An Introduction to Harmonic Wavelet Analysis of Machine Vibrations PUBLIC ACCESS

[+] Author Affiliations
Jose I. Bonel-Cerdan, Jorgen L. Nikolajsen

Staffordshire University, Stafford, UK

Paper No. 97-GT-058, pp. V004T14A011; 8 pages
  • ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition
  • Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education; IGTI Scholar Award
  • Orlando, Florida, USA, June 2–5, 1997
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-7871-2
  • Copyright © 1997 by ASME


The Fast Wavelet Transform (FWT) is a powerful new tool which can be used for vibration analysis and condition monitoring of advanced rotating machinery. The main advantage of wavelet analysis for condition monitoring is that so-called wavelet maps can be produced showing three dimensional plots of amplitude versus frequency and time. This is in contrast to Fast Fourier Transform (FFT) analysis, in which the time domain of the signal is lost. The wavelet maps provide striking visual indications of tiny changes in machine behaviour which cannot be detected in a normal frequency spectrum. This improves the chances of averting catastrophic failures and expands the time window available to take corrective action. Additional advantages of wavelet analysis over FFT analysis include: (1) no requirements for periodicity of the signal, (2) extremely fast computation, (3) the location of patterns in the time domain and (4) an effective detection of high frequency details.

Wavelet analyses of all types are available but user-friendly information is hard to come by and this has a detrimental effect on progress towards practical commercial applications. Thus, the main purpose of this paper is to provide a simple and clear introduction to wavelet analysis and its use in machine condition monitoring. The paper has been written for an audience having some familiarity with spectrum analysis but no prior knowledge of wavelets.

Copyright © 1997 by ASME
This article is only available in the PDF format.



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