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Abstract Bolt looseness may occur on wind turbine (WT) blades exposed to operational and environmental variability conditions, which sometimes can cause catastrophic consequences. Therefore, it is necessary to monitor the loosening state of WT blade root bolts. In order to solve this problem, this paper proposes a method to monitor the looseness of blade root bolts using the sensors installed on the WT blade. An experimental platform was first built by installing acceleration and strain sensors for monitoring bolt looseness. Through the physical experiment of blade root bolts' looseness, the response data of blade sensors is then obtained under different bolt looseness numbers and degrees. Afterwards, the sensor signal of the blade root bolts is analyzed in time domain, frequency domain, and time‐frequency domain, and the sensitivity features of various signals are extracted. So the eigenvalue category as the input of the state discrimination model was determined. The LightGBM (light gradient boosting machine) classification algorithm was applied to identify different bolt looseness states for the multi‐domain features. The impact of different combinations of sensor categories and quantities as the data source on the identification results is discussed, and a reference for the selection of sensors is provided. The proposed method can discriminate four bolt states at an accuracy of around 99.8% using 5‐fold cross‐validation.

Bolt looseness may occur on wind turbine (WT) blades exposed to operational and environmental variability conditions, which sometimes can cause catastrophic consequences. Therefore, it is necessary to monitor the loosening state of WT blade root bolts. In order to solve this problem, this paper proposes a method to monitor the looseness of blade root bolts using the sensors installed on the WT blade. An experimental platform was first built by installing acceleration and strain sensors for monitoring bolt looseness. Through the physical experiment of blade root bolts' looseness, the response data of blade sensors is then obtained under different bolt looseness numbers and degrees. Afterwards, the sensor signal of the blade root bolts is analyzed in time domain, frequency domain, and time‐frequency domain, and the sensitivity features of various signals are extracted. So the eigenvalue category as the input of the state discrimination model was determined. The LightGBM (light gradient boosting machine) classification algorithm was applied to identify different bolt looseness states for the multi‐domain features. The impact of different combinations of sensor categories and quantities as the data source on the identification results is discussed, and a reference for the selection of sensors is provided. The proposed method can discriminate four bolt states at an accuracy of around 99.8% using 5‐fold cross‐validation. [ABSTRACT FROM AUTHOR]

Abstract Offshore wind power has been in the spotlight among renewable energy sources. The current trends of increased power ratings and longer blades come together with the aim to reduce energy costs by design optimisation. The standard approach to deal with uncertainties in wind‐turbine design has been by the use of characteristic values and safety factors. This paper focusses on modelling the effect of structural and aerodynamic uncertainties in blades. First, the uncertainties in laminate properties are characterised and propagated in a blade structural model by means of a Monte Carlo simulation. Wind tunnel measurement data are then used to define the variability in lift and drag coefficients for both clean and rough aerofoil behaviour, which is then used to extrapolate rough behaviours throughout the blade. A stochastic spatial interpolation parameter is used to define the evolution of the degradation level. The combined effect and the variance contribution of these two uncertainty sources in turbine loads is finally defined by aeroelastic turbine simulation. This research aims to provide a framework to deal with uncertainties in wind‐turbine blade design and understand their effects in turbine behaviour.

