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.
Original language | English |
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Title of host publication | European Workshop on Structural Health Monitoring |
Subtitle of host publication | EWSHM 2022 - Volume 3 |
Editors | Piervincenzo Rizzo, Alberto Milazzo |
Place of Publication | Cham, Switzerland |
Publisher | Springer |
Pages | 892-901 |
ISBN (Electronic) | 978-3-031-07322-9 |
ISBN (Print) | 978-3-031-07321-2 |
DOIs | |
Publication status | Published - 2022 |
Event | 10th European Workshop on Structural Health Monitoring, EWSHM 2022 - Palermo, Italy Duration: 4 Jul 2022 → 7 Jul 2022 |
Publication series
Name | Lecture Notes in Civil Engineering |
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Volume | 270 LNCE |
ISSN (Print) | 2366-2557 |
ISSN (Electronic) | 2366-2565 |
Conference
Conference | 10th European Workshop on Structural Health Monitoring, EWSHM 2022 |
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Country/Territory | Italy |
City | Palermo |
Period | 4/07/22 → 7/07/22 |
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-careOtherwise 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.
Keywords
- Acoustic Emission
- Condition Monitoring
- Roller Bearing
- Clustering
- Offshore