Nonlinear Flap-Wise Vibration Characteristics ofWind Turbine Blades Based onMulti-Scale AnalysisMethod

This work presents a novel approach to achieve nonlinear vibration response based on the Hamilton principle.We chose the 5-MW reference wind turbine which was established by the National Renewable Energy Laboratory(NREL),to research the effects of the nonlinear flap-wise vibration characteristics.The turbine wheel is simplified by treating the blade of a wind turbine as an Euler-Bernoulli beam,and the nonlinear flap-wise vibration characteristics of the wind turbine blades are discussed based on the simplification first.Then,the blade’s large-deflection flap-wise vibration governing equation is established by considering the nonlinear term involving the centrifugal force.Lastly,it is truncated by the Galerkin method and analyzed semi-analytically using the multi-scale analysis method,and numerical simulations are carried out to compare the simulation results of finite elements with the numerical simulation results using Campbell diagram analysis of blade vibration.The results indicated that the rotational speed of the impeller has a significant impact on blade vibration.When the wheel speed of 12.1 rpm and excitation amplitude of 1.23 the maximum displacement amplitude of the blade has increased from 0.72 to 3.16.From the amplitude-frequency curve,it can be seen that the multi-peak characteristic of blade amplitude frequency is under centrifugal nonlinearity.Closed phase trajectories in blade nonlinear vibration,exhibiting periodic motion characteristics,are found through phase diagrams and Poincare section diagrams.

Videometric research on deformation measurement of large-scale wind turbine blades

Utilization of wind energy is a promising way to generate power,and wind turbine blades play a key role in collecting the wind energy effectively.This paper attempts to measure the deformation parameter of wind turbine blades in mechanics experiments using a videometric method. In view that the blades experience small buckling deformation and large integral deformation simultaneously, we proposed a parallel network measurement(PNM) method including the key techniques such as camera network construction,camera calibration,distortion correction,the semi-automatic high-precision extraction of targets,coordinate systems unification,and bundle adjustment,etc. The relatively convenient construction method of the measuring system can provide an abundant measuring content,a wide measuring range and post processing.The experimental results show that the accuracy of the integral deformation measurement is higher than 0.5 mm and that of the buckling deformation measurement higher than 0.1mm.

Stiffness Degradation Modeling for Composite Wind Turbine Blades Based on Full-Scale Fatigue Testing

In order to provide more insights into the damage propagation composite wind turbine blades(blade)under cyclic fatigue loading,a stiffness degradation model for blade is proposed based on the full-scale fatigue testing of a blade.A novel non-linear fatigue damage accumulation model is proposed using the damage assessment theories of composite laminates for the first time.Then,a stiffness degradation model is established based on the correlation of fatigue damage and residual stiffness of the composite laminates.Finally,a stiffness degradation model for the blade is presented based on the full-scale fatigue testing.The scientific rationale of the proposed stiffness model of blade is verified by using full-scale fatigue test data of blade with a total length of 52.5 m.The results indicate that the proposed stiffness degradation model of the blade agrees well with the fatigue testing results of this blade.This work provides a basis for evaluating the fatigue damage and lifetime of blade under cyclic fatigue loading.

An Advanced Control Strategy for Dual-Actuator Driving System in Full-Scale Fatigue Test of Wind Turbine Blades

A new dual-actuator fatigue loading system of wind turbine blades was designed.Compared with the traditional pendulum loading mode,the masses in this system only moved linearly along the loading direction to increase the exciting force.However,the two actuators and the blade constituted a complicated non-linear energy transferring system,which led to the non-synchronization of actuators.On-site test results showed that the virtual spindle synchronous strategy commonly used in synchronous control was undesirable and caused the instability of the blade’s amplitude eventually.A cross-coupled control strategy based on the active disturbance rejection algorithm was proposed.Firstly,a control system model was built according to the synchronization error and tracking error.Furthermore,based on arranging the transition process,estimating the system state and error feedback,and compensating disturbance,an active disturbance rejection controller was designed by adopting the optimal control function.Finally,on-site test results showed that the cross-coupled control strategy based on the active disturbance rejection algorithm could ensure the synchronization of two actuators.The maximum speed synchronization error of the two motors was less than 16 RPM,the displacement synchronization error of the two actuators was less than 0.25 mm and approaching zero after 4 seconds,and the peak value of vibration of the blade was less than 5 mm,which satisfied the fatigue test requirement.

