LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
R. Riva; S. Cacciola; C. L. Bottasso; C. L. Bottasso (2016)
Publisher: Copernicus Publications
Journal: Wind Energy Science
Languages: English
Types: Article
Subjects: TJ807-830, Renewable energy sources
The formulation is model-independent, in the sense that it does not require knowledge of the equations of motion of the periodic system being analyzed, and it is applicable to an arbitrary number of blades and to any configuration of the machine. In addition, as wind turbulence can be viewed as a stochastic disturbance, the method is also applicable to real wind turbines operating in the field.

The characteristics of the new method are verified first with a simplified analytical model and then using a high-fidelity multi-body model of a multi-MW wind turbine. Results are compared with those obtained by the well-known operational modal analysis approach.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Allen, M. S. and Ginsberg, J. H.: Floquet modal analysis to detect cracks in a rotating shaft on anisotropic supports, Proceedings of 24th IMAC Conference, 30 January-2 February 2006, St. Louis, Missouri, 2006.
    • Allen, M. S., Chauhan, S., and Hansen, M. H.: Advanced operational modal analysis methods for linear time periodic system identification, Proceedings of 29th IMAC Conference, 31 January-3 February 2011, Jacksonville, Florida, doi:10.1007/978-1-4419-9316-8_3, 2011a.
    • Allen, M. S., Sracic, M. W., Chauhan, S., and Hansen, M. H.: Output-only modal analysis of linear time periodic systems with application to wind turbine simulation data, Mech. Syst. Signal Pr., 25, 1174-1191, doi:10.1016/j.ymssp.2010.12.018, 2011b.
    • Avendaño-Valencia, L. D. and Fassois, S. D.: In-operation identification of wind turbine non-stationary dynamics: a comparison of various methods, Proceedings of 5th IOMAC Conference, 13- 15 May 2013, Guimarães, Portugal, 2013.
    • Avendaño-Valencia, L. D. and Fassois, S. D.: Stationary and nonstationary random vibration modelling and analysis for an operating wind turbine, Mech. Syst. Signal Pr., 47, 263-285, doi:10.1016/j.ymssp.2013.07.022, 2014.
    • Bertogalli, V., Bittanti, S., and Lovera, M.: Simulation and identification of helicopter rotor dynamics using a generalpurpose multibody code, J. Franklin I., 366, 783-797, doi:10.1016/S0016-0032(98)00053-2, 1999.
    • Bittanti, S. and Colaneri, P.: Periodic Systems - Filtering and Control, Springer-Verlag, London, 2009.
    • Bittanti, S. and De Nicolao, G.: Spectral factorization of linear periodic systems with application to the optimal prediction of periodic ARMA models, Automatica, 29, 517-522, doi:10.1016/0005-1098(93)90149-N, 1993.
    • Bittanti, S., Bolzern, P., De Nicolao, G., Piroddi, L., and Purassanta, D. A.: Minimum prediction error algorithm for estimation of periodic ARMA models, Proceeding of the ECC 1991 European Control Conference, Grenoble, France, 1200-1203, 1991.
    • Bittanti, S., Bolzern, P., De Nicolao, L., and Piroddi, L.: Representation, prediction and identification of cyclostationary processes - A state space approach, in: Cyclostationarity in Communications and Signal Processing, edited by: Gardner W. A., IEEE Press, Piscataway, NJ, 267-294, 1994.
    • Borri, M.: Helicopter Rotor Dynamics by Finite Element Time Approximation, Comput. Math. Appl., 12, 149-160, doi:10.1016/0898-1221(86)90092-1, 1986.
    • Bottasso, C. L. and Cacciola, S.: Model-independent periodic stability analysis of wind turbines, Wind Energy, 18, 865-887, doi:10.1002/we.1735, 2015.
    • Bottasso, C. L. and Croce, A.: Cp-Lambda: User's Manual, Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano, Milano, Italy, 2006-2016.
