Fundamental natural frequencies investigation for a typical 5-MW wind turbine blade

Continuous structures such as beams, rods and plates can be modelled by discrete mass and stiffness parameters and analysed as multi-degree-of-freedom systems. The analysis of structural vibration is necessary to obtain the natural frequencies of a structure and the response to the external excitation. In this way, it can be determined whether a particular structure will fulfil its intended function and, in addition, the results of the dynamic loadings acting on a structure can be predicted. The lack of a sober analytical research about the vibrational behaviour of the 5-MW wind turbine blade pushed us to investigate about this crucial issue, however, most of the discreet researches are concerned with the aerodynamic effects rather than structural analysis. In this article, Rayleigh–Ritz method was implemented for a typical 5-MW wind turbine blade. MATLAB codes were developed and natural frequencies were obtained for both flapwise and edgewise vibrational behaviour. A good agreement was observed between the analytical results and the manufacturer results.

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Modal analysis of an iced offshore composite wind turbine blade

Wind Engineering ◽

10.1177/0309524x211011685 ◽

2021 ◽

pp. 0309524X2110116

Author(s):

Oumnia Lagdani ◽

Mostapha Tarfaoui ◽

Mourad Nachtane ◽

Mourad Trihi ◽

Houda Laaouidi

Keyword(s):

Wind Turbine ◽

Modal Analysis ◽

Turbine Blade ◽

Natural Frequencies ◽

Wind Turbine Blade ◽

Resonance Phenomenon ◽

Mode Shapes ◽

The Finite Element Method ◽

Numerical Work ◽

Composite Blades

In the far north, low temperatures and atmospheric icing are a major danger for the safe operation of wind turbines. It can cause several problems in fatigue loads, the balance of the rotor and aerodynamics. With the aim of improving the rigidity of the wind turbine blade, composite materials are currently being used. A numerical work aims to evaluate the effect of ice on composite blades and to determine the most adequate material under icing conditions. Different ice thicknesses are considered in the lower part of the blade. In this paper, modal analysis is performed to obtain the natural frequencies and corresponding mode shapes of the structure. This analysis is elaborated using the finite element method (FEM) computer program through ABAQUS software. The results have laid that the natural frequencies of the blade varied according to the material and thickness of ice and that there is no resonance phenomenon.

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Experimental updating of a segmented wind turbine blade numerical model using the substructure method

The Journal of Strain Analysis for Engineering Design ◽

10.1177/0309324720932786 ◽

2020 ◽

pp. 030932472093278

Author(s):

Majdi Yangui ◽

Slim Bouaziz ◽

Mohamed Taktak ◽

Mohamed Haddar

Keyword(s):

Numerical Model ◽

Wind Turbine ◽

Turbine Blade ◽

Natural Frequencies ◽

Model Updating ◽

Mechanical Performance ◽

Shell Element ◽

Wind Turbine Blade ◽

Model Parameters ◽

Fused Deposition

During the development of the wind turbine system, blades are considered as the most critical components. The blades’ dynamic characteristics must be investigated during the design process to improve their mechanical performance. This work presents an experimental updating of a segmented wind turbine blade numerical model. For this purpose, the blade segments were manufactured using the fused deposition 3D printing technology and assembled using a threaded spar and nut. For different values of the segments assembly load, the natural frequencies and damping ratios were identified using the eigensystem realization algorithm method. The dynamic behavior of the segmented blade was examined numerically using the three-node shell element, taking into consideration the additional stiffness generated by the applied assembly load. In this study, numerical and experimental modal analysis were used to identify the first five eigenfrequencies of the blade. To update the numerical model parameters, through the identified experimental results, an iterative method was developed based on the Craig–Bampton substructure approach. Results show that the blade natural frequencies are proportional to the segments assembly load. The application of the proposed method on the segmented blade numerical model updating shows that the present method is computationally efficient.