Monitoring of Wind Turbine Blades Based on Dual-Tree Complex Wavelet Transform

Structural health monitoring(SHM)in-service is very important for wind turbine system.Because the central wavelength of a fiber Bragg grating(FBG)sensor changes linearly with strain or temperature,FBG-based sensors are easily applied to structural tests.Therefore,the monitoring of wind turbine blades by FBG sensors is proposed.The method is experimentally proved to be feasible.Five FBG sensors were set along the blade length in order to measure distributed strain.However,environmental or measurement noise may cover the structural signals.Dual-tree complex wavelet transform(DT-CWT)is suggested to wipe off the noise.The experimental studies indicate that the tested strain fluctuate distinctly as one of the blades is broken.The rotation period is about 1 s at the given working condition.However,the period is about 0.3 s if all the wind blades are in good conditions.Therefore,strain monitoring by FBG sensors could predict damage of a wind turbine blade system.Moreover,the studies indicate that monitoring of one blade is adequate to diagnose the status of a wind generator.

An Automated Ultrasonic NDT System for In-Situ Inspection of Wind Turbine Blades

It is crucial to maintain wind turbine blades regularly, due to the high stress leading to defects or damage. Conventional methods require shipping the blades to a workshop for off-site inspection, which is extremely time-consuming and very costly. This work investigates the use of pulse-echo ultrasound to detect internal damages in wind turbine blades without the necessity to ship the blades off-site. A prototype 2D ultrasonic NDT （non-destructive testing） system has been developed and optimised for in-situ wind turbine blade inspection. The system is designed to be light weight so it can be easily carried by an inspector onto the wind turbine blade for in-situ inspection. It can be operated in 1D A-scan, 2D C-scan or 3D volume scan. A software system has been developed to control the automated scanning and show the damage areas in a 2D/3D map with different colours so that the inspector can easily identify the defective areas. Experiments on GFRP （glass fibre reinforced plastics） and wind turbine blades （made of GFRP） samples showed that internal defects can be detected. The main advantages of this system are fully automated 2D spatial scanning and the ability to alert the user to the damage of the inspected sample. It is intended to be used for in-situ inspection to save maintenance time and hence considered to be economically beneficial for the wind energy industry.

A Compact Laser Shearography System for On-Site Robotic Inspection of Wind Turbine Blades

Shearography is an optical technique in the field of nondestructive evaluation(NDE)of various materials.Its main advantages are that it is noncontact type and can cover a large area in a single inspection.As a result,although it has been widely acknowledged as an effective technique particularly for NDE of composite materials to detect subsurface defects such as delamination,disbond,cracks,and impact damages,the use of shearography for on-site inspection of wind turbine blades(WTBs)has not been reported.This is due to wind causing structural vibration in the WTB.The solution in this paper is to make the shearography sit on the WTB during inspection when the WTB is parked,so that the relative motion between the shearography and the WTB is minimized within the tolerance of the shearography system.The ultimate goal of the solution is to enable a robot-assisted shearography system to inspect the WTB on-site.This paper presents the research work on a new shearography design for integration with a robotic climber for on-site WTB inspection.The approach is tested and evaluated in experimental settings,and a comparative assessment of the approach with other robotic NDE techniques is carried out.The results demonstrate the potential benefits and suitability of the approach for on-site robotic inspection of WTBs.

Damage Identification of Wind Turbine Blades–A Brief Review

The increasing size of these blades of wind turbines emphasizes the need for reliable monitoring and maintenance.This brief review explores the detection and analysis of damage in wind turbine blades.The study highlights various techniques,including acoustic emission analysis,strain signal monitoring,and vibration analysis,as effective approaches for damage detection.Vibration analysis,in particular,shows promise for fault identification by analyzing changes in dynamic characteristics.Damage indices based on modal properties,such as natural frequencies,mode shapes,and curvature,are discussed.

