Output-only modal analysis of wind turbine tower based on vibration response under emergency stop.

Abstract The identification technique of output-only modal parameters is proposed for the large wind turbine tower under emergency stop. Compared with the response of regular operating conditions, the immediate tower structural response under emergency stop much more resembles a state of free vibration, which is more appropriate for the modal identification of the wind turbine tower. The vibration response is measured in the nacelle, which is easy to perform in the field modal test. The variational mode decomposition (VMD) is applied to decompose the vibration response into several band-limited intrinsic mode functions. The free responses of decomposed functions are extracted by applying the random decrement technique (RDT). Finally, the modal damping ratio and natural frequency are identified from each free modal response by using the Hilbert transform method. Simulations and a 1.5 MW wind turbine field modal test results verify the effectiveness of the proposed identification method. The main modal parameters of wind turbine, including weak modes, are effectively extracted by using output-only vibration responses under emergency stop. The modal parameter identification method is provided for the large wind turbine structure under the engineering condition.

[1]  E. C. Mikulcik,et al.  A method for the direct identification of vibration parameters from the free response , 1977 .

[2]  Genda Chen,et al.  Analytical mode decomposition with Hilbert transform for modal parameter identification of buildings under ambient vibration , 2014 .

[3]  Yao Yao,et al.  Application of the Variational-Mode Decomposition for Seismic Time–frequency Analysis , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4]  Richard Russell,et al.  A Multi-Input Modal Estimation Algorithm for Mini-Computers , 1982 .

[5]  Ming Li,et al.  Variational mode decomposition denoising combined the detrended fluctuation analysis , 2016, Signal Process..

[6]  Peter Avitabile,et al.  Comparison of Modal Parameters Extracted Using MIMO, SIMO, and Impact Hammer Tests on a Three-Bladed Wind Turbine , 2014 .

[7]  Christof Devriendt,et al.  Experimental and computational damping estimation of an offshore wind turbine on a monopile foundation , 2013 .

[8]  Yachao Zhang,et al.  Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods , 2016 .

[9]  Thomas G. Carne,et al.  The Natural Excitation Technique (NExT) for modal parameter extraction from operating wind turbines , 1993 .

[10]  Brian Schwarz,et al.  Modal Parameter Estimation from Operating Data , 2003 .

[11]  P. Tse,et al.  An improved Hilbert–Huang transform and its application in vibration signal analysis , 2005 .

[12]  Jack E. Cermak,et al.  Random decrement based method for modal parameter identification of a dynamic system using acceleration responses , 2007 .

[13]  Darryll J. Pines,et al.  Structural health monitoring using empirical mode decomposition and the Hilbert phase , 2006 .

[14]  Palle Andersen,et al.  Modal Identification from Ambient Responses using Frequency Domain Decomposition , 2000 .

[15]  Dominique Zosso,et al.  Variational Mode Decomposition , 2014, IEEE Transactions on Signal Processing.

[16]  Yasuhiro Koda,et al.  Identifiable Stress State of Wind Turbine Tower-foundation System Based on Field Measurement and FE Analysis , 2014 .

[17]  Bart Peeters,et al.  Full-scale modal wind turbine tests: comparing shaker excitation with wind excitation , 2011 .

[18]  Yanxue Wang,et al.  Filter bank property of variational mode decomposition and its applications , 2016, Signal Process..

[19]  B. Peeters,et al.  Stochastic System Identification for Operational Modal Analysis: A Review , 2001 .

[20]  Xinqun Zhu,et al.  Time-varying system identification using a newly improved HHT algorithm , 2009 .

[21]  L. Battisti,et al.  In-field testing of a steel wind turbine tower , 2011 .

[22]  Carlos E. Ventura,et al.  Damping estimation by frequency domain decomposition , 2001 .

[23]  Shaohong Cheng,et al.  Structural Response of a Commercial Wind Turbine to Various Stopping Events , 2012 .

[24]  Patrick Guillaume,et al.  Experimental and computational damping estimation of an offshore wind turbine on a monopile foundation , 2013 .

[25]  Wenyi Liu,et al.  Status and problems of wind turbine structural health monitoring techniques in China , 2010 .

[26]  Ahmed Elgamal,et al.  Shake Table Testing of a Utility-Scale Wind Turbine , 2012 .

[27]  Yanxue Wang,et al.  Research on variational mode decomposition and its application in detecting rub-impact fault of the rotor system , 2015 .

[28]  Silian Lin,et al.  Identification of Natural Frequencies and Dampings of In Situ Tall Buildings Using Ambient Wind Vibration Data , 2004 .

[29]  Abdollah Bagheri,et al.  Structural system identification based on variational mode decomposition , 2018 .

[30]  Carlos A. Perez-Ramirez,et al.  New methodology for modal parameters identification of smart civil structures using ambient vibrations and synchrosqueezed wavelet transform , 2016, Eng. Appl. Artif. Intell..

[31]  Tong Wang,et al.  A frequency–spatial domain decomposition (FSDD) method for operational modal analysis , 2010 .

[32]  Lars Vabbersgaard Andersen,et al.  Cross-wind modal properties of offshore wind turbines identified by full scale testing , 2013 .

[33]  Jer-Nan Juang,et al.  An eigensystem realization algorithm for modal parameter identification and model reduction. [control systems design for large space structures] , 1985 .

[34]  Thomas G. Carne,et al.  The inception of OMA in the development of modal testing technology for wind turbines , 2010 .

[35]  C. Gontier,et al.  Robustness of an arma identification method for modal analysis of mechanical systems in the presence of noise , 1995 .

[36]  N. Huang,et al.  System identification of linear structures based on Hilbert–Huang spectral analysis. Part 1: normal modes , 2003 .