    • Bottasso, C. L., Cacciola, S. and Riva, R.: Floquet stability analysis of wind turbines using input-output models, Proceedings of AIAA Scitech - 32nd ASME Wind Energy Symposium, 13-17 January 2014, National Harbor, MD, USA, doi:10.2514/6.2014-0713, 2014.
    • Byrd, R. H., Hribar, M. E., and Nocedal, J.: An interior point algorithm for large scale nonlinear programming, SIAM J. Optimiz., 9, 8777-900, doi:10.1137/S1052623497325107, 1999.
    • Byrd, R. H., Gilbert, J. C., and Nocedal, J.: A trust region method based on interior point techniques for nonlinear programming, Math. Program., 89, 149-185, doi:10.1007/PL00011391, 2000.
    • Carne, T. G. and James III, G. H.: The inception of OMA in the development of modal testing technology for wind turbines, Mech. Syst. Signal Pr., 24, 1213-1226, doi:10.1016/j.ymssp.2010.03.006, 2010.
    • Chauhan, S., Hansen, M. H., and Tcherniak, D.: Application of operational modal analysis and blind source separation/independent component analysis techniques to wind turbines, Proceedings of 27th IMAC Conference, 9-12 February 2009, Orlando, Florida, 2009.
    • Coleman, R. P. and Feingold, A. M.: Theory of self-excited mechanical oscillations of helicopter rotors with hinged blades, NACA Report TN 1351, 1958.
    • Eggleston, D. M. and Stoddard, F. S.: Wind Turbine Engineering Design, Van Nostrand Reinhold, New York, NY, USA, 1987.
    • Franklin, G. F. and Powell, J. D.: Digital Control of Dynamical Systems, 1st Edn., Addison-Wesley Publishing Company, Reading, MA, USA, 1980.
    • Hansen, M. H.: Aeroelastic stability analysis of wind turbines using an eigenvalue approach, Wind Energy, 7, 133-143, doi:10.1002/we.116, 2004.
    • Hansen, M. H., Thomsen, K., and Fuglsang, P.: Two methods for estimating aeroelastic damping of operational wind turbine modes from experiments, Wind Energy, 9, 179-191, doi:10.1002/we.187, 2006.
    • Hansen, M. O. L., Sørensen, J. N., Voutsinas, S., Sørensen, N., and Madsen, H. A.: State of the art in wind turbine aerodynamics and aeroelasticity, Prog. Aerosp. Sci., 42, 285-330, doi:10.1016/j.paerosci.2006.10.002, 2006.
    • Hauer, J. F., Demeure, C. J., and Scharf, L. L.: Initial results in Prony analysis of power system response signal, IEEE T. Power Syst., 5, 80-89, doi:10.1109/59.49090, 1990.
    • Jonkman, B. J. and Kilcher, L.: TurbSim User's Guide: Version 1.06.00, NREL Technical report, 2012.
    • Kutner, M. H., Nachtsheim, C. J., Neter, J., and Li, W.: Applied Linear Statistical Models, 5th Edn., McGraw-Hill/Irwin, New York, 2005.
    • Ljung, L.: System Identification - Theory for the User, 2nd Edn., Prentice Hall, Englewood Cliffs, NJ, USA, 1999.
    • Manwell, J. F., McGowan, J. G., and Rogers, A. L.: Wind Energy Explained - Theory, Design and Application, Wiley, New York, 2009.
    • Mevel, L., Gueguen, I., and Tcherniak, D.: LPTV subspace analysis of wind turbine data, 7th European Workshop on Structural Health Monitoring, 8-11 July 2014, La Cité, Nantes, France, 221-228, 2014.
    • Murtagh, P. J. and Basu, B.: Identification of equivalent modal damping for a wind turbine at standstill using Fourier and wavelet analysis, Proceedings of the Institution of Mechanical Engineers, Part K, J. Multi-body Dynam., 221, 577-589, doi:10.1243/14644193JMBD90, 2007.