Fast prediction of rain erosion in wind turbine blades using a data-based computational tool

Wind turbines(WTs)face a high risk of failure due to environmental factors like erosion,particularly in high-precipitation areas and offshore scenarios.In this paper we introduce a novel computational tool for the fast prediction of rain erosion damage on WT blades that is useful in operation and maintenance decision making tasks.The approach is as follows:Pseudo-Direct Numerical Simulation(P-DNS)simulations of the droplet-laden flow around the blade section profile are employed to build a high-fidelity data set of impact statistics for potential operating conditions.Using this database as training data,a machine learning-based surrogate model provides the feature of the impact pattern over the 2-D section for given wind and rain conditions.With this information,a fatigue-based model estimates the remaining lifetime and erosion damage for both homogeneous and coating-substrate blade materials.This prediction is done by quantifying the accumulated droplet impact energy and evaluating operative conditions over time periods for which the weather at the installation site is known.In this work,we describe the modules that compose the prediction method,namely the database creation,the training of the surrogate model and their coupling to build the prediction tool.Then,the method is applied to predict the remaining lifetime and erosion damage to the blade sections of a reference WT.To evaluate the reliability of the tool,several site locations(offshore,coastal,and inland),the coating material and the coating thickness of the blade are investigated.In few minutes we are able to estimate erosion after many years of operation.The results are in good agreement with field observations,showing the promise of the new rain erosion prediction approach.

Effect of Rigid Pitch Motion on Flexible Vibration Characteristics of a Wind Turbine Blade

Adynamic pitch strategy is usually adopted to improve the aerodynamic performance of the blade of awind turbine.The dynamic pitch motion will affect the linear vibration characteristics of the blade.However,these influences have not been studied in previous research.In this paper,the influences of the rigid pitch motion on the linear vibration characteristics of a wind turbine blade are studied.The blade is described as a rotating cantilever beam with an inherent coupled rigid-flexible vibration,where the rigid pitch motion introduces a parametrically excited vibration to the beam.Partial differential equations governing the nonlinear coupled pitch-bend vibration are proposed using the generalized Hamiltonian principle.Natural vibration characteristics of the inherent coupled rigid-flexible system are analyzed based on the combination of the assumed modes method and the multi-scales method.Effects of static pitch angle,rotating speed,and characteristics of harmonic pitch motion on flexible natural frequencies andmode shapes are discussed.It shows that the pitch amplitude has a dramatic influence on the natural frequencies of the blade,while the effects of pitch frequency and pith phase on natural frequencies are little.

Research on Fatigue Damage Behavior of Main Beam Sub-Structure of Composite Wind Turbine Blade

Given the difficulty in accurately evaluating the fatigue performance of large composite wind turbine blades(referred to as blades),this paper takes the main beam structure of the blade with a rectangular cross-sectionas the simulation object and establishes a composite laminate rectangular beam structure that simultaneouslyincludes the flange,web,and adhesive layer,referred to as the blade main beam sub-structure specimen,throughthe definition of blade sub-structures.This paper examines the progressive damage evolution law of the compositelaminate rectangular beam utilizing an improved 3D Hashin failure criterion,cohesive zone model,B-K failurecriterion,and computer simulation technology.Under static loading,the layup angle of the anti-shear web hasa close relationship with the static load-carrying capacity of the composite laminate rectangular beam;under fatigueloading,the fatigue damage will first occur in the lower flange adhesive area of the whole composite laminaterectangular beam and ultimately result in the fracture failure of the entire structure.These results provide a theoreticalreference and foundation for evaluating and predicting the fatigue performance of the blade main beamstructure and even the full-size blade.

Multifunctional nanocomposite coating for wind turbine blades

In this study,multifunctional carbon nanofiber(CNF)paper-based nanocomposite coating was developed for wind turbine blades.The importance of vibration damping in relation to structural stability,dynamic response,position control,and durability of wind turbine blades cannot be underestimated.The vibration damping properties of the nanocomposite blades were significantly improved and the damping ratio of the nanocomposite increased by 300%compared to the baseline composite.In addition,the CNF paper-based composite exhibited good impact-friction resistance,with a wear rate as low as 1.78×10^(−4)mm^(3)/Nm.The nanocomposite also shows the potential to improve the blockage of water from entering the nanocomposite,being a superhydrophobic material,with a contact angle higher than 160.0◦,which could improve the longevity of a wind turbine blade.Overall,multifunctional nanocomposite coating material shows great promise for usage with wind turbine blades,owing to its excellent damping properties,great friction resistance,and superhydrophobicity.

