A pseudo wavelet system-based vibration signature extracting method for rotating machinery fault detection
A pseudo wavelet system-based vibration signature extracting method for rotating machinery fault detection
复制标题
基于伪小波系统的旋转机械故障检测振动特征提取方法
DOI：
10.1007/s11431-013-5139-z
复制
发表时间：
2013-01
期刊：
影响因子：
--
通讯作者：
HE ZhengJia
中科院分区：
文献类型：
--
作者：
ZHANG ZhouSuo;ZI YanYang;YANG ZhiBo;HE ZhengJia
旋转机械作为大型复杂机械系统的典型，容易出现多种类型的机械故障，尤其是其旋转部件。尽管可以通过振动测量来收集它们，但关键故障特征总是被大量干扰内容所掩盖，因此难以识别。此外，由于机械故障特征的独特时频特征，经典的二进小波变换（DWT）并不适合在噪声环境中检测它们。为了解决DWT的不足，基于小波紧框架的滤波器构造策略，提出了伪小波系统(PWS)。所提出的 PWS 是通过专门设计的平移不变滤波器组结构实现的，该结构生成非二元小波子带以及二元小波子带。 PWS 将振动信号更精细地划分到频标平面中。此外，为了正确识别故障机械部件产生的基本瞬态特征，提出了一种新的信号脉冲度量，称为空间谱系综峰度（SSEK）。 SSEK用于在分解的小波子带中选择最佳分析参数，以便可以明确地识别被屏蔽的关键故障特征。该方法已应用于工程故障诊断案例，处理结果表明了其有效性并优于现有的一些方法。
The rotating machinery, as a typical example of large and complex mechanical systems, is prone to diversified sorts of mechanical faults, especially on their rotating components. Although they can be collected via vibration measurements, the critical fault signatures are always masked by overwhelming interfering contents, therefore difficult to be identified. Moreover, owing to the distinguished time-frequency characteristics of the machinery fault signatures, classical dyadic wavelet transforms (DWTs) are not perfect for detecting them in noisy environments. In order to address the deficiencies of DWTs, a pseudo wavelet system (PWS) is proposed based on the filter constructing strategies of wavelet tight frames. The presented PWS is implemented via a specially devised shift-invariant filterbank structure, which generates non-dyadic wavelet subbands as well as dyadic ones. The PWS offers a finer partition of the vibration signal into the frequency-scale plane. In addition, in order to correctly identify the essential transient signatures produced by the faulty mechanical components, a new signal impulsiveness measure, named spatial spectral ensemble kurtosis (SSEK), is put forward. SSEK is used for selecting the optimal analyzing parameters among the decomposed wavelet subbands so that the masked critical fault signatures can be explicitly recognized. The proposed method has been applied to engineering fault diagnosis cases, in which the processing results showed its effectiveness and superiority to some existing methods.
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影响因子：
8.4
作者：
Qin, Yi;Tang, Baoping;Wang, Jiaxu
通讯作者：
Wang, Jiaxu
影响因子：
0.9
作者：
GERONIMO, JS;HARDIN, DP;MASSOPUST, PR
通讯作者：
MASSOPUST, PR
DOI：
10.1006/acha.2000.0301
发表时间：
2000
期刊：
--
影响因子：
--
作者：
C. Chui;Wenjie He
通讯作者：
C. Chui;Wenjie He
基于非线性冗余提升小波包分析的滚子轴承故障诊断
DOI：
10.3390/s110100260
发表时间：
2011
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Gao L;Yang Z;Cai L;Wang H;Chen P
通讯作者：
Chen P
DOI：
--
发表时间：
2007
期刊：
Journal of Vibration Engineering
影响因子：
--
作者：
Wang Xiao-dong
通讯作者：
Wang Xiao-dong