Damage detection in wind turbine blades based on time series correlations

S. Hoell, P. Omenzetter

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

1 Citation (Scopus)

Abstract

Changes in public energy policies with increasing emphasis on renewable sources lead to ever growing sizes of wind turbines and erections in remote areas, such as offshore. For wind energy, operations and maintenance can make up to 20% of the total energy production costs, which adversely affects production targets and expected revenues. In order to ensure progress in wind energy technologies, effective structural health monitoring for wind turbine blades (WTBs) is one approach that can make a difference. The present paper shows an application of a novel localised vibration based structural damage detection (SDD) technique for WTBs based on the correlations between vibrational responses measured by a sensor array. Firstly, the theory of signal cross-correlation and statistical hypothesis testing for SDD are introduced. Then, advanced numerical simulations of a large WTB are performed for SDD under aerodynamic loading. Finally, the setup and preliminary experimental work conducted on a small scale WTB are discussed. The obtained results demonstrate the advantages of the novel approach, which are promising for future developments of SDD methods for WTBs.

Original languageEnglish
Title of host publicationSHMII 2015 - 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure
EditorsA De Stefano
PublisherInternational Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII
Pages1-10
Number of pages10
DOIs
Publication statusPublished - 2015
Event7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015 - Torino, Italy
Duration: 1 Jul 20153 Jul 2015

Conference

Conference7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015
CountryItaly
CityTorino
Period1/07/153/07/15

ASJC Scopus subject areas

  • Building and Construction
  • Civil and Structural Engineering
  • Artificial Intelligence

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  • Cite this

    Hoell, S., & Omenzetter, P. (2015). Damage detection in wind turbine blades based on time series correlations. In A. De Stefano (Ed.), SHMII 2015 - 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure (pp. 1-10). International Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII. https://doi.org/10.13140/RG.2.1.2310.5123