Damage detection in flexible risers using statistical pattern recognition techniques

Carlos Alberto Riveros; Tomoaki Utsunomiya; Katsuya Maeda; Kazuaki Itoh

Damage detection in flexible risers using statistical pattern recognition techniques

Carlos Alberto Riveros, Tomoaki Utsunomiya, Katsuya Maeda, Kazuaki Itoh

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A statistical pattern recognition technique based on time series analysis of vibration data is presented in this paper. A 20-meter riser model experimentally validated is used for the numerical implementation of this technique. The dynamic response of the riser model is assessed using a semi-empirical approach with an increased mean drag coefficient model during lock-in events. Structural damage is associated with fatigue damage. Therefore, hinge connections are used to represent several damage scenarios. Then, the statistical pattern recognition technique is used to identify and locate structural damage using vibration data collected from sensors strategically located. Sensor locations are obtained from an optimum sensor placement method. The numerical results show that damage in oscillating flexible risers can be assessed using the presented statistical pattern recognition technique.

Original language	English
Title of host publication	Proceedings of The Seventeenth 2007 International Offshore and Polar Engineering Conference, ISOPE 2007
Pages	2746-2753
Number of pages	8
Publication status	Published - 2007
Externally published	Yes
Event	17th 2007 International Offshore and Polar Engineering Conference, ISOPE 2007 - Lisbon, Portugal Duration: Jul 1 2007 → Jul 6 2007

Publication series

Name	Proceedings of the International Offshore and Polar Engineering Conference
ISSN (Print)	1098-6189
ISSN (Electronic)	1555-1792

Other

Other	17th 2007 International Offshore and Polar Engineering Conference, ISOPE 2007
Country/Territory	Portugal
City	Lisbon
Period	7/1/07 → 7/6/07

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Ocean Engineering
Mechanical Engineering

Cite this

Damage detection in flexible risers using statistical pattern recognition techniques. / Riveros, Carlos Alberto; Utsunomiya, Tomoaki; Maeda, Katsuya et al.
Proceedings of The Seventeenth 2007 International Offshore and Polar Engineering Conference, ISOPE 2007. 2007. p. 2746-2753 (Proceedings of the International Offshore and Polar Engineering Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Riveros, CA, Utsunomiya, T, Maeda, K & Itoh, K 2007, Damage detection in flexible risers using statistical pattern recognition techniques. in Proceedings of The Seventeenth 2007 International Offshore and Polar Engineering Conference, ISOPE 2007. Proceedings of the International Offshore and Polar Engineering Conference, pp. 2746-2753, 17th 2007 International Offshore and Polar Engineering Conference, ISOPE 2007, Lisbon, Portugal, 7/1/07.

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author = "Riveros, {Carlos Alberto} and Tomoaki Utsunomiya and Katsuya Maeda and Kazuaki Itoh",

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AU - Riveros, Carlos Alberto

AU - Utsunomiya, Tomoaki

AU - Maeda, Katsuya

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N2 - A statistical pattern recognition technique based on time series analysis of vibration data is presented in this paper. A 20-meter riser model experimentally validated is used for the numerical implementation of this technique. The dynamic response of the riser model is assessed using a semi-empirical approach with an increased mean drag coefficient model during lock-in events. Structural damage is associated with fatigue damage. Therefore, hinge connections are used to represent several damage scenarios. Then, the statistical pattern recognition technique is used to identify and locate structural damage using vibration data collected from sensors strategically located. Sensor locations are obtained from an optimum sensor placement method. The numerical results show that damage in oscillating flexible risers can be assessed using the presented statistical pattern recognition technique.

AB - A statistical pattern recognition technique based on time series analysis of vibration data is presented in this paper. A 20-meter riser model experimentally validated is used for the numerical implementation of this technique. The dynamic response of the riser model is assessed using a semi-empirical approach with an increased mean drag coefficient model during lock-in events. Structural damage is associated with fatigue damage. Therefore, hinge connections are used to represent several damage scenarios. Then, the statistical pattern recognition technique is used to identify and locate structural damage using vibration data collected from sensors strategically located. Sensor locations are obtained from an optimum sensor placement method. The numerical results show that damage in oscillating flexible risers can be assessed using the presented statistical pattern recognition technique.

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AN - SCOPUS:36448942920

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T3 - Proceedings of the International Offshore and Polar Engineering Conference

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BT - Proceedings of The Seventeenth 2007 International Offshore and Polar Engineering Conference, ISOPE 2007

T2 - 17th 2007 International Offshore and Polar Engineering Conference, ISOPE 2007

Y2 - 1 July 2007 through 6 July 2007

ER -

Damage detection in flexible risers using statistical pattern recognition techniques

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

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