Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoring

Xiao Chen; Sergei Semenov; Malcolm McGugan; Steen Hjelm Madsen; Süleyman Cem Yeniceli; Peter Berring; Kim Branner

doi:10.1016/j.compositesa.2020.106189

Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoring

Xiao Chen^*, Sergei Semenov, Malcolm McGugan, Steen Hjelm Madsen, Süleyman Cem Yeniceli, Peter Berring, Kim Branner

^*Corresponding author for this work

Villum Center for Advanced Structural and Material Testing

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

Understanding fatigue damage growth of composite wind turbine blades is an essential step towards reliable structural health monitoring (SHM) and accurate lifetime prediction. This study presents a comprehensive experimental investigation into damage growth within a full-scale composite wind turbine blade under fatigue loading. The blade has artificial defects embedded to initiate damage growth. The damages are detected and monitored using Infrared (IR) thermography, Digital Image Correlation (DIC), and Acoustic Emission (AE). Steady damage growth and imminent structural failure are identified, demonstrating the effectiveness of these techniques to detect subsurface damages. New experimental observations include cyclic buckling of a trailing edge region and tapping and rubbing between the shear web and spar cap, both damages due to adhesive joint debonds. These observations highlight the necessity and the complexity of reliable modeling of nonlinear structural behavior on a large scale in order to predict local fatigue crack growth.

Original language	English
Article number	106189
Journal	Composites - Part A: Applied Science and Manufacturing
Volume	140
Number of pages	17
ISSN	1359-835X
DOIs	https://doi.org/10.1016/j.compositesa.2020.106189
Publication status	Published - 2021

Keywords

Wind turbine blade
Delamination
Fatigue test
Damage detection
Structural health monitoring
Defect

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10.1016/j.compositesa.2020.106189

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CASMaT: Villum Center for Advanced Structural and Material Testing
Stang, H., Kleis, C., Mikkelsen, L. P., Sørensen, B. F., Toftegaard, H., Berggreen, C., Branner, K., Michel, A., Andreassen, M. J., Luczak, M., Chen, X., Bjørnbak-Hansen, J., Legarth, B. N., Waldbjørn, J. P., Bangaru, A. K., Moncy, A. & Quinlan, A. R.
07/11/2017 → …
Project: Research

Smart Damage Prognostics by Automated Thermographic Analysis for Wind Turbine Blades under Cyclic Loads
Xiao Chen (Speaker)
26 May 2021
Activity: Talks and presentations › Conference presentations

File
Local buckling, three-dimensional stresses and progressive failure of root transition region of large composite WT blades
Xiao Chen (Invited speaker)
26 Jun 2017
Activity: Talks and presentations › Conference presentations

File

Cite this

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title = "Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoring",

abstract = "Understanding fatigue damage growth of composite wind turbine blades is an essential step towards reliable structural health monitoring (SHM) and accurate lifetime prediction. This study presents a comprehensive experimental investigation into damage growth within a full-scale composite wind turbine blade under fatigue loading. The blade has artificial defects embedded to initiate damage growth. The damages are detected and monitored using Infrared (IR) thermography, Digital Image Correlation (DIC), and Acoustic Emission (AE). Steady damage growth and imminent structural failure are identified, demonstrating the effectiveness of these techniques to detect subsurface damages. New experimental observations include cyclic buckling of a trailing edge region and tapping and rubbing between the shear web and spar cap, both damages due to adhesive joint debonds. These observations highlight the necessity and the complexity of reliable modeling of nonlinear structural behavior on a large scale in order to predict local fatigue crack growth.",

keywords = "Wind turbine blade, Delamination, Fatigue test, Damage detection, Structural health monitoring, Defect",

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journal = "Composites - Part A: Applied Science and Manufacturing",

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AU - Chen, Xiao

AU - Semenov, Sergei

AU - McGugan, Malcolm

AU - Madsen, Steen Hjelm

AU - Yeniceli, Süleyman Cem

AU - Berring, Peter

AU - Branner, Kim

PY - 2021

Y1 - 2021

N2 - Understanding fatigue damage growth of composite wind turbine blades is an essential step towards reliable structural health monitoring (SHM) and accurate lifetime prediction. This study presents a comprehensive experimental investigation into damage growth within a full-scale composite wind turbine blade under fatigue loading. The blade has artificial defects embedded to initiate damage growth. The damages are detected and monitored using Infrared (IR) thermography, Digital Image Correlation (DIC), and Acoustic Emission (AE). Steady damage growth and imminent structural failure are identified, demonstrating the effectiveness of these techniques to detect subsurface damages. New experimental observations include cyclic buckling of a trailing edge region and tapping and rubbing between the shear web and spar cap, both damages due to adhesive joint debonds. These observations highlight the necessity and the complexity of reliable modeling of nonlinear structural behavior on a large scale in order to predict local fatigue crack growth.

AB - Understanding fatigue damage growth of composite wind turbine blades is an essential step towards reliable structural health monitoring (SHM) and accurate lifetime prediction. This study presents a comprehensive experimental investigation into damage growth within a full-scale composite wind turbine blade under fatigue loading. The blade has artificial defects embedded to initiate damage growth. The damages are detected and monitored using Infrared (IR) thermography, Digital Image Correlation (DIC), and Acoustic Emission (AE). Steady damage growth and imminent structural failure are identified, demonstrating the effectiveness of these techniques to detect subsurface damages. New experimental observations include cyclic buckling of a trailing edge region and tapping and rubbing between the shear web and spar cap, both damages due to adhesive joint debonds. These observations highlight the necessity and the complexity of reliable modeling of nonlinear structural behavior on a large scale in order to predict local fatigue crack growth.

KW - Wind turbine blade

KW - Delamination

KW - Fatigue test

KW - Damage detection

KW - Structural health monitoring

KW - Defect

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DO - 10.1016/j.compositesa.2020.106189

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Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoring

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Keywords

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Projects

CASMaT: Villum Center for Advanced Structural and Material Testing

Activities

Smart Damage Prognostics by Automated Thermographic Analysis for Wind Turbine Blades under Cyclic Loads

Local buckling, three-dimensional stresses and progressive failure of root transition region of large composite WT blades

Cite this