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A signal-processing algorithm for the detailed determination of delamination in multilayer structures is proposed in this work. The algorithm is based on calculating the phase velocity of the Lamb wave A0 mode and estimating this velocity dispersion. Both simulation and experimental studies were conducted to validate the proposed technique. The delamination having a diameter of 81 mm on the segment of a wind turbine blade (WTB) was used for verification of the proposed technique. Four cases were used in the simulation study: defect-free, delamination between the first and second layers, delamination between the second and third layers, and defect (hole). The calculated phase velocity variation in the A0 mode was used to determine the location and edge coordinates of the delaminations and defects. It has been found that in order to estimate the depth at which the delamination is, it is appropriate to calculate the phase velocity dispersion curves. The difference in the reconstructed phase velocity dispersion curves between the layers simulated at different depths is estimated to be about 60 m/s. The phase velocity values were compared with the delamination of the second and third layers and a hole drilled at the corresponding depth. The obtained simulation results confirmed that the drilled hole can be used as a defect corresponding to delamination. The WTB sample with a drilled hole of 81 mm was used in the experimental study. Using the proposed algorithm, detailed defect parameters were obtained. The results obtained using simulated and experimental signals indicated that the proposed new algorithm is suitable for the determination of delamination parameters in a multilayer structure. [ABSTRACT FROM AUTHOR]

Passive flow control around airfoils, wind turbines, and submarines to enhance their aerodynamic properties is the subject of interest in several studies. Previous research provides different solutions, from basic changes in surface roughness and simple geometries to complex shapes and mechanical solutions. This article presents experimental research using the Particle Image Velocimetry (PIV) method on a NACA 0012 airfoil at a Reynolds number of 66,400. Initially, the airfoil was tested for three different angles of attack: 13°, 15°, 17°, and 19°. These tests revealed that angles of attack above 15° significantly increase boundary layer detachment, as shown in the normalized streamwise velocity fields U x . In the second stage of the research, a different-shaped microcylinder with a characteristic dimension (d/c) of 0.01 was added to the leading edge of the airfoil at a high angle of attack of 17°. Unlike traditional vortex generators placed at the rear of the airfoil, this configuration aimed to reduce boundary layer detachment. The experiment demonstrated that the microcylinder effectively reduced boundary layer detachment at this angle of attack. [ABSTRACT FROM AUTHOR]

This study compares the logistics of decommissioning wind turbine blades for energy recovery in a cement kiln (proposed scenario) to industrial landfill site disposal and coke fuel in a cement kiln combined (base scenario) to check the financial cost of the operation in each scenario. The wind farm coordinates, wind turbine blade mass, and logistics costs of the 760 wind farms in Northeast Brazil were used to determine the location of a material processing center (MPC) for wind turbine blade waste. The findings showed that the cost of the proposed scenario was higher than that of the base scenario when a single MPC was considered to serve the Northeast region. However, the proposed scenario was preferable when installing decentralized MPCs to serve the Northeast region. The installation of four additional decentralized MPCs shows that energy recovery is a more favorable technological route in the economic performance for disposing of 96% of the wind turbine blades in operation in the Northeast region, which represents 210,188 tonnes. Therefore, the gradual implementation of MPCs should consider a wind turbine blade decommissioning plan to support the energy recovery potential. [ABSTRACT FROM AUTHOR]

The lifecycle of wind turbine blades is around 20–25 years. This makes studies on the reuse of dismantled blades an urgent need for our generation; however, their recycling is very difficult due to the specific makeup of their composite material. In this study, the authors determined a concept for the reuse of turbine blade sections filled with concrete for geotechnical structures, retaining the walls, piles, or parts of their foundations. Working out detailed structural solutions to the above problem should be preceded by the identification of material parameters. In particular, getting to know the interface stress-strain characteristics is crucial. Therefore, this research focuses on the cooperation between recycled FRP composites and concrete in load-carrying, including experiments and numerical analyses. Regarding the two types of destructive stress, which may occur at the interface under both compression and bending, two types of tests were executed: the 'push-out test', modelling the interface's answer to shear stress, and the 'pull-off test', demonstrating the interface's reaction to normal stress. Additionally, the strength parameters of the materials used were tested. The numerical model for the push-out process was calibrated on the basis of the tests, and this way the shear bond strength and the coefficient of friction between the concrete and the recycled FRP laminate were assessed. [ABSTRACT FROM AUTHOR]

