Fault detection of an internal combustion engine through vibration analysis by wavelets transform

Gina P. Novillo, Néstor Diego Rivera Campoverde, Héctor Adrian Auquilla Veintimilla, César Daniel Beltrán Orellana

Research output: Contribution to journalArticlepeer-review


This paper presents a vibration analysis of an internal alternative combustion engine through frequency analysis and wavelet transform, where a form study of the temporary signal and the energy of that signal is carried out to extract certain characteristic values that allow to differentiate and identify to which pre-established operating conditions, a specific vibration signal belongs. Software is used to make the data decomposition, analysis and value extraction. Different analysis results are presented on this investigation like frequency analysis, spectrogram analysis, wavelet analysis, cross wavelet analysis, and results validation by extracting values of the signals of two tests generating a variation chart showing runs variability if it is big o tiny variability. This analysis is performed to characterize the engine vibration signals so that it is possible to identify an incipient failure in a non-intrusive manner and optimize its maintenance. Also, it can be determined the repetitive form that describes a temporary signal of mechanical vibrations of a motor, if its work cycle it is considered to separate the temporary signal into sections, as long as there are no lower frequency components than the result of dividing the sampling frequency for the number of points that are in a work cycle (the limit frequency).

Original languageEnglish
Pages (from-to)929-936
Number of pages8
JournalInternational Journal on Advanced Science, Engineering and Information Technology
Issue number3
StatePublished - 2020

Bibliographical note

Funding Information:
The authors express gratitude to Engineer Nestor Rivera for all his unconditional support and contributing his knowledge to the realization of this paper. Also, the authors are thankful to the investigation group "Grupo de Investigaci?n en Ingenieria de Transporte", GIIT, of the Universidad Polit?cnica Salesiana for all support during this investigation.

Publisher Copyright:
© 2020, Insight Society.

Copyright 2020 Elsevier B.V., All rights reserved.


  • Fault detection
  • FFT
  • Internal combustion engine
  • Spectrogram
  • Wavelets transform


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