Application of Spectral Kurtosis to Acoustic Emission Signatures from Bearings

  • Babak Eftekharnejad
  • Mhmod Hamel
  • Abdulmajid Addali
  • David Mba
Conference paper

Abstract

The application of Acoustic Emission (AE) in condition monitoring of rotating machines has been well documented. The majority of research works in this field has involved the use of conventional time domain analysis for processing the AE signals from the machines and there has been little attention given to application of more advanced signal processing methods. This research presents a study in which some advanced signal processing techniques such as Wavelet and Spectral Kurtosis (SK) has been applied to offer improved diagnosis for bearing defect detection

Keywords

Acoustic Emission Wind Turbine Acoustic Emission Signature Short Time Fourier Transform Acoustic Emission Activity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Babak Eftekharnejad
    • 1
  • Mhmod Hamel
    • 2
  • Abdulmajid Addali
    • 2
  • David Mba
    • 2
  1. 1.Renewable Energy Systems Ltd, Kings LangleyHertfordshireUK
  2. 2.School of EngineeringCranfield UniversityBedfordUK

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