The wind turbine blades are exposed, during functioning, to the abrasive wear generated by the impact with air-borne sand particles. In this work, samples of a commercial wind turbine blade, made of a multi-layered composite material, are subjected to abrasive wear tests, using an air streamed wearing particles test rig. Following the analysis of the tests' results was found that the only protection against failure of the blade by abrasive damage is the surface layer. After its' penetration, the layers below are quickly destroyed, leading to the blade destruction. The investigation of the main abrasive wear influencing factors—particles' speed and acting time, showed that the particles' speed is the most important. To prove that an artificial neural network-based model was used. Also, a method for improvement of the blade resistance to abrasive wear is proposed, consisting of applying on the blade's surface of a polymeric foil. This offers supplementary protection of the surface layer, delaying its degradation. The tests performed on the protected samples prove the validity of the proposed method. Overall, the work showed the weakness of the blades' resistance in case of working in abrasive wear conditions and identified an improving method. [ABSTRACT FROM AUTHOR]

This paper aimed to understand the AE signal characteristics and damage mechanism of wind turbine blade main spar materials with different defects during the damage evolution process. According to the typical delamination and wrinkle defects in wind turbine blades, the GFRP composite with defects is artificially prefabricated. Through acoustic emission experiments, the mechanical properties and acoustic emission characteristic trends of wind turbine blade main spar composites with different defects under tensile loading conditions were analyzed, and the damage evolution mechanism of different defects was explained according to the microscopic results. The results show that the existence of artificial defects will not only affect the mechanical properties of composite materials but also affect the damage evolution process of the materials. The size and location of delamination defects and the different aspect ratio of the wrinkle defects have a certain influence on the damage mechanism of the material. K-means cluster analysis of AE parameters identified the damage models of GFRP composites. The types of damage modes of delamination defects and wrinkle defects are the same, and the range of characteristic frequency is roughly the same. This study has important reference significance for structural damage monitoring and damage evolution research of wind turbine blade composites. [ABSTRACT FROM AUTHOR]

Wind turbine blades are critical components of wind energy systems, and their structural health is essential for reliable operation and maintenance. Several studies have used time-domain and frequency-domain features alongside machine learning techniques to predict faults in wind turbine blades, such as erosion and cracks. However, a key gap remains in integrating these methods into a unified framework for fault prediction, which could offer a more comprehensive solution for diagnosing faults. This paper presents an approach to classify faults in wind turbine blades by leveraging well-known signals and analysis with machine learning techniques. The methodology involves a detailed feature engineering process that extracts and analyzes features from the time and frequency domains. Open-source vibration data collected from an experimental setup (where a small wind turbine with an artificially eroded and cracked blade was tested) were utilized. The time- and frequency-domain features were extracted and analyzed using various machine learning algorithms. It was found that erosion and crack faults have unique time- and frequency-domain features. The crack fault introduces an amplitude modulation in the vibration time wave, which produces sidebands around the fundamental frequency in the frequency domain. However, erosion fault introduces asymmetricity and flatness to the vibration time wave, which produces harmonics in the frequency-domain plot. The results also highlighted that utilizing both time- and frequency-fault features enhances the performance of the machine learning algorithms. This study further illustrates that even though some machine learning algorithms provide similar high classification accuracy, they might differ in quantifying error Types I, II, and, III, which is extremely important for maintenance engineers, as it might lead to undetected fault events and false alarm events. [ABSTRACT FROM AUTHOR]

Copyright of Baghdad Science Journal is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wind energy is a renewable energy source with a significant impact on the date for harnessing it. Different types of wind turbines (WTs) are being built to generate affordable, dependable, and eco-friendly renewable wind energy. Over time, cracks are found to be developed in the blades of the WTs, which is considered the most common type of damage that ultimately causes the catastrophic failure of the structures. This study aims to develop a structural health monitoring (SHM) framework for localizing cracks of a WT blade using a convolutional neural network (CNN)–based deep learning algorithm. With that objective, the NACA (National Advisory Committee for Aeronautics) 63-412 profile (WT blade) of length 29 m was modelled in finite element analysis (FEA) ANSYS 2022 R2. A crack is introduced to the model by making a groove at different blade locations. The mode shape and natural frequencies are obtained and validated with those reported in the literature. Further, the blade is excited by an impact load applied at the tip of the blade, and acceleration time histories are collected. The acceleration time history data are converted to scalogram images and fed into the CNN algorithm for damage classification and localization. In this study, the concept of class activation maps is also utilized for visual representations of the input images' areas that significantly influence a class's classification score. The classified results show that using CNN can successfully localize the region of the cracks and motivate us to examine it on a laboratory-based model. [ABSTRACT FROM AUTHOR]

