Inspection and monitoring of wind turbine blade-embedded wave defects during fatigue testing
Abstract
The research we present in this article focuses on a 9-m CX-100 wind turbine blade, designed by a team led by Sandia National Laboratories and manufactured by TPI Composites Inc. The key difference between the 9-m blade and baseline CX-100 blades is that this blade contains fabric wave defects of controlled geometry inserted at specified locations along the blade length. The defect blade was tested at the National Wind Technology Center at the National Renewable Energy Laboratory using a schedule of cycles at increasing load level until failure was detected. Our researchers used digital image correlation, shearography, acoustic emission, fiber-optic strain sensing, thermal imaging, and piezoelectric sensing as structural health monitoring techniques. Furthermore, this article provides a comparison of the sensing results of these different structural health monitoring approaches to detect the defects and track the resultant damage from the initial fatigue cycle to final failure.
- Authors:
-
- Univ. of Massachusetts, Lowell, MA (United States)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Luna Innovations Incorporated, Blacksburg, VA (United States)
- Kennedy Space Center, FL (United States)
- Laser Technology Inc., Norristown, PA (United States)
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1122363
- Report Number(s):
- SAND-2013-10376J
Journal ID: ISSN 1475-9217; 491460
- Grant/Contract Number:
- AC04-94AL85000
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Structural Health Monitoring
- Additional Journal Information:
- Journal Volume: 13; Journal Issue: 6; Journal ID: ISSN 1475-9217
- Publisher:
- SAGE Publications
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 17 WIND ENERGY; 42 ENGINEERING; digital image correlation; shearography; fiber-optic sensing; damage detection; composites; wind turbine blade; defect
Citation Formats
Niezrecki, Christopher, Avitabile, Peter, Chen, Julie, Sherwood, James, Lundstrom, Troy, LeBlanc, Bruce, Hughes, Scott, Desmond, Michael, Beattie, Alan, Rumsey, Mark, Klute, Sandra M., Pedrazzani, Renee, Werlink, Rudy, and Newman, John. Inspection and monitoring of wind turbine blade-embedded wave defects during fatigue testing. United States: N. p., 2014.
Web. doi:10.1177/1475921714532995.
Niezrecki, Christopher, Avitabile, Peter, Chen, Julie, Sherwood, James, Lundstrom, Troy, LeBlanc, Bruce, Hughes, Scott, Desmond, Michael, Beattie, Alan, Rumsey, Mark, Klute, Sandra M., Pedrazzani, Renee, Werlink, Rudy, & Newman, John. Inspection and monitoring of wind turbine blade-embedded wave defects during fatigue testing. United States. https://doi.org/10.1177/1475921714532995
Niezrecki, Christopher, Avitabile, Peter, Chen, Julie, Sherwood, James, Lundstrom, Troy, LeBlanc, Bruce, Hughes, Scott, Desmond, Michael, Beattie, Alan, Rumsey, Mark, Klute, Sandra M., Pedrazzani, Renee, Werlink, Rudy, and Newman, John. Tue .
"Inspection and monitoring of wind turbine blade-embedded wave defects during fatigue testing". United States. https://doi.org/10.1177/1475921714532995. https://www.osti.gov/servlets/purl/1122363.
