Full Content is available to subscribers

Subscribe/Learn More  >

An Enhanced Extraction Method Based on EEMD for Processing a Bearing Vibration Signal With Multiple Vibration Sources

[+] Author Affiliations
Wei Guo

University of Electronic Science and Technology of China, Chengdu, Sichuan, China

Paper No. IMECE2014-38177, pp. V04BT04A073; 7 pages
  • ASME 2014 International Mechanical Engineering Congress and Exposition
  • Volume 4B: Dynamics, Vibration, and Control
  • Montreal, Quebec, Canada, November 14–20, 2014
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4648-3
  • Copyright © 2014 by ASME


Condition monitoring and fault diagnosis for rolling element bearings is an imperative part for preventive maintenance procedures and reliability improvement of rotating machines. When a localized fault occurs at the early stage of real bearing failures, the impulses generated by the defect are relatively weak and usually overwhelmed by large noise and other higher-level macro-structural vibrations generated by adjacent machine components and machines. To indicate the bearing faulty state as early as possible, it is necessary to develop an effective signal processing method for extracting the weak bearing signal from a vibration signal containing multiple vibration sources. The ensemble empirical mode decomposition (EEMD) method inherits the advantage of the popular empirical mode decomposition (EMD) method and can adaptively decompose a multi-component signal into a number of different bands of simple signal components. However, the energy dispersion and many redundant components make the decomposition result obtained by the EEMD losing the physical significance. In this paper, to enhance the decomposition performance of the EEMD method, the similarity criterion and the corresponding combination technique are proposed to determine the similar signal components and then generate the real mono-component signals. To validate the effectiveness of the proposed method, it is applied to analyze raw vibration signals collected from two faulty bearings, each of which involves more than one vibration sources. The results demonstrate that the proposed method can accurately extract the bearing feature signal; meanwhile, it makes the physical meaning of each IMF clear.

Copyright © 2014 by ASME
Topics: Bearings , Vibration , Signals



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In