Separation of vibration signal content using an improved discrete-random separation method

Onderzoeksoutput: Conference paper

Samenvatting

Vibration signals of machinery typically consist of various types of signal content. Two such types can be classified as stochastic and deterministic. In the past, several methods have been developed to tackle the separation of these two categories. One such solution is the Discrete/Random Separation method which estimates a frequency-domain transfer function from the signal to separate the predictable periodic content from the random content. Two of the downsides of the existing Discrete/Random Separation method in its current form are the variance of the estimated filter and its dependency on the time delay choice. This paper investigates the potential to alleviate these downsides by extending the definition of the filter from a single-delay to a multi-delay filter estimation procedure. This extension improves the reliability of the filter for practical usage and reduces the dependency of the result on the chosen filter delay. The improved DRS filter is examined on both simulated and experimental wind turbine gearbox vibration data.

Originele taal-2English
TitelSeparation of vibration signal content using an improved discrete-random separation method
RedacteurenW. Desmet, B. Pluymers, D. Moens, S. Vandemaele
UitgeverijISMA 2020
Pagina's1-9
Aantal pagina's9
ISBN van elektronische versie9789082893113
StatusPublished - 2020
EvenementISMA 2020 - Leuven, Leuven, Belgium
Duur: 22 sep 202024 sep 2020

Publicatie series

NaamProceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics

Conference

ConferenceISMA 2020
LandBelgium
StadLeuven
Periode22/09/2024/09/20

Bibliografische nota

Funding Information:
The authors would like to sincerely thank the National Renewable Energy Laboratory for providing the well-documented data sets and for organizing the wind turbine gearbox condition monitoring round robin study, which produced a lot of interesting research content. The authors would also like to acknowledge the support of De Blauwe Cluster through the project Supersized 4.0. This research was also supported by funding from the Flemish Government under the “Onderzoeksprogramma Artificiele Intelligentie (AI) Vlaanderen” programme.

Publisher Copyright:
© 2020 Proceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics. All rights reserved.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

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