0
RESEARCH PAPERS: Mechanical Signature Analysis Papers

Bearing Fault Detection Using Adaptive Noise Cancelling

[+] Author and Article Information
G. K. Chaturvedi, D. W. Thomas

Department of Electronics, University of Southampton, Southampton, SO9 5NH, England

J. Mech. Des 104(2), 280-289 (Apr 01, 1982) (10 pages) doi:10.1115/1.3256337 History: Received June 03, 1981; Online November 17, 2009

Abstract

The ability to diagnose a mechanical fault is enhanced if the monitoring signal can be preprocessed to reduce the effect of unwanted noise. To this end, the adaptive noise cancelling technique (ANC) can substantially improve the signal to noise ratio where the required signal is contaminated by noise. ANC makes use of two inputs—a primary input which contains the corrupted signal, and a reference input containing noise correlated in some unknown way with the primary noise. A variation of ANC is also proposed and it is shown that this can be applied effectively in those situations where inputs contain correlated signals but uncorrelated or weakly correlated noises. Using vibrational data derived from a reasonably complex bearing rig and preprocessing the data by the ANC technique, this paper shows that the statistical and spectral analysis techniques can be made more effective in their diagnostic roles after the application of ANC.

Copyright © 1982 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Tables

Errata

Discussions

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 Journal Articles
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