<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></abstract>

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.

Local Regularity Analysis with Wavelet Transform in Gear Tooth Failure Detection

Management Systems in Production Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Local Regularity Analysis with Wavelet Transform in Gear Tooth Failure Detection"}

Diagnosing gear tooth and bearing failures in industrial power transition situations has been studied a lot but challenges still remain. This study aims to...

Local Regularity Analysis with Wavelet Transform in Gear Tooth Failure Detection

Article Category: Special Issue Title: Maintenance Performance Measurement and Management Challenges: from Sensing to Decision Support

Published Online: Aug 01, 2017

Page range: 176 - 182

Received: Oct 01, 2016

Accepted: Apr 01, 2017

DOI: https://doi.org/10.1515/mspe-2017-0026

Keywords
epicyclic gearbox, spectral analysis, Hölder regularity, wavelet modulus maxima, water power station

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Local Regularity Analysis with Wavelet Transform in Gear Tooth Failure Detection

Article Category: Special Issue Title: Maintenance Performance Measurement and Management Challenges: from Sensing to Decision Support

Published Online: Aug 01, 2017

Page range: 176 - 182

Received: Oct 01, 2016

Accepted: Apr 01, 2017

DOI: https://doi.org/10.1515/mspe-2017-0026

Keywordsepicyclic gearbox, spectral analysis, Hölder regularity, wavelet modulus maxima, water power station

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
epicyclic gearbox, spectral analysis, Hölder regularity, wavelet modulus maxima, water power station