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

B. Scheeren; Lotfollah Pahlavan

doi:10.1007/978-3-031-07322-9_90

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

^*Corresponding author for this work

Ship Hydromechanics and Structures

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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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.

Original language	English
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	https://doi.org/10.1007/978-3-031-07322-9_90
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
Volume	270 LNCE
ISSN (Print)	2366-2557
ISSN (Electronic)	2366-2565

Conference

Conference	10th European Workshop on Structural Health Monitoring, EWSHM 2022
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-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.

Keywords

Acoustic Emission
Condition Monitoring
Roller Bearing
Clustering
Offshore

Access to Document

10.1007/978-3-031-07322-9_90

978-3-031-07322-9_90Final published version, 2.69 MB

Cite this

Scheeren, B., & Pahlavan, L. (2022). Condition Assessment of Low-Speed Slew Bearings in Offshore Applications Using Acoustic Emission Monitoring. In P. Rizzo, & A. Milazzo (Eds.), European Workshop on Structural Health Monitoring: EWSHM 2022 - Volume 3 (pp. 892-901). (Lecture Notes in Civil Engineering; Vol. 270 LNCE). Springer. https://doi.org/10.1007/978-3-031-07322-9_90

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title = "Condition Assessment of Low-Speed Slew Bearings in Offshore Applications Using Acoustic Emission Monitoring",

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.",

keywords = "Acoustic Emission, Condition Monitoring, Roller Bearing, Clustering, Offshore",

author = "B. Scheeren and Lotfollah Pahlavan",

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.; 10th European Workshop on Structural Health Monitoring, EWSHM 2022 ; Conference date: 04-07-2022 Through 07-07-2022",

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doi = "10.1007/978-3-031-07322-9_90",

language = "English",

isbn = "978-3-031-07321-2",

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Scheeren, B & Pahlavan, L 2022, Condition Assessment of Low-Speed Slew Bearings in Offshore Applications Using Acoustic Emission Monitoring. in P Rizzo & A Milazzo (eds), European Workshop on Structural Health Monitoring: EWSHM 2022 - Volume 3. Lecture Notes in Civil Engineering, vol. 270 LNCE, Springer, Cham, Switzerland, pp. 892-901, 10th European Workshop on Structural Health Monitoring, EWSHM 2022, Palermo, Italy, 4/07/22. https://doi.org/10.1007/978-3-031-07322-9_90

Condition Assessment of Low-Speed Slew Bearings in Offshore Applications Using Acoustic Emission Monitoring. / Scheeren, B.; Pahlavan, Lotfollah.
European Workshop on Structural Health Monitoring: EWSHM 2022 - Volume 3. ed. / Piervincenzo Rizzo; Alberto Milazzo. Cham, Switzerland: Springer, 2022. p. 892-901 (Lecture Notes in Civil Engineering; Vol. 270 LNCE).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Scheeren, B.

AU - Pahlavan, Lotfollah

N1 - 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.

PY - 2022

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N2 - 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.

AB - 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.

KW - Acoustic Emission

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ER -

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

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