Offshore wind power has been in the spotlight among renewable energy sources. The current trends of increased power ratings and longer blades come together with the aim to reduce energy costs by design optimisation. The standard approach to deal with uncertainties in wind‐turbine design has been by the use of characteristic values and safety factors. This paper focusses on modelling the effect of structural and aerodynamic uncertainties in blades. First, the uncertainties in laminate properties are characterised and propagated in a blade structural model by means of a Monte Carlo simulation. Wind tunnel measurement data are then used to define the variability in lift and drag coefficients for both clean and rough aerofoil behaviour, which is then used to extrapolate rough behaviours throughout the blade. A stochastic spatial interpolation parameter is used to define the evolution of the degradation level. The combined effect and the variance contribution of these two uncertainty sources in turbine loads is finally defined by aeroelastic turbine simulation. This research aims to provide a framework to deal with uncertainties in wind‐turbine blade design and understand their effects in turbine behaviour. [ABSTRACT FROM AUTHOR]

Wind turbine fatigue estimation is based on time‐consuming Monte Carlo simulations for various wind conditions, followed by cycle‐counting procedures and the application of engineering damage models. The outputs of the fatigue simulations are large in volume and of high dimensionality, as they typically consist of estimates on finite‐element computational meshes. The strain and stress tensor time series, which are the primary quantities of interest when considering the problem of fatigue estimation, are dictated by complex vibration characteristics due to the coupled effect of aerodynamics, structural dynamics, geometrically non‐linear mechanics, and control. A Variational Auto‐Encoder (VAE) is trained in order to model the probability distribution of the accumulated fatigue on the root cross‐section of a simulated wind turbine blade. The VAE is conditioned on historical data that correspond to coarse wind‐field measurement statistics, such as mean hub‐height wind speed, standard deviation of hub‐height wind speed and shear exponent. In the absence of direct measurements of structural loads, the proposed technique finds applications in making long‐term probabilistic deterioration predictions from historical Supervisory, Control, and Data Acquisition (SCADA) data, while capturing the inherent aleatoric uncertainty due to the incomplete information on strain time series of the wind turbine structure, when only SCADA data statistics are available. [ABSTRACT FROM AUTHOR]

A generalized computational methodology for reduced order acoustic‐structural coupled modeling of the aeroacoustics of a wind turbine blade is presented. This methodology is used to investigate the acoustic pressure distribution in and around airfoils to guide the development of a passive damage detection approach for structural health monitoring of wind turbine blades for the first time. The output of a k − ε turbulence model computational fluid dynamics simulation is used to calculate simple acoustic sources on the basis of model tuning with published experimental data. The methodology is then applied to a computational case study of a 0.3048‐m chord NACA 0012 airfoil with two internal cavities, each with a microphone placed along the shear web. Five damage locations and four damage sizes are studied and compared with the healthy baseline case for three strategically selected acoustic frequencies: 1, 5, and 10 kHz. In 22 of the 36 cases in which the front cavity is damaged, the front cavity microphone measures an increase in sound pressure level (SPL) above 3 dB, while rear cavity damage only results in six out of 24 cases with a 3‐dB increase in the rear cavity. The 1‐ and 5‐kHz cases show a more consistent increase in SPL than the 10‐kHz case, illustrating the spectral dependency of the model. The case study shows how passive acoustic detection could be used to identify blade damage, while providing a template for application of the methodology to investigate the feasibility of passive detection for any specific turbine blade. [ABSTRACT FROM AUTHOR]

Wind turbine blades are subject to lightning strikes, which may result in severe damage of the blade materials. The withstanding performance of different blade materials needs to be classified in order to maximize their operational safety. Lightning impulse voltages were applied to model blades with different core materials (polyvinyl chloride [PVC], polyethylene terephthalate [PET], and balsa wood) to characterize the breakdown points (electrically vulnerable areas) on the blades. It has been found that the areas subjected to puncturing are located in the back part (toward the trailing edge) of the sandwich structure, especially at locations close to the main beam. Model blades made of balsa wood are more susceptible to puncturing breakdown than PVC and PET. High impulse currents were imposed at the most probably stricken spots in the impulse voltage tests to compare the severity of damage for PVC, PET, and balsa wood in an attempt to understand the thermal effect of lightning discharge following the final jump. Results show that balsa wood is most resistive to while PVC suffers most damage due to the thermal impact of lightning. Molecular simulation of the chemical degradation process and thermal gas production dynamics was performed at atomic level to explain the damage mechanisms of the three core materials. The performance data of the blade core materials against lightning strike obtained in the present work provide strong guidance on the optimal design of wind turbine blade structure and selection of blade core material. [ABSTRACT FROM AUTHOR]

