Structural damage detection in wind turbine blades based on time series representations of dynamic responses

Simon Hoell*, Piotr Omenzetter

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

3 Citations (Scopus)
11 Downloads (Pure)


The development of large wind turbines that enable to harvest energy more efficiently is a consequence of the increasing demand for renewables in the world. To optimize the potential energy output, light and flexible wind turbine blades (WTBs) are designed. However, the higher flexibilities and lower buckling capacities adversely affect the long-term safety and reliability of WTBs, and thus the increased operation and maintenance costs reduce the expected revenue. Effective structural health monitoring techniques can help to counteract this by limiting inspection efforts and avoiding unplanned maintenance actions. Vibration-based methods deserve high attention due to the moderate instrumentation efforts and the applicability for in-service measurements. The present paper proposes the use of cross-correlations (CCs) of acceleration responses between sensors at different locations for structural damage detection in WTBs. CCs were in the past successfully applied for damage detection in numerical and experimental beam structures while utilizing only single lags between the signals. The present approach uses vectors of CC coefficients for multiple lags between measurements of two selected sensors taken from multiple possible combinations of sensors. To reduce the dimensionality of the damage sensitive feature (DSF) vectors, principal component analysis is performed. The optimal number of principal components (PCs) is chosen with respect to a statistical threshold. Finally, the detection phase uses the selected PCs of the healthy structure to calculate scores from a current DSF vector, where statistical hypothesis testing is performed for making a decision about the current structural state. The method is applied to laboratory experiments conducted on a small WTB with non-destructive damage scenarios.

Original languageEnglish
Title of host publicationSmart Materials and Nondestructive Evaluation for Energy Systems 2015
Subtitle of host publicationProceedings of SPIE
EditorsNorbert G Meyendorf
Place of PublicationBellingham
Number of pages11
ISBN (Print)9781628415421
Publication statusPublished - 27 Mar 2015
EventConference on Smart Materials and Nondestructive Evaluation for Energy Systems - San Diego, Canada
Duration: 9 Mar 201510 Mar 2015

Publication series

NameProceedings of SPIE
ISSN (Print)0277-786X


ConferenceConference on Smart Materials and Nondestructive Evaluation for Energy Systems


  • damage detection
  • wind turbines
  • wind turbine blades
  • time series methods
  • principal component analysis
  • statistical hypothesis testing
  • cross-correlations
  • health
  • localization
  • energy


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