A redundant wavelet transform for vibration signals in electric motors

S. Seker, J. Dikun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study is focused on the redundant wavelet transform application for vibration signals collected from induction motor of 5 HP aged under the accelerated aging processes. For this purpose, comparing the healthy and faulty cases of the motors, some inherent advantages of the redundant transform over the unredundant one is extracted. This possibility can be provided by means of the Continuous Wavelet Transform (CWT) because it is a redundant transform. Hence some failure properties of the motor bearings can be shown by initial case of the motor before the aged case. This is most important and powerful side of this study and then, failed motor case can be easily tracked by help of this approach.

Original languageEnglish
Title of host publicationProceedings of ISMA 2014 - International Conference on Noise and Vibration Engineering and USD 2014 - International Conference on Uncertainty in Structural Dynamics
EditorsP. Sas, D. Moens, H. Denayer
PublisherKU Leuven
Pages429-435
Number of pages7
ISBN (Electronic)9789073802919
Publication statusPublished - 2014
Event26th International Conference on Noise and Vibration Engineering, ISMA 2014, Including the 5th International Conference on Uncertainty in Structural Dynamics, USD 2014 - Leuven, Belgium
Duration: 15 Sept 201417 Sept 2014

Publication series

NameProceedings of ISMA 2014 - International Conference on Noise and Vibration Engineering and USD 2014 - International Conference on Uncertainty in Structural Dynamics

Conference

Conference26th International Conference on Noise and Vibration Engineering, ISMA 2014, Including the 5th International Conference on Uncertainty in Structural Dynamics, USD 2014
Country/TerritoryBelgium
CityLeuven
Period15/09/1417/09/14

Fingerprint

Dive into the research topics of 'A redundant wavelet transform for vibration signals in electric motors'. Together they form a unique fingerprint.

Cite this