. In this research, a new method is put forward on rolling element bearing (REB) incipient impact information using synchronous averaging reassigned wavelet scalogram (SARWS) according to time–frequency analysis. Firstly, multi-cycle signal is processed by continuous wavelet transform. Then, time frequency distribution for every working cycle of vibration signal is obtained by wavelet scalogram (WS) based on time domain information. Thirdly, reassigned wavelet scalogram (RWS) for every working cycle of REB can be calculated. In the end, synchronous averaging is applied on RWS, which can effectively reduce noise interference and identify the weak fault information. Both simulated signals and real vibration signals collected from REB of rotating machinery are used to verify this proposed method. Analyzed results show that the proposed method is effective for REB incipient weak fault classification.
登录
查看更多内容
影响因子：
8.4
作者：
Zhike Peng;F. Chu;P. Tse
通讯作者：
Zhike Peng;F. Chu;P. Tse
影响因子：
4.7
作者：
J. Antoni;J. Daniere;F. Guillet;R. Randall
通讯作者：
J. Antoni;J. Daniere;F. Guillet;R. Randall
影响因子：
8.3
作者：
E. Lihovd;T. Johannessen;C. Steinebach;M. Rasmussen
通讯作者：
E. Lihovd;T. Johannessen;C. Steinebach;M. Rasmussen
影响因子：
4.7
作者：
J. Antoni;J. Daniere;F. Guillet
通讯作者：
J. Antoni;J. Daniere;F. Guillet
影响因子：
8.4
作者：
Halim, Enayet B.;Choudhury, M. A. A. Shoukat;Zuo, Ming J.
通讯作者：
Zuo, Ming J.