Skip to main content
padlock icon - secure page this page is secure

Lyapunov Exponent Employing Fractional Spline Wavelet for Fault Diagnosis of Rolling Bearing

Buy Article:

$106.34 + tax (Refund Policy)

A novel Fractional Spline Wavelet Transform (FrSWT) method used as denoise is presented based on the different correlativity of different signals in fractional wavelet field, then the method combined with Lyapunov exponent is applied to fault diagnosis of rolling bearing. Compared with the traditional wavelet packet transform, firstly the excellent denoising performance of this proposed method is illustrated though simulated signals form bearing system, then the simulation results demonstrates that Lyapunov exponent employing fractional spline wavelet for fault diagnosis of rolling bearing is more accurate and effective to recognize the fault of rolling bearing than its counterpart.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics


Document Type: Research Article

Publication date: March 1, 2012

More about this publication?
  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more