Condition Assessment of Low-Speed Slew Bearings in Offshore Applications Using Acoustic Emission Monitoring

Conference Paper (2022)
Authors

B. Scheeren (TU Delft - Ship Hydromechanics and Structures)

L. Pahlavan (TU Delft - Ship Hydromechanics and Structures)

Research Group
Ship Hydromechanics and Structures
Copyright
© 2022 B. Scheeren, Lotfollah Pahlavan
To reference this document use:
https://doi.org/10.1007/978-3-031-07322-9_90
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 B. Scheeren, Lotfollah Pahlavan
Research Group
Ship Hydromechanics and Structures
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
892-901
ISBN (print)
978-3-031-07321-2
ISBN (electronic)
978-3-031-07322-9
DOI:
https://doi.org/10.1007/978-3-031-07322-9_90
Reuse Rights

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Abstract

This study presents an approach for the detection of evolving degradation in large-scale low-speed roller bearings by clustering of Acoustic Emission (AE) events, and its application to experimental degradation data. To acquire the latter, a purpose-built linear bearing, representative of a segment of a turret bearing, has been instrumented with multiple piezoelectric AE transducers in the frequency range between 40–580 kHz. Clustering based on cross-correlation has identified a number of significant clusters that are linked to the observed damage. The results suggest that condition monitoring based on AE waveform similarity clustering is suitable for detection and identification of degradation in a large-scale roller bearing.

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