Damage Detection in an Operating Vestas V27 Wind Turbine Blade by use of Outlier Analysis

Martin Dalgaard Ulriksen; Dmitri Tcherniak; Lars Damkilde

doi:10.1109/EESMS.2015.7175851

Damage Detection in an Operating Vestas V27 Wind Turbine Blade by use of Outlier Analysis

Martin Dalgaard Ulriksen, Dmitri Tcherniak, Lars Damkilde

Danish Centre for Risk and Safety Management

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

33 Citations (Scopus)

Abstract

The present paper explores the application of a well-established vibration-based damage detection method to an operating Vestas V27 wind turbine blade. The blade is analyzed in a total of four states, namely, a healthy one plus three damaged ones in which trailing edge openings of increasing sizes are introduced. In each state, the blade is subjected to controlled actuator hits, yielding forced vibrations that are measured in a total of 12 accelerometers; of which 11 are used for damage detection. The dimensionality of these acceleration data is reduced by means of principal component analysis (PCA), and then a reduced set of selected principal scores are employed as damage features in the Mahalanobis metric in order to detect damage-induced anomalies.

Original language	English
Title of host publication	IEEE Workshop on Environmental, Energy and Structural Monitoring Systems
Number of pages	6
Publisher	IEEE Press
Publication date	2015
DOIs	https://doi.org/10.1109/EESMS.2015.7175851
Publication status	Published - 2015
Event	IEEE Workshop: on Environmental, Energy and Structural Monitoring Systesms - , Italy Duration: 9 Jul 2015 → 10 Jul 2015

Workshop

Workshop	IEEE Workshop
Country/Territory	Italy
Period	09/07/2015 → 10/07/2015

Keywords

Damage Detection
Vestas V27
Wind Turbine Blade

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10.1109/EESMS.2015.7175851

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title = "Damage Detection in an Operating Vestas V27 Wind Turbine Blade by use of Outlier Analysis",

abstract = "The present paper explores the application of a well-established vibration-based damage detection method to an operating Vestas V27 wind turbine blade. The blade is analyzed in a total of four states, namely, a healthy one plus three damaged ones in which trailing edge openings of increasing sizes are introduced. In each state, the blade is subjected to controlled actuator hits, yielding forced vibrations that are measured in a total of 12 accelerometers; of which 11 are used for damage detection. The dimensionality of these acceleration data is reduced by means of principal component analysis (PCA), and then a reduced set of selected principal scores are employed as damage features in the Mahalanobis metric in order to detect damage-induced anomalies.",

keywords = "Damage Detection, Vestas V27, Wind Turbine Blade, Damage Detection, Vestas V27, Wind Turbine Blade",

author = "Ulriksen, {Martin Dalgaard} and Dmitri Tcherniak and Lars Damkilde",

year = "2015",

doi = "10.1109/EESMS.2015.7175851",

language = "English",

booktitle = "IEEE Workshop on Environmental, Energy and Structural Monitoring Systems",

publisher = "IEEE Press",

note = "IEEE Workshop ; Conference date: 09-07-2015 Through 10-07-2015",

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Damage Detection in an Operating Vestas V27 Wind Turbine Blade by use of Outlier Analysis. / Ulriksen, Martin Dalgaard; Tcherniak, Dmitri; Damkilde, Lars.
IEEE Workshop on Environmental, Energy and Structural Monitoring Systems. IEEE Press, 2015.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

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AU - Tcherniak, Dmitri

AU - Damkilde, Lars

PY - 2015

Y1 - 2015

N2 - The present paper explores the application of a well-established vibration-based damage detection method to an operating Vestas V27 wind turbine blade. The blade is analyzed in a total of four states, namely, a healthy one plus three damaged ones in which trailing edge openings of increasing sizes are introduced. In each state, the blade is subjected to controlled actuator hits, yielding forced vibrations that are measured in a total of 12 accelerometers; of which 11 are used for damage detection. The dimensionality of these acceleration data is reduced by means of principal component analysis (PCA), and then a reduced set of selected principal scores are employed as damage features in the Mahalanobis metric in order to detect damage-induced anomalies.

AB - The present paper explores the application of a well-established vibration-based damage detection method to an operating Vestas V27 wind turbine blade. The blade is analyzed in a total of four states, namely, a healthy one plus three damaged ones in which trailing edge openings of increasing sizes are introduced. In each state, the blade is subjected to controlled actuator hits, yielding forced vibrations that are measured in a total of 12 accelerometers; of which 11 are used for damage detection. The dimensionality of these acceleration data is reduced by means of principal component analysis (PCA), and then a reduced set of selected principal scores are employed as damage features in the Mahalanobis metric in order to detect damage-induced anomalies.

KW - Damage Detection

KW - Vestas V27

KW - Wind Turbine Blade

KW - Damage Detection

KW - Vestas V27

KW - Wind Turbine Blade

U2 - 10.1109/EESMS.2015.7175851

DO - 10.1109/EESMS.2015.7175851

M3 - Article in proceeding

BT - IEEE Workshop on Environmental, Energy and Structural Monitoring Systems

PB - IEEE Press

T2 - IEEE Workshop

Y2 - 9 July 2015 through 10 July 2015

ER -

Damage Detection in an Operating Vestas V27 Wind Turbine Blade by use of Outlier Analysis

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