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Dynamic and Aeroelastic Analyses of a Wind Turbine Blade Modeled as a Thin-Walled Composite Beam

Volume 6B: Energy ◽

10.1115/imece2014-38679 ◽

2014 ◽

Cited By ~ 1

Author(s):

Serhat Yilmaz ◽

Seher Eken ◽

Metin O. Kaya

Keyword(s):

Wind Turbine ◽

Turbine Blade ◽

Transverse Shear ◽

Natural Frequencies ◽

Equations Of Motion ◽

Wind Turbine Blade ◽

Mode Shapes ◽

Box Beam ◽

Aeroelastic Analysis ◽

Thin Walled

In this paper, dynamic and aeroelastic analysis of a wind turbine blade modeled as an anisotropic composite thin-walled box beam is carried out. The analytical formulation of the beam is derived for the flapwise bending, chordwise bending and transverse shear deformations. The derivation of both strain and kinetic energy expressions are made and the equations of motion are obtained by applying the Hamilton’s principle. The equations of motion are solved by applying the extended Galerkin method (EGM) for anti-symmetric lay-up configuration that is also referred as Circumferentially Uniform Stiffness (CUS). As a result various coupled vibration modes are exhibited. This type of beam features two sets of independent couplings: i) extension-torsion coupling, ii) flapwise/chordwise bending-flapwise/chorwise transverse shear coupling. For both cases, the natural frequencies are validated by making comparisons with the results in literature and effects of coupling, transverse shear, ply-angle orientation, and rotational speed on the natural frequencies are examined and the mode shapes of the rotating thin-walled composite beams are further obtained. Blade element momentum theory (BEMT) is utilized to model the wind turbine blade aerodynamics. After combining the structural and the aerodynamic models, the aeroelastic analysis are performed and flutter boundaries are obtained.

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Continuous wavelet transform-based method for enhancing estimation of wind turbine blade natural frequencies and damping for machine learning purposes

Measurement ◽

10.1016/j.measurement.2020.108897 ◽

2021 ◽

Vol 172 ◽

pp. 108897

Author(s):

R. Janeliukstis

Keyword(s):

Machine Learning ◽

Wavelet Transform ◽

Wind Turbine ◽

Turbine Blade ◽

Continuous Wavelet Transform ◽

Natural Frequencies ◽

Wind Turbine Blade ◽

Continuous Wavelet

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Detection of ice mass based on the natural frequencies of wind turbine blade

10.5194/wes-2016-30 ◽

2016 ◽

Author(s):

Sudhakar Gantasala ◽

Jean-Claude Luneno ◽

Jan-Olov Aidanpaa

Keyword(s):

Wind Turbine ◽

Turbine Blade ◽

Mass Distribution ◽

Natural Frequencies ◽

Wind Turbine Blade ◽

Cold Climate ◽

Training Data ◽

Ann Model ◽

Data Set ◽

Mass Distributions

Abstract. Wind turbines installed in the cold climate regions accumulate ice on the blades affecting their aeroelastic behavior and turbine power output. It is essential to detect icing in the early stages to start the deicing systems so that the losses due to icing can be minimized. The increase in mass distribution of the blade due to icing reduces its natural frequencies and how much these frequencies reduce depends on the amount of ice mass and their location on the blade. Ice detection systems like BLADEControl (Bosch Rexroth) and fos4blade IceDetection (fos4X) systems detect ice based on the deviations in blade natural frequencies, but cannot identify the location and amount of ice mass. In this work, the authors propose a method to detect average ice mass accumulated along three zones defined along the blade based on its natural frequencies using Artificial Neural Networks (ANN). Different ice masses are added on a wind turbine blade and their natural frequencies are simulated using a finite element model of the blade vibrations. ANN is trained with the natural frequencies of the iced blade as inputs and corresponding ice mass distributions used in the three zones as outputs. ANN approximates the non-linear function between inputs and outputs in the training process. After training with a large data set of possible ice mass distributions, ANN model can be used to predict ice mass distributions in the three zones for any set of natural frequencies (input to ANN) of the iced blade. NREL 5 MW wind turbine blade is considered in this study to demonstrate the proposed method. Various cases of ice mass distributions are tested by the trained ANN model and the predicted ice mass distributions are compared against actual ice mass distribution values. ANN model is able to predict ice mass distributions exactly if they are similar to the ice mass distributions used in the training data, otherwise the ice masses are predicted with an error. Overall, the proposed method is able to approximately detect average ice mass accumulated along the blade which is not possible before.

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