Research on the Follow-Up Control Strategy of Biaxial Fatigue Test of Wind Turbine Blade Based on Electromagnetic Excitation

Aiming at the drift problem that the tracking control of the actual load relative to the target load during the electromagnetic excitation biaxial fatigue test of wind turbine blades is easy to drift,a biaxial fatigue testingmachine for electromagnetic excitation is designed,and the following strategy of the actual load and the target load is studied.A Fast Transversal Recursive Least Squares algorithm based on fuzzy logic(Fuzzy FTRLS)is proposed to develop a fatigue loading following dynamic strategy,which adjusts the forgetting factor in the algorithmthrough fuzzy logic to overcome the contradiction between convergence accuracy and convergence speed and solve the phenomenon of amplitude overshoot and phase lag of the actual load relative to the target load.Combined with the previous research results,a simulation model was constructed to verify the strategy’s effectiveness.Field tests were carried out to verify its follow-up effect.The results showthat the tracking error of flapwise and edgewise direction iswithin 4%,which has better robustness and dynamic and static performance than the traditional Recursive Least Squares(RLS)algorithm.

Parameter sensitivities analysis for classical flutter speed of a horizontal axis wind turbine blade

The parameter sensitivities affecting the flutter speed of the NREL （National Renewable Energy Laboratory） 5-MW baseline HAWT （horizontal axis wind turbine） blades are analyzed. An aeroelastic model, which comprises an aerodynamic part to calculate the aerodynamic loads and a structural part to determine the structural dynamic responses, is established to describe the classical flutter of the blades. For the aerodynamic part, Theodorsen unsteady aerodynamics model is used. For the structural part, Lagrange’s equation is employed. The flutter speed is determined by introducing “V–g” method to the aeroelastic model, which converts the issue of classical flutter speed determination into an eigenvalue problem. Furthermore, the time domain aeroelastic response of the wind turbine blade section is obtained with employing Runge-Kutta method. The results show that four cases （i.e., reducing the blade torsional stiffness, moving the center of gravity or the elastic axis towards the trailing edge of the section, and placing the turbine in high air density area） will decrease the flutter speed. Therefore, the judicious selection of the four parameters （the torsional stiffness, the chordwise position of the center of gravity, the elastic axis position and air density） can increase the relative inflow speed at the blade section associated with the onset of flutter.

Fatigue Assessment Method for Composite Wind Turbine Blade

Fatigue strength assessment of a horizontal axis wind turbine(HAWT)composite blade is considered.Fatigue load cases are identified,and loads are calculated by the GH Bladed software which is specified at the IEC61400 international specification and GL(Germanisher Lloyd)regulations for the wind energy conversion system.Stress analysis is performed with a 3-D finite element method(FEM).Considering Saint-Venant′s principle,a uniform cross section FEM model is built at each critical zone.Stress transformation matrixes(STM)are set up by applied six unit load components on the FEM model separately.STM can be used to convert the external load into stresses in the linear elastic range.The main material of composite wind turbine blade is fiber reinforced plastics(FRP).In order to evaluate the degree of fatigue damage of FRP,the stresses of fiber direction are extracted and the well-known strength criterion-Puck theory is used.The total fatigue damage of each laminate on the critical point is counted by the rain-flow counting method and Miner′s damage law based on general S-N curves.Several sections of a 45.3mblade of a 2 MW wind turbine are studied using the fatigue evaluation method.The performance of this method is compared with far more costly business software FOCUS.The results show that the fatigue damage of multi-axis FRP can be assessed conveniently by the FEM-STM method.And the proposed method gives a reliable and efficient method to analyze the fatigue damage of slender composite structure with variable cross-sections.

Effects of Wind-Wave Misalignment on a Wind Turbine Blade Mating Process:Impact Velocities,Blade Root Damages and Structural Safety Assessment

Most wind turbine blades are assembled piece-by-piece onto the hub of a monopile-type offshore wind turbine using jack-up crane vessels.Despite the stable foundation of the lifting cranes,the mating process exhibits substantial relative responses amidst blade root and hub.These relative motions are combined effects of wave-induced monopile motions and wind-induced blade root motions,which can cause impact loads at the blade root’s guide pin in the course of alignment procedure.Environmental parameters including the wind-wave misalignments play an important role for the safety of the installation tasks and govern the impact scenarios.The present study investigates the effects of wind-wave misalignments on the blade root mating process on a monopile-type offshore wind turbine.The dynamic responses including the impact velocities between root and hub in selected wind-wave misalignment conditions are investigated using multibody simulations.Furthermore,based on a finite element study,different impact-induced failure modes at the blade root for sideways and head-on impact scenarios,developed due to wind-wave misalignment conditions,are investigated.Finally,based on extreme value analyses of critical responses,safe domain for the mating task under different wind-wave misalignments is compared.The results show that although misaligned wind-wave conditions develop substantial relative motions between root and hub,aligned wind-wave conditions induce largest impact velocities and develop critical failure modes at a relatively low threshold velocity of impact.