In this paper, the electric fields in the wind turbine blades due to the lightning stepped leader are studied, and the dielectric breakdown is assessed. The developed finite element analysis (FEA) includes the full length of the leader and enables one to incorporate various uniform and non-uniform charge density models. The lightning striking distance is calculated using the rolling sphere method. The electric field in a horizontal axis wind turbine with three blades representing Sandia 100 m All-glass Baseline Wind Turbine Blades (SNL 100-00) at three different lightning protection levels (LPL) is computed and compared to the dielectric breakdown strength of the blades. The dielectric breakdown strength of the blades is evaluated based on the experimental data. The results show that the tip region of the blade is the most vulnerable to the dielectric breakdown with the safety factor as low as 1.32 at LPL I. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Wind turbine blade failure can be catastrophic and lead to unexpected power interruptions. In this paper, a Structural Health Monitoring (SHM) algorithm is presented for wireless monitoring of wind turbine blades. The SHM algorithm utilizes accumulated strain energy data, such as would be acquired by piezoelectric materials. The SHM algorithm compares the accumulated strain energy at the same position on the three blades. This exploits the inherent triple redundancy of the blades and avoids the need for a structural model of the blade. The performance of the algorithm is evaluated using probabilistic metrics such as detection probability (True Positive) and false alarm rate (False Positive). The decision time is chosen to be sufficiently long that a particular damage level can be detected even in the presence of system sensor noise and wind variations. Finally, the proposed algorithm is evaluated with a case study of a utility-scale turbine. The noise level is based on measurements acquired from strain sensors mounted on the blades of a Clipper Liberty C96 turbine. Strain energy changes associated with damage from matrix cracking and delamination are simulated with a finite element model. The case study demonstrates that the proposed algorithm can detect damage with a high probability based on a decision time period of approximately 50-200 days. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents a novel framework for the structural design and analysis of wind turbine blades and establishes its accuracy. The framework is based on a beam model composed of two parts-a 2D finite element-based cross-section analysis tool and a 3D beam finite element model. The cross-section analysis tool is able to capture the effects stemming from material anisotropy and inhomogeneity for sections of arbitrary geometry. The proposed framework is very efficient and therefore ideally suited for integration within wind turbine aeroelastic design and analysis tools. A number of benchmark examples are presented comparing the results from the proposed beam model to 3D shell and solid finite element models. The examples considered include a square prismatic beam, an entire wind turbine rotor blade and a detailed wind turbine blade cross section. Phenomena at both the blade length scale-deformation and eigenfrequencies-and cross section scale-3D material strain and stress fields-are analyzed. Furthermore, the effect of the different assumptions regarding the boundary conditions is discussed in detail. The benchmark examples show excellent agreement suggesting that the proposed framework is a highly efficient alternative to 3D finite element models for structural analysis of wind turbine blades. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Recurrent non-destructive testing inspections are necessary to prevent damages in wind turbine rotor blades, but so far, there is no established method that detects defects in blades from greater distances - although this becomes increasingly important in the context of hardly accessible offshore wind parks. Thermography is a promising method for detecting subsurface defects, but various challenges arise when this method is applied on-site to turbine blades in operation. Disturbing influences from the environment easily lead to a misinterpretation of thermograms (i.e. thermographic images), such as thermal signatures caused by reflections, dirt and other superficial inhomogeneities. This study explores several problems and effects that arise, when (rotating) blades are monitored with thermography. It will then be demonstrated that a meaningful defect inspection in this scenario is essentially restricted to a procedure following three steps: Firstly, calculating the so-called difference thermograms of all blade pairs for eliminating disturbing reflections. Secondly, identifying potentially relevant signals, which are associated neither with structural features nor with dynamical effects, and the identification of these signals' allocations (through comparison of all difference thermograms with each other). And thirdly, comparing these signals with (processed) photos for excluding incorrect indications by surface effects. Unlike common thermographic analysis methods, which typically only include an aspect of this procedure, the composition presented in this contribution constitutes an advanced technique for minimizing disturbing influences in thermograms. The proposed thermographic technique enables the detection of potential subsurface defects within rotating rotor blades from greater distances - such as from the ground, air crafts or vessels. