Automated wind turbine gearbox bearing diagnosis algorithm based on vibration data analysis and signal pre-whitening

Meik Schlechtingen, Ilmar Santos*

*Corresponding author for this work

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Abstract

In this paper an automated wind turbine gearbox bearing diagnosis algorithm is presented. The algorithm is based on most recent research results for separating discrete (gear) from random (bearing) frequency components using Cepstral Editing Procedure (CEP) based signal Pre-Whitening (PW). The proposed automated procedure builds up on the semi-automated procedure described by Sawalhi et al. in 2007. The procedure is updated with regards to the most recent achievements made concerning signal separation and extended with a frequency content identifier and rule based diagnosis to fully automate the diagnosis process. Furthermore, this paper gives a selection of important statements made in literature throughout the last decade to summarize the algorithms used and focus on the most important issues. Each of the involved processing steps is discussed with respect to its effectiveness based on real data.
The proposed procedure is applied to wind turbine data coming from seventeen wind turbines of the 2 MW class, for which vibration data are available containing both healthy and damaged states. Three application examples are given, where the automated procedure successfully diagnosed High Speed Shaft (HSS) bearing damages in the data sets.
Original languageEnglish
Title of host publicationProceedings of 13th SIRM: The 13th International Conference on Dynamics of Rotating Machinery
Place of PublicationKgs. Lyngby
PublisherTechnical University of Denmark
Publication date2019
Pages88-114
ISBN (Electronic)978-87-7475-568-5
Publication statusPublished - 2019
Event13th International Conference on Dynamics of Rotating Machinery - Technical University of Denmark, Copenhagen, Denmark
Duration: 13 Feb 201915 Feb 2019
Conference number: 13

Conference

Conference13th International Conference on Dynamics of Rotating Machinery
Number13
LocationTechnical University of Denmark
CountryDenmark
CityCopenhagen
Period13/02/201915/02/2019

Cite this

Schlechtingen, M., & Santos, I. (2019). Automated wind turbine gearbox bearing diagnosis algorithm based on vibration data analysis and signal pre-whitening. In Proceedings of 13th SIRM: The 13th International Conference on Dynamics of Rotating Machinery (pp. 88-114). Kgs. Lyngby: Technical University of Denmark.