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Content Provider | IET Digital Library |
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Author | Jiang, Zhanglei Wu, Yapeng Li, Jun Liu, Yaru Wang, Jifang Xu, Xiaoli |
Abstract | The original signal of rolling bearing fault contains a large number of phase coupling components and is easily submerged in the background noise, which make the fault information difficult to be extracted accurately. Aiming at the above problems, a method of fault feature extraction for rolling bearing is proposed, which combines empirical mode decomposition (EMD) with a 1.5-dimensional spectrum. The original signal is decomposed by EMD to obtain the intrinsic modal function (IMF) of different scales. The IMF is selected by the size of a correlation coefficient and a kurtosis value to eliminate the high-frequency components, which is reconstructed to achieve the purpose of noise reduction. The reconstructed Hilbert envelope signal is analysed by the 1.5-dimensional spectrum to extract the nonlinear characteristic of two phase couplings, so that the fault characteristic frequency of the bearing is obtained. By analysing the signal of actual rolling bearings, the fault characteristic frequency of bearing inner and outer rings can be effectively extracted, and the validity and feasibility of the method are proved. |
Starting Page | 8843 |
Ending Page | 8847 |
Page Count | 5 |
Volume Number | 2019 |
e-ISSN | 20513305 |
Issue Number | Issue 23, Dec (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/23 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9121 |
Journal | The Journal of Engineering |
Publisher | The Institution of Engineering and Technology |
Publisher Date | 2019-03-25 |
Access Restriction | Open |
Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
Subject Keyword | 1.5-dimensional Spectrum Actual Rolling Bearings Bearing Fault Bearing Inner Rings Civil And Mechanical Engineering Computing Digital Signal Processing EMD Fault Characteristic Frequency Fault Diagnosis Fault Feature Extraction Fault Information Feature Extraction High-frequency Component Hilbert Envelope Signal Hilbert Transform Machine Bearings Mechanical Component Mechanical Engineering Mechanical Engineering Application of IT Mechanical Engineering Computing Outer Rings Phase Coupling Component Rolling Bearing Rolling Bearings Signal Processing Signal Processing And Detection Vibrations Vibrations And Shock Wave |
Content Type | Text |
Resource Type | Article |
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