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Fatigue testing of a 48.3 m wind turbine blade needs to utilize the blade's oscillation range of 8.4 m along the flapwise direction for one million cycles. Control of such a remarkable oscillation range makes flapwise fatigue testing difficult and requires a large supply of energy. This study minimized the actuating force required for flapwise fatigue testing using an on-board-type resonance exciter with constant amplitude. Constraints related to the exciter's stroke and capacity and the maximum error between target loads and test loads were also considered. Based on a new algorithm suggested in this study, first, we found test setup candidates minimizing the maximum error under a given testing frequency and then found more candidates having slightly larger maximum errors as the exciter's location moved toward the blade's tip. Next, using damping ratio equations for the test blade, a required actuating force of the exciter at each test setup candidate was calculated. Considering the exciter's capacity, we found an optimum test setup that requires a minimum actuating force in the vicinity of the minimum of the maximum error between target loads and test loads. To conclude, the approach suggested in this study was able to conclusively achieve the required fatigue testing of the test blade, avoiding the adverse increase of fatigue testing time possible to happen due to a required actuating force larger than the exciter's capacity. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Modern wind turbine rotor blades are usually made from fibre-reinforced composite subcomponents. In the final assembly stage, these subcomponents are bonded together by several adhesive joints. One important adhesive joint is situated at the trailing edge, which refers to the downstream edge where the air-flow rejoins and leaves the blade. Maintenance inspections of wind turbine rotor blades show that among other forms of damage, local debonding of the shells along the trailing edge is a frequent failure type. The cause of trailing edge failure in wind turbine blades is complex, and detailed information is scarce. This paper is concerned with the fracture analysis of adhesive joints in general, with a particular focus on trailing edges. For that, the energy release rates in prescribed cracks present in the bond line of a generic trailing edge joint are investigated. In connection with this examination, the paper elucidates the influence of geometrical non-linearity in form of local buckling on both the increase of the energy release rate and the change of mode mixity. First, experimental results on adhesively bonded small-scale subcomponents are presented. Thereafter, a practical approach is presented, which links the experimental results conducted on a small scale to the numerical failure prediction of large-scale models. The proposed method is based on the virtual crack closure technique and defines the mode mixity at bimaterial interfaces unambiguously. The method is consequently applied to a wind turbine blade submodel in order to predict crack growth in the trailing edge. Thereby, the influence of different crack lengths on crack initiation and propagation is considered. The paper concludes with general thoughts on adhesively bonded trailing edge joints regarding the prevention of local debonding. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper utilized the inherent directional properties of composite materials to increase the critical buckling load of a 70 m carbon/glass hybrid wind turbine blade. The effect of changing the fiber orientations of the less stiff, off-axis glass fiber plies (referred to as stability plies in this paper) was studied via nonlinear finite element buckling simulations. The orientation of the stability plies was found to influence the onset of the Brazier effect, which further influenced blade stability and buckling failure location. Although both blade weight and laminate thickness remained constant, an increase in critical buckling load of 8% was achieved with a negligible change in bending stiffness. The more stable blade allowed for removal of material leading to a decrease in maximum laminate thickness and a drop in blade mass of 3.3%. Modifications to the ply stacking sequence and carbon fiber usage were also considered and were found to affect the buckling load but not necessarily the optimum fiber orientation of the stability plies. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT This study presents a real-time shape estimation technique based on measured strains at multiple points. For the measurement of multiple strain data, fiber Bragg grating (FBG) sensors are used because of their excellent strain accuracy and multiplexing capability with minimal mechanical loading. The displacement-strain relation of a blade structure is systematically formulated using a finite element model, where the locations and directions of the FBG sensors are taken into account. Because there could be unavoidable modeling uncertainties, the operational modal analysis is also introduced to construct a displacement-strain transformation matrix. In the laboratory, the developed technique is applied to a wind turbine blade in which the FBG sensors are embedded. The blade deformation is reconstructed using the proposed method when the blade is subjected to static and vibratory loadings. At the same time, a stereo pattern recognition system consisting of eight cameras directly captures the deformation of the blade to validate the estimated blade shapes. For various loading cases, the estimated results of the blade shape agree very well with the reference measurements. