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Filtered evelope spectrum using short periodograms for bearing fault identification under variable speed

  • Edgar F. Sierra-AlonsoEmail author
  • Jerome Antoni
  • German Castellanos-Dominguez
Conference paper
Part of the Mechanisms and Machine Science book series (Mechan. Machine Science, volume 73)

Abstract

This paper introduces a method based on short periodograms, combining, envelope analysis, and spectral kurtosis (SK). In order to highlight an underlying impulsive spectral component of a vibration signal, to do so, the proposed method takes into account the well-known welch’s method of periodograms applied to a non-overlapping filtered signal segment using the SK. An SK short-time approach is considered, due to, a high variable speed even in angle domain has an underlying non-stationarity caused by the fact that the transfer function is angle variant. In the end, it is obtained a noiseless envelope spectrum, averaging the filtered periodograms of each envelope of the non-overlapped signal segments. To prove the effectiveness of the proposed method, it is tested on a highly non-stationary vibration signal measured from an aircraft engine under a run-up test. As a result, we can identify a bearing failure embedded highly non-stationary noise. Besides as the proposed method makes use of short periodograms is fast, reliable, and entirely non-parametric, making it readily applicable to highlight any underlying impulsive behaviour in a vibration signal.

Keywords

envelope analysis periodogram spetral kurtosis bearing failure identification 

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Notes

Acknowledgments

Convocatoria 647 de 2014 de Colciencias-Colfuturo and IDEXLYON “aide à la mobilité internationale des doctorants”.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Edgar F. Sierra-Alonso
    • 1
    • 2
    Email author
  • Jerome Antoni
    • 1
  • German Castellanos-Dominguez
    • 2
  1. 1.Laboratoire Vibrations AcoustiqueUniv Lyon, INSA-LyonVilleurbanneFrance
  2. 2.Signal Processing and Recognition GroupUniversidad Nacional de ColombiaManizales CaldasColombia

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