Numerical simulation technology is a crucial tool for reducing costs and increasing efficiency in the wind power industry. However, with the development of large-scale wind turbines, the computational cost of numerical simulation has gradually increased. This paper uses the geometric similarity, structural similarity criterion, Reynolds similarity and boundary layer theory to establish a scaled model of the geometric three-dimensional shape, composite material, and finite element mesh of large wind turbine blades. The study analyzes the aerodynamic, gravitational, and centrifugal load variations within the scaled model. The proportional relationship between the scaled model's operating parameters, the numerical simulation's environmental parameters, and the mechanical response parameters is established. These parameters are coordinated to ensure the similarity of the blade structure and the fluid dynamics. For a geometric scale factor of 0.316, the relative difference in maximum deflection is 4.52%, with a reduction in calculation time by 48.1%. On the premise of ensuring the calculation accuracy of the aerodynamic and structural response of the blade, the calculation efficiency is effectively improved. [ABSTRACT FROM AUTHOR]

Lightning is the severest threaten to safe operation of wind turbines. In this letter, the authors present the first altitude‐triggered lightning experiment involving an elevated 12 m‐long wind turbine blade placed on the ground. A total of 50 precursors with amplitude over 62.9 A were observed through measurements of channel‐base current, fast electric field, and optical data. The air gap with around 3–5 m has been bridged between the wire's lower extremity and the metal blade tip during ascending of the rocket and it is observed to be luminous by slow framing rate camera. The precursors are classified into three groups, namely bipolar pulses, unipolar pulses, and group pulses. Excluding the precursors preceding the initial stage and M‐components at the late‐time of the initial stage, five stages are classified. In the first stage, the current remains limited at a relatively small value, while the electric field exhibited a slow rising behavior with positive polarity. In the second stage, the current starts to increase, and the electric field rapidly intensifies due to the accumulating charge, and the wire is assumed to experience an explosion. In the third stage, the reconnection process occurs. The current is characterized by a peak value of 1.45 kA with 10%–90% risetime of 10.4 μs. The electric fields suffer from notable decrease and are characterized by a microsecond‐scale V‐shape pulse. The current cutoff is quite short that almost not found. In the fourth step, the current is characterized by superimposed pulses. The final stage is the channel darkening. Plain Language Summary: Observation results are reported in detail about the altitude‐triggered lightning experiment involving an elevated 12 m‐long wind turbine blade placed on the ground. There are fruitful precursors prior to the beginning of the initial stage. The precursors demonstrate that the air gap with around 3–5 m has been bridged between the wire and the metal blade tip. The precursors are grouped into three groups, namely bipolar pulses, unipolar pulses, and group pulses. The initial stage is classified into five periods. The triggering wire is believed to be vapourized during the second stage. The so‐called initial current variation (ICV), also called reconnection process, occurs at the third stage. The superimposed pulses are found immediately after the reconnection process in the fourth stage. The late‐time of the initial stage is also characterized by superimposed pulses associated with M‐components. This work is potentially helpful to understand the physical process lightning strikes a wind turbine, and design lightning protection strategies for wind turbines. Key Points: First altitude‐triggered lightning experiment associated with an elevated 12 m‐long wind turbine blade has been conducted through simultaneous measurements of current, electric fields and optical dataThe 50 precursors over 62.9 A proceeding the initial stage are classified into three groups: (a) bipolar pulses with the notably initial positive peak and followed by the negative excursion; (b) unipolar pulses with the notably initial positive peak but with quite flat late‐time response; and (c) group pulsesFive stages associated with channel reestablishment are classified according to the measured current and electric field, in which the current cutoff is quite short that almost not found [ABSTRACT FROM AUTHOR]