    • Peters, D. A. and Lieb, S. M., and Ahaus, L. A.: Interpretation of Floquet eigenvalues and eigenvectors for periodic systems, J. Am. Helicopt. Soc., 56, 1-11, doi:10.4050/JAHS.56.032001, 2011.
    • Rissanen, J.: Algorithms for triangular decomposition of block Hankel and Toeplitz matrices with application to factoring positive matrix polynomials, Math. Comput., 27, 247-154, doi:10.1090/S0025-5718-1973-0329235-5, 1973.
    • Sandberg, H., Möllerstedt, B., and Bernhardsson, B.: Frequencydomain analysis of Linear Time Periodic Systems, IEEE T. Automat. Contr., 50, 1971-1983, doi:10.1109/TAC.2005.860294, 2005.
    • Sayed, A. H. and Kailath, T.: A survey of spectral factorization methods, Numer. Lin. Algebr., 8, 467-496, doi:10.1002/nla.250, 2001.
    • Shifei, Y. and Allen, M. S.: Output-only modal analysis using continuous scan laser doppler vibrometry and application to a 20 kW wind turbine, Mech. Syst. Signal Pr., 31, 228-245, doi:10.1016/j.ymssp.2012.04.012, 2012.
    • Shifei, Y. and Allen, M. S.: Lifting approach to simplify outputonly continuous-scan laser vibrometry, Mech. Syst. Signal Pr., 45, 267-282, doi:10.1016/j.ymssp.2013.11.010, 2014.
    • Skjoldan, P. F. and Bauchau, O. A.: Determination of modal parameters in complex nonlinear systems, J. Comput. Nonlin. Dynam., 6.3, 031017, doi:10.1115/1.4002975, 2011.
    • Skjoldan, P. F. and Hansen, M. H.: On the similarity of the Coleman and Lyapunov-Floquet transformations for modal analysis of bladed rotor structures, J. Sound Vibrat., 327, 424-439, doi:10.1016/j.jsv.2009.07.007, 2009.
    • Skjoldan, P. F. and Hansen, M. H.: Implicit Floquet analysis of wind turbines using tangent matrices of a non-linear aeroelastic code, Wind Energy, 15, 275-287, doi:10.1002/we.467, 2012.
    • Skjoldan, P. F. and Hansen, M. H.: Effects of extreme wind shear on aeroelastic modal damping of wind turbines, Wind Energy, 16, 401-415, doi:10.1002/we.1495, 2013.
    • Spiridonakos, M. D. and Fassois, S. D.: FS-TARMA models for non-stationary vibration analysis: an overview and comparison, 15th IFAC Symposium on System Identification, 6- 8 July 2009, Saint Malo, France, doi:10.3182/20090706-3-fr2004.00206, 2009.
    • Tcherniak, D., Chauhan, S., and Hansen, M. H.: Applicability limits of operational modal analysis to operational wind turbines, Proceedings of 28th IMAC Conference, 1-4 February 2010, Jacksonville, Florida, doi:10.1007/978-1-4419-9716-6_29, 2010.
    • Thomsen, K., Petersen, J. T., Nim, E., Øye, S., and Petersen, B.: A method for determination of damping for edgewise blade vibrations, Wind Energy, 3, 233-246, doi:10.1002/we.42, 2000.
    • Waltz, R. A., Morales, J. L., Nocedal, J., and Orban, D.: An interior algorithm for nonlinear optimization that combines line search and trust region steps, Math. Program., 107, 391-408, doi:10.1007/s10107-004-0560-5, 2006.
    • Wereley, N. M.: Analysis and control of linear periodically time varying systems, PhD thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, 1991.
    • Wereley, N. M. and Hall, S. R.: Frequency response of linear time periodic systems, Proceedings of the 29th IEEE Conference on Decision and Control, Honolulu, USA, 3650-3655, doi:10.1109/CDC.1990.203516, 1990.
    • Wolfram Research: Mathematica, Version 9.0, Wolfram Research, Inc., Champaign, IL, 2013.
  • No related research data.
  • No similar publications.