Inspection and Monitoring of Wind Turbine Blade-Embedded Wave Defects During Fatigue Testing

Scott Hughes, Christopher Niezrecki, Peter Avitabile, Julie Chen, James Sherwood, Troy Lundstrom, Bruce LeBlanc, Alan Beattie, Mark Rumsey, Sandra Klute, Renee Pedrazzani, Rudy Werlink, John Newman, Michael Desmond

Research output: Contribution to journalArticlepeer-review

46 Scopus Citations


The research presented 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. Researchers used digital image correlation, shearography, acoustic emission, fiber-optic strain sensing, thermal imaging, and piezoelectric sensing as structural health monitoring techniques. 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.

Original languageAmerican English
Pages (from-to)629-643
Number of pages15
JournalStructural Health Monitoring
Issue number6
StatePublished - 20 Nov 2014

Bibliographical note

Publisher Copyright:
© The Author(s) 2014.

NREL Publication Number

  • NREL/JA-5000-60860


  • composites
  • damage detection
  • defect
  • Digital image correlation
  • fiber-optic sensing
  • shearography
  • wind turbine blade


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