Experimental damage detection in a wind turbine blade model using principal components of response correlation functions

S. Hoell*, P. Omenzetter

*Corresponding author for this work

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

3 Citations (Scopus)
9 Downloads (Pure)


The utilization of vibration signals for structural damage detection (SDD) is appealing due to the strong theoretical foundation of such approaches, ease of data acquisition and processing efficiency. Different methods are available for defining damage sensitive features (DSFs) based on vibrations, such as modal analysis or time series methods. The present paper proposes the use of partial autocorrelation coefficients of acceleration responses as DSFs. Principal component (PC) analysis is used to transform the initial DSFs to scores. The resulting scores from the healthy and damaged states are used to select the PCs which are most sensitive to damage. These are then used for making decisions about the structural state by means of statistical hypothesis testing conducted on the scores. The approach is applied to experiments with a laboratory scale wind turbine blade (WTB) made of glass-fibre reinforced epoxy composite. Damage is non-destructively simulated by attaching small masses and the WTB is excited with the help of an electrodynamic shaker using band-limited white noise. The SDD results for the selected subsets of PCs show a clear improvement of the detectability of early damages compared to other DSF selections.

Original languageEnglish
Title of host publication11th International Conference on Damage Assessment of Structures
Place of PublicationBristol
PublisherIOP Publishing Ltd.
Number of pages8
Publication statusPublished - 2015
Event11th International Conference on Damage Assessment of Structures (DAMAS) - Ghent, Belgium
Duration: 24 Aug 201526 Aug 2015

Publication series

NameJournal of Physics Conference Series
ISSN (Print)1742-6588


Conference11th International Conference on Damage Assessment of Structures (DAMAS)


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