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT A geometrically exact beam model for simulating the structural dynamic response of the CX-100 wind turbine blade is presented. The underlying geometrically nonlinear theory is detailed, and its implementation into a finite-element code, NLBeam, developed as part of this research is outlined. The parameters used to represent the varying cross-sectional distributions of stiffness and mass are calculated consistent with the geometrically exact beam theory by using the variational asymptotic method, as developed by Hodges and Yu et al. through the commercially available code, (VABS) variational asymptotic beam sectional analysis. Code and calculation verification are documented through a systematic grid convergence study applied independently to both the cross-sectional, and static and dynamic beam simulations. An initial assessment of the model is made by comparing simulation results with experimental test data for three cases: quasistatic loading, linearized modal dynamic behavior and steady-state oscillating dynamic loads. Simulation results are shown to be in reasonable agreement with experimental data. Future improvements to the model, as well as additional experimental characterization that can benefit such modeling efforts, are outlined. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Wind turbine rotor blades are commonly manufactured from composite materials by a moulding process. Typically, the wind turbine blade is produced in two halves, which are eventually adhesively joined along their edges. Investigations of operating wind turbine blades show that debonding of the trailing edge joint is a common failure type, and information on specific reasons is scarce. This paper is concerned with the estimation of the strain energy release rates (SERRs) in trailing edges of wind turbine blades in order to gain insight into the driving failure mechanisms. A method based on the virtual crack closure technique (VCCT) is proposed, which can be used to identify critical areas in the adhesive joint of a trailing edge. The paper gives an overview of methods applicable for fracture cases comprising non-parallel crack faces in the realm of linear fracture mechanics. Furthermore, the VCCT is discussed in detail and validated against numerical analyses in 2D and 3D. Finally, the SERR of a typical blade section subjected to various loading conditions is investigated and assessed in order to identify potential design drivers for trailing edge details. Analysis of the blade section model suggests that mode III action is governing and accordingly that flapwise shear and torsion are the most important load cases.Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT As wind turbines continue to grow in size, it becomes increasingly important to ensure that they are as structurally efficient as possible to ensure that wind energy can be a cost-effective source of power generation. A way to achieve this is through weight reductions in the blades of the wind turbine. In this study, topology optimization is used to find alternative structural configurations for a 45 m blade from a 3 MW wind turbine. The result of the topology optimization is a layout that varies along the blade length, transitioning from a structure with trailing edge reinforcement to one with offset spar caps. Sizing optimization was then performed on a section with the trailing edge reinforcement and was shown to offer potential weight savings of 13.8% when compared with a more conventional design. These findings indicate that the conventional structural layout of a wind turbine blade is sub-optimal under the static load conditions that were applied, suggesting an opportunity to reduce blade weight and cost. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT A modal re-analysis approach is proposed for refinement designs of rotary wind turbine blades on the basis of matrix perturbation methods. The approach entails effects of stress stiffening, spin softening, uncertainty of material properties and structural modifications of blades. Three perturbation methods are used to conduct the re-analysis approach, including the standard perturbation method and two improvements proposed by H. C. Hu and S. H. Chen, respectively. Numerical results of a typical wind turbine blade indicate that the two improved methods deliver better accuracy than the standard perturbation method in terms of eigenpairs. In application to blade designs, Chen's method is suitable for a multi-step modal re-analysis with explicit small parameters and cultivates the first-order and second-order perturbations of eigenpairs as well. In contrast, Hu's method is a better choice for a single-step modal re-analysis without determining any small parameter explicitly and directly offers approximate eigenpairs instead of somehow tedious perturbation processes. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]