@article{osti_1122363,
title = {Inspection and monitoring of wind turbine blade-embedded wave defects during fatigue testing},
author = {Niezrecki, Christopher and Avitabile, Peter and Chen, Julie and Sherwood, James and Lundstrom, Troy and LeBlanc, Bruce and Hughes, Scott and Desmond, Michael and Beattie, Alan and Rumsey, Mark and Klute, Sandra M. and Pedrazzani, Renee and Werlink, Rudy and Newman, John},
abstractNote = {The research we present in this article focuses on a 9-m CX-100 wind turbine blade, designed by a team led by Sandia National Laboratories and manufactured by TPI Composites Inc. The key difference between the 9-m blade and baseline CX-100 blades is that this blade contains fabric wave defects of controlled geometry inserted at specified locations along the blade length. The defect blade was tested at the National Wind Technology Center at the National Renewable Energy Laboratory using a schedule of cycles at increasing load level until failure was detected. Our researchers used digital image correlation, shearography, acoustic emission, fiber-optic strain sensing, thermal imaging, and piezoelectric sensing as structural health monitoring techniques. Furthermore, this article provides a comparison of the sensing results of these different structural health monitoring approaches to detect the defects and track the resultant damage from the initial fatigue cycle to final failure.},
doi = {10.1177/1475921714532995},
journal = {Structural Health Monitoring},
number = 6,
volume = 13,
place = {United States},
year = {Tue May 20 00:00:00 EDT 2014},
month = {Tue May 20 00:00:00 EDT 2014}
}
Web of Science
Works referenced in this record:
High-spatial-resolution distributed strain measurement in optical fiber with Rayleigh scatter
journal, January 1998
- Froggatt, Mark; Moore, Jason
- Applied Optics, Vol. 37, Issue 10
Measurement of localized heating in fiber optic components with millimeter spatial resolution
conference, January 2006
- Soller, B. J.; Gifford, D. K.; Wolfe, M. S.
- OFCNFOEC 2006. 2006 Optical Fiber Communication Conference and the National Fiber Optic Engineers Conference
High Resolution Distributed Strain or Temperature Measurements in Single- and Multi-Mode Fiber Using Swept-Wavelength Interferometry
conference, January 2006
- Kreger, Stephen T.; Gifford, Dawn K.; Froggatt, Mark E.
- Optical Fiber Sensors
Fatigue Testing of 9 m Carbon Fiber Wind Turbine Research Blades
conference, June 2012
- Paquette, Joshua; van Dam, Jeroen; Hughes, Scott
- 46th AIAA Aerospace Sciences Meeting and Exhibit
Structural Testing of 9m Carbon Fiber Wind Turbine Research Blades
conference, June 2012
- Paquette, Joshua; van Dam, Jeroen; Hughes, Scott
- 45th AIAA Aerospace Sciences Meeting and Exhibit
The application of non-destructive techniques to the testing of a wind turbine blade
report, June 1994
- Sutherland, H.; Beattie, A.; Hansche, B.
Works referencing / citing this record:
Measurement of quality test of aerodynamic profiles in wind turbine blades using laser triangulation technique
journal, June 2019
- Moreno‐Oliva, Víctor Iván; Román‐Hernández, Edwin; Torres‐Moreno, Eduardo
- Energy Science & Engineering, Vol. 7, Issue 5
Comparison of nondestructive testing techniques for the inspection of wind turbine blades' spar caps
journal, May 2018
- Martin, Robert W.; Sabato, Alessandro; Schoenberg, Andrew
- Wind Energy, Vol. 21, Issue 11
Prospective challenges in the experimentation of the rain erosion on the leading edge of wind turbine blades
journal, September 2018
- Bartolomé, Luis; Teuwen, Julie
- Wind Energy, Vol. 22, Issue 1
Wind Turbine Blade Damage Detection Using Supervised Machine Learning Algorithms
journal, August 2017
- Regan, Taylor; Beale, Christopher; Inalpolat, Murat
- Journal of Vibration and Acoustics, Vol. 139, Issue 6
Vertical Axis Wind Turbine Aerodynamics: Summary and Review of Momentum Models
journal, February 2019
- Mohammed, Amin A.; Ouakad, Hassen M.; Sahin, Ahmet Z.
- Journal of Energy Resources Technology, Vol. 141, Issue 5
Active acoustic damage detection of structural cavities using internal acoustic excitations
journal, March 2019
- Beale, Christopher; Inalpolat, Murat; Niezrecki, Christopher
- Structural Health Monitoring, Vol. 19, Issue 1
Passive acoustic damage detection of structural cavities using flow-induced acoustic excitations
journal, July 2019
- Beale, Christopher; Willis, David J.; Niezrecki, Christopher
- Structural Health Monitoring, Vol. 19, Issue 3
Damage mode identification of composite wind turbine blade under accelerated fatigue loads using acoustic emission and machine learning
journal, September 2019
- Liu, Pengfei; Xu, Dong; Li, Jingguo
- Structural Health Monitoring, Vol. 19, Issue 4