Research on Surface Defect Detection Technology of Wind Turbine Blade Based on UAV Image

In the background of“double carbon,”vigorously developing new energy is particularly important.Wind power is an important clean energy source.In the field of new energy,wind power scale is also expanding.With the wind turbine,the probability of large-scale blade damage is also increasing.Because the large wind turbine blade crack detection cost is high and because of the poor working environment,this paper proposes a wind turbine blade surface defect detection method based on UAV acquisition images and digital image pro-cessing.The application of weighted averages to achieve grayscale processing,followed by median filtering to achieve image noise reduction,and an improved histogram equalization algorithm is proposed and used for the characteristics of the UAV acquisition images,which enhances the image by limiting the contrast adaptive his-togram equalization algorithm to make the details at the target area and defects more clear and complete,and improves the detection efficiency.The detection of the blade surface is achieved by separating and extracting the feature information from the defects through image foreground segmentation,threshold processing,and framing by the connected domain.The validity and accuracy of the proposed method in leaf detection were verified by experiments.

Criterion of aerodynamic performance of large-scale offshore horizontal axis wind turbines

With the background of offshore wind energy projects, this paper studies aerodynamic performance and geometric characteristics of large capacity wind turbine rotors （1 to 10 MW）, and the main characteristic parameters such as the rated wind speed, blade tip speed, and rotor solidity. We show that the essential criterion of a high- performance wind turbine is a highest possible annual usable energy pattern factor and a smallest possible dimension, capturing the maximum wind energy and producing the maximum annual power. The influence of the above-mentioned three parameters on the pattern factor and rotor geometry of wind turbine operated in China＇s offshore meteoro- logical environment is investigated. The variation patterns of aerodynamic and geometric parameters are obtained, analyzed, and compared with each other. The present method for aerodynamic analysis and its results can form a basis for evaluating aerodynamic performance of large-scale offshore wind turbine rotors.

A Comparative Study of Bayes Classifiers for Blade Fault Diagnosis in Wind Turbines through Vibration Signals

Renewable energy sources are considered much in energy fields because of thecontemporary energy calamities. Among the important alternatives being considered, windenergy is a durable competitor because of its dependability due to the development of theinnovations, comparative cost effectiveness and great framework. To yield wind energymore proficiently, the structure of wind turbines has turned out to be substantially bigger,creating conservation and renovation works troublesome. Due to various ecologicalconditions, wind turbine blades are subjected to vibration and it leads to failure. If thefailure is not diagnosed early, it will lead to catastrophic damage to the framework. In orderto increase safety observations, to reduce down time, to bring down the recurrence ofunexpected breakdowns and related enormous maintenance, logistic expenditures and tocontribute steady power generation, the wind turbine blade must be monitored now andthen to assure that they are in good condition. In this paper, a three bladed wind turbinewas preferred and using vibration source, the condition of a wind turbine blade is examined.The faults like blade crack, erosion, hub-blade loose connection, pitch angle twist and bladebend faults were considered and these faults are classified using Bayes Net (BN),Discriminative Multinomial Naïve Bayes (DMNB), Naïve Bayes (NB), Simple NaïveBayes (SNB), and Updateable Naïve Bayes (UNB) classifiers. These classifiers arecompared and better classifier is suggested for condition monitoring of wind turbine blades.

Comparative Study on Tree Classifiers for Application to Condition Monitoring ofWind Turbine Blade through Histogram Features Using Vibration Signals: A Data-Mining Approach

Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources.The wind turbine is an essential system used to change kinetic energy into electrical energy.Wind turbine blades,in particular,require a competitive condition inspection approach as it is a significant component of the wind turbine system that costs around 20-25 percent of the total turbine cost.The main objective of this study is to differentiate between various blade faults which affect the wind turbine blade under operating conditions using a machine learning approach through histogram features.In this study,blade bend,hub-blade loose connection,blade erosion,pitch angle twist,and blade cracks were simulated on the blade.This problem is formulated as a machine learning problem which consists of three phases,namely feature extraction,feature selection and feature classification.Histogram features are extracted from vibration signals and feature selection was carried out using the J48 decision tree algorithm.Feature classification was performed using 15 tree classifiers.The results of the machine learning classifiers were compared with respect to their accuracy percentage and a better model is suggested for real-time monitoring of a wind turbine blade.