Hilbert-Huang transform and marginal spectrum for detection and diagnosis of localized defects in roller bearings
Hilbert-Huang transform and marginal spectrum for detection and diagnosis of localized defects in roller bearings
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DOI：
10.1007/s12206-008-1110-5
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发表时间：
2009-02-01
影响因子：
1.6
通讯作者：
Zheng, Haiqi
中科院分区：
文献类型：
--
作者：
Li, Hui;Zhang, Yuping;Zheng, Haiqi
本文介绍了一种新的信号处理技术Hilbert-Huang变换及其边际谱在滚子轴承振动信号分析和故障诊断中的应用。介绍了经验模态分解（EMD）、Hilbert-Huang变换（HHT）和边际谱。第一。利用EMD将振动信号分解为若干个本征模态函数。然后得到每个IMF呼叫的边际谱。根据边际谱检测滚动轴承局部故障，识别故障模式。实验结果表明，该方法不仅提高了频谱分辨率，而且提高了对轧辊轴承故障检测和诊断的可靠性。
This work presents the application of a new signal processing technique, the Hilbert-Huang, transtorm and its marginal spectrum, in analysis of vibration signals and fault diagnosis of roller bearings. The empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. First. the vibration signals are separated into several intrinsic mode functions (IMFs) by using EMD. Then the marginal spectrum of each IMF call be obtained. According to the marginal Spectrum, the localized fault in a roller bearing call be detected and fault patterns call be identified. The experimental results show that the proposed method may provide not only all increase in the spectral resolution but also reliability for the fault detection and diagnosis of roller hearings.