We designed 60% thick airfoil to improve the aerodynamic performance in the root region of wind turbine rotor blades, taking into account current constraints. After an extensive literature review and patent research, a design methodology (including the considerations of simple manufacturing) was set up, and extensive 2D- and 3D-CFD investigations with four codes (Xfoil, MSES, ANSYS fluent, and DLR-tau) were performed, including implementation inside a generic 10 MW test-blade (CIG10MW). Comparison with results from Blade Element Momentum (BEM) methods and the estimation of 3D effects due to the rotating blade were undertaken. One specific shape (with a pronounced flat-back) was selected and tested in the Deutsche WindGuard aeroacoustic Wind Tunnel (DWAA), in Bremerhaven, Germany. A total of 34 polars were measured, included two trailing edge shapes and aerodynamic devices such as vortex generators, gurney flaps, zig-zag tape, and a splitter plate. Considerable changes in lift and drag characteristics were observed due to the use of aerodynamic add-ons. With the studies presented here, we believe we have closed an important technological gap. [ABSTRACT FROM AUTHOR]

Wind energy, as a renewable energy source, is becoming increasingly important. The maintenance and damage detection of wind turbine blades are particularly crucial. For this purpose, the study aims to optimize the You Only Look Once (YOLO) processing algorithm for drone images to improve the detection efficiency. Firstly, the damage images captured by drones are preprocessed and optimized, including deblurring, noise reduction, and image enhancement. Subsequently, the YOLOv5 model is improved in terms of structure and regression function, and a novel damage detection model is proposed. The research results indicated that the minimum loss function value of the improved model was 2.75, the average accuracy was 95 %, and the highest intersection over union was 91 %. After simulation testing, the detection effect of this model on abrasion, crackle, edge cracking, and coating peeling images was significantly better than other models in the same series. Its average time was as short as 2.43 s, reaching a maximum frame rate of 35.46. From this, the combination of drone image technology and improved image processing algorithm has a positive impact on improving the operational efficiency and safety of wind turbine blades. Compared with the traditional methods, the proposed model has significant advantages in terms of accuracy and real-time performance of damage detection, providing a new technical means for efficient maintenance of wind turbines. Meanwhile, the method shows high robustness and reliability in different types of damage detection, demonstrating the extensive potential in practical applications.

We designed 60% thick airfoil to improve the aerodynamic performance in the root region of wind turbine rotor blades, taking into account current constraints. After an extensive literature review and patent research, a design methodology (including the considerations of simple manufacturing) was set up, and extensive 2D- and 3D-CFD investigations with four codes (Xfoil, MSES, ANSYS fluent, and DLR-tau) were performed, including implementation inside a generic 10 MW test-blade (CIG10MW). Comparison with results from Blade Element Momentum (BEM) methods and the estimation of 3D effects due to the rotating blade were undertaken. One specific shape (with a pronounced flat-back) was selected and tested in the Deutsche WindGuard aeroacoustic Wind Tunnel (DWAA), in Bremerhaven, Germany. A total of 34 polars were measured, included two trailing edge shapes and aerodynamic devices such as vortex generators, gurney flaps, zig-zag tape, and a splitter plate. Considerable changes in lift and drag characteristics were observed due to the use of aerodynamic add-ons. With the studies presented here, we believe we have closed an important technological gap.

In order to study the structural performance of the new bend-twist coupling blade, NREL 5 MW blade was taken as the prototype, and the geometric model of the blade was established by using NX Open Grip parameterization language. The composite lamination design was carried out in accordance with the real processing technology, and the aerodynamic force of the blade was obtained by the computational fluid dynamics (CFD) method. The bend-twist coupling characteristics, harmonic response and strength of conventional and bending-torsional coupling blades were analyzed respectively. The results show that the blade tip displacement increases with the increase of the web deflection. For the same angle, the blade tip displacement of γ > 0 blades was smaller than that γ < 0 blades. The bend-twist coupling effect is the most obvious when γ = 10° and 15°. Compared with the conventional blade, the second-order displacement responses of bend-twist coupling blades are significantly reduced. The γ = 15° blade can reduce the stress on the surface and has a good load reduction performance.

