Averaged cov-driven subspace identification for modal analysis of a modified troposkien blade with displacement measurement

Nadia Najafi, Mohammad Esmail Aryaee Panah, Uwe Schmidt Paulsen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

An operational modal analysis study has been carried out on a 1- kW, vertical-axis wind turbine rotor blade, using a stereo vision technique. Numerical simulation has also been carried out and results were compared to classical modal analysis and OMA results. The displacement time series used in the analysis are very short because of limitations in the image acquisition system. Short time series are not fully qualified for OMA and analyzing the data needs a proper method. Covariance driven Stochastic Subspace Identification method (SSI-cov) has been used for short time series like earthquakes. In the SSI-cov method, a block Toeplitz matrix is formed which contains output correlation functions. 10 displacement time series have been recorded with 187 Hz sampling rate, and about 3 time series were chosen to be analyzed. The block Toeplitz matrix of 3 time series are averaged out and the procedure how to analyse short time series is described in this paper. For OMA validation, a classical modal analysis is done with signals from accelerometers mounted on the blade. The blade is exited with a hammer. The natural frequencies are estimated by picking the peaks from the FRFs (Frequency Response Function) obtained at different points. Finally the natural frequencies and mode shapes obtained from classical modal analysis and OMA results are compared to numerical simulations of the blade with COMSOL.
Original languageEnglish
Title of host publicationProceedings of IOMAC'15
Publication date2015
Pages645-656
ISBN (Print)978-84-617-3880-9
Publication statusPublished - 2015
Event2015 International Operational Modal Analysis Conference - Gijón, Spain
Duration: 10 May 201514 May 2015

Conference

Conference2015 International Operational Modal Analysis Conference
CountrySpain
CityGijón
Period10/05/201514/05/2015

Keywords

  • Stereo vision
  • Operational Modal Analysis
  • Covariance driven SSI

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