University of Oulu

Nissilä, J. (2017) Local Regularity Analysis with Wavelet Transform in Gear Tooth Failure Detection, 25 (3), doi:10.1515/mspe-2017-0026

Local regularity analysis with wavelet transform in gear tooth failure detection

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Author: Nissilä, Juhani1
Organizations: 1Faculty of Information Technology and Electrical Engineering, Applied and computational mathematics, University of Oulu
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.4 MB)
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Language: English
Published: De Gruyter, 2017
Publish Date: 2017-10-17


Diagnosing gear tooth and bearing failures in industrial power transition situations has been studied a lot but challenges still remain. This study aims to look at the problem from a more theoretical perspective. Our goal is to find out if the local regularity i.e. smoothness of the measured signal can be estimated from the vibrations of epicyclic gearboxes and if the regularity can be linked to the meshing events of the gear teeth. Previously it has been shown that the decreasing local regularity of the measured acceleration signals can reveal the inner race faults in slowly rotating bearings. The local regularity is estimated from the modulus maxima ridges of the signal’s wavelet transform. In this study, the measurements come from the epicyclic gearboxes of the Kelukoski water power station (WPS). The very stable rotational speed of the WPS makes it possible to deduce that the gear mesh frequencies of the WPS and a frequency related to the rotation of the turbine blades are the most significant components in the spectra of the estimated local regularity signals.

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Series: Management systems in production engineering
ISSN: 2299-0461
ISSN-E: 2450-5781
ISSN-L: 2299-0461
Volume: 25
Issue: 3
Pages: 176 - 182
DOI: 10.1515/mspe-2017-0026
Type of Publication: A1 Journal article – refereed
Field of Science: 214 Mechanical engineering
213 Electronic, automation and communications engineering, electronics
Copyright information: © 2017. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0