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IJML 2012 Vol.2(1): 82-87
doi: 10.7763/IJMLC.2012.V2.93

Application of Wavelet Transform for Fault Diagnosis in Rotating Machinery

Hocine Bendjama , Salah Bouhouche , Mohamed Seghir Boucherit

  • Iron and Steel Applied Research Unit-CSC, BP 196, Annaba, Algeria, and the Process Control Laboratory, National Polytechnic Scool, BP 182, El-Harrach, Algiers, Algeria

Abstract

Vibration analysis is essential in improving condition monitoring and fault diagnostics of rotating machinery. Many signal analysis methods are able to extract useful information from vibration data. Currently, the most of these methods use spectral analysis based on Fourier Transform (FT). However, these methods present some limitations; it is the case of non-stationary signals. In the present work, we are interested to the vibration signal analysis by the Wavelet Transform (WT). The WT is one of the most important methods for signal processing; it is especially suitable for non-stationary vibration measurements obtained from accelerometer sensors. The monitoring results indicate that the WT can diagnose the abnormal change in the measured data.

Keywords

  • Vibration analysis
  • fault diagnosis
  • rotating machinery
  • spectral analysis
  • wavelet transform
93-T021

How to Cite

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Hocine Bendjama, Salah Bouhouche, and Mohamed Seghir Boucherit, "Application of Wavelet Transform for Fault Diagnosis in Rotating Machinery," International Journal of Machine Learning, vol. 2, no. 1, pp. 82-87, 2012. https://doi.org/10.7763/IJMLC.2012.V2.93

Copyright & License

Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • DOI: 10.18178/IJML
  • Frequency: Quarterly
  • Average Days to Accept: 68 days
  • Acceptance Rate: 27%
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • DOI: 10.18178/IJML
  • Abstracing/Indexing: Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: editor@ijml.org
  • APC: 500USD