Graphene platelets (GPLs) are gaining popularity across various sectors for enhancing the strength and reducing the weight of structures, thanks to their outstanding mechanical characteristics and low manufacturing cost. Among many engineering structures, wind turbine blades are a prime candidate for the integration of such advanced nanofillers, offering potential improvements in the efficiency of energy generation and reductions in the construction costs of support structures. This study aims to explore the potential of GPLs for use in wind turbine blades by evaluating their impact on material costs as well as mechanical performance. A series of finite element analyses (FEAs) were conducted to examine the variations of mechanical performances—specifically, free vibration, bending, torsional deformation, and weight reductions relative to conventional fiberglass-based blades. Details of computational modeling techniques are presented in this paper. Based on the outcomes of these analyses, the mechanical performances of GPL-reinforced wind turbine blades are reviewed along with a cost–benefit analysis, exemplified through a 5MW-class wind turbine blade. The findings affirm the practicality and benefits of employing GPLs in the design and fabrication of wind turbine blades. [ABSTRACT FROM AUTHOR]

In order to solve the end-effector force control response speed hysteresis and mechanical vibration problems caused by parameter perturbations and other disturbances during the processing of wind turbine blades by polishing robots, this paper proposes a robot pneumatic end-effector polishing force control strategy based on adaptive sliding mode backstepping algorithm. Based on the establishment of the mathematical model of the end-effector pneumatic system, a smooth and continuous sliding mode control law is adopted to solve the design conflict between sliding mode control theory and backstepping method, and to suppress output chattering in sliding mode control. By utilizing the insensitivity of the sliding mode control to the system model, the influence of matching disturbances on the system is eliminated. The non-matching disturbances of the known model are accurately compensated by backstepping control, and parameter uncertainty is effectively handled by adaptive control. Simulation and experimental results show that this method can effectively solve the uncertainty of system parameters and has good disturbance suppression ability, significantly improving the surface quality of wind turbine blades. [ABSTRACT FROM AUTHOR]

The wind energy sector is experiencing rapid growth, marked by the expansion of wind farms and the development of large-scale turbines. However, conventional manual methods for wind turbine operations and maintenance are struggling to keep pace with this development, encountering challenges related to quality, efficiency, and safety. In response, unmanned aerial vehicles (UAVs) have emerged as a promising technology offering capabilities to effectively and economically perform these tasks. This paper provides a review of state-of-the-art research and applications of UAVs in wind turbine blade damage detection, operations, and maintenance. It encompasses various topics, such as optical and thermal UAV image-based inspections, integration with robots or embedded systems for damage detection, and the design of autonomous UAV flight planning. By synthesizing existing knowledge and identifying key areas for future research, this review aims to contribute insights for advancing the digitalization and intelligence of wind energy operations. [ABSTRACT FROM AUTHOR]

With the trend towards larger and lighter designs of wind turbines, blades are progressively being developed to have longer and more flexible configurations. Under standstill conditions, the separated flow induced by a wide range of incident flow angles can cause complex aerodynamic elastic phenomena on blades. However, classical momentum blade element theory methods show limited applicability at high angles of attack, leading to significant inaccuracies in wind turbine performance prediction. In this paper, the geometrically accurate beam theory and high-fidelity CFD method are combined to establish a bidirectional fluid–structure coupling model, which can be used for the prediction of the aeroelastic response of wind turbine blades and the analysis of fluid–structure coupling. Aeroelastic calculations are carried out for a single blade under different working conditions to analyze the influence of turbulence, gravity and other parameters on the aeroelastic response of the blade. The results show that the dominant frequency of the vibration deformation response in the edgewise direction is always the same as the first-order edgewise frequency of the blade when the incoming flow condition is changed. The loading of gravity will make the aeroelastic destabilization of the blade more significant, which indicates that the influence of gravity should be taken into account in the design of the aeroelasticity of the wind turbine. Increasing the turbulence intensity will change the dominant frequency of the vibration response in the edgewise direction, and at the same time, it will be beneficial to the stabilization of the aeroelasticity response. [ABSTRACT FROM AUTHOR]

A study was conducted on the changes in mechanical properties and fatigue failure characteristics due to voids, one of the fabrication defects in composite materials. This study was primarily based on glass fiber fabrics applied to wind turbine blades and their material properties were predicted through micro and meso modeling of composite materials by simulating random defects including voids. As the wind turbine blades become larger, various defects develop. The fundamental changes in the materials' properties due to voids were predicted through homogenization methods and Representative Volume Element (RVE), and the failure properties were obtained through progressive failure analysis by applying virtual coupons according to ASTM D3090 and ASTM D6641. The progressive failure was identified using the Matzenmiller–Lubliner–Taylor (MLT) failure condition, and the fatigue failure characteristics were assessed through the Tsai–Hill 3D load. [