Levenberg, K.: A method for the solution of certain non-linear problems in
least squares, Q. Appl. Math., 2,
164–168, 1944. a
Lutzmann, P., Goehler, B., Scherer-Kloeckling, C., Scherer-Negenborn, N.,
Brunner, S., van Putten, F., and Hill, C. A.: Laser Doppler Vibrometry on
Rotating Wind Turbine Blades, 18th Coherent Laser Radar Conference, boulder,
Colorado, USA, 2016. a
Marquardt, D. W.: An Algorithm for Least-Squares Estimation of Nonlinear
Parameters, J. Soc. Ind. Appl. Math.,
11, 431–441, 1963. a
Mayda, E., Obrecht, J., Dixon, K., Zamora, A., Mailly, L., Sievers, R., and
Singh, M.: Wind Turbine Rotor R&D – An OEM Perspective, International
Conference on Future Technologies for Wind Energy, Laramie, Wyoming, USA, 7–9 October, 2013. a
Nidec SSB Wind Systems GmbH: More than a well-rounded solution: BladeVision,
Brochure,
https://www.ssbwindsystems.de/pdf/SSB_Wind_Broschuere_BladeVision_EN.pdf, last access: 31 January 2020. a
Ozbek, M. and Rixen, D. J.: Operational Modal Analysis of a 2.5 MW Wind Turbine
using Optical Measurement Techniques and Strain Gauges, Wind Energy, 16,
367–381, 2013. a
Rubak, R. and Petersen, J. T.: Monopile as Part of Aeroelastic Wind Turbine
Simulation Code, Proceedings of Copenhagen Offshore Wind, Copenhagen, Denmark, 26–28 October 2005. a
Schmidt Paulsen, U., Erne, O., Möller, T., Sanow, G., and Schmidt, T.: Wind
Turbine Operational and Emergency Stop Measurements Using Point Tracking
Videogrammetry, Proceedings of the 2009 SEM Annual Conference & Exposition
on Experimental & Applied Mechanic, Albuquerque, New Mexico, USA,
1–4 June 2009, 1128–1137, 2009. a
Skjoldan, P.: Aeroelastic modal dynamics of wind turbines including anisotropic
effects, PhD Thesis, Technical University of Denmark, Riso National Laboratory for Sustainable Energy, DTU Risoe-PhD-66, 2011. a
Sutton, M. A., Orteu, J. J., and Schreier, H.: Image Correlation for Shape,
Motion and Deformation Measurements: Basic Concepts, Theory and Applications,
Springer US, ISBN 978-0-387-78747-3, 2009.
a,
b
Veers, P., Dykes, K., Lantz, E., Barth, S., Bottasso, C. L., Carlson, O.,
Clifton, A., Green, J., Green, P., Holttinen, H., Laird, D., Lehtomäki,
V., Lundquist, J. K., Manwell, J., Marquis, M., Meneveau, C., Moriarty, P.,
Munduate, X., Muskulus, M., Naughton, J., Pao, L., Paquette, J., Peinke, J.,
Robertson, A., Sanz Rodrigo, J., Sempreviva, A. M., Smith, J. C., Tuohy, A.,
and Wiser, R.: Grand challenges in the science of wind energy, Science, 366, 6464,
https://doi.org/10.1126/science.aau2027,
2019.
a
Winstroth, J. and Seume, J. R.: Wind Turbine Rotor Blade Monitoring Using
Digital Image Correlation: Assessment on a Scaled Model, 32nd ASME Wind
Energy Symposium, 13–17 January 2014, National Harbor, Maryland,
2014a. a
Winstroth, J. and Seume, J. R.: Wind Turbine Rotor Blade Monitoring Using
Digital Image Correlation: 3D Simulation of the Experimental Setup, EWEA
2014, 10–13 March 2014, Barcelona, Spain, 2014b. a
Winstroth, J. and Seume, J. R.: Error Assessment of Blade Deformation
Measurements on a Multi-Megawatt Wind Turbine Based on Digital Image
Correlation, Proceedings of the ASME Turbo Expo, GT2014-43622, Montréal, Canda, 15–19 June 2015.
a,
b
Winstroth, J., Schoen, L., Ernst, B., and Seume, J. R.: Wind Turbine Rotor
Blade Monitoring Using Digital Image Correlation: A Comparison to Aeroelastic
Simulations of a Multi-Megawatt Wind Turbine, J. Phys. Conf.
Ser., 524, 012064,
https://doi.org/10.1088/1742-6596/524/1/012064, 2014.
a
Wiser, R., Jenni, K., Seel, J., Baker, E., Hand, M., Lantz, E., and Smith, A.:
Forecasting Wind Energy Costs and Cost Drivers: The Views of the World’s
Leading Experts, Tech. rep., IEA Wind Task 26, 2016. a
Wu, R., Zhang, D., Yu, Q., Jiang, Y., and Arola, D.: Health monitoring of wind
turbine blades in operation using three-dimensional digital image
correlation, Mech. Syst. Signal Pr., 130, 470–483,
https://doi.org/10.1016/j.ymssp.2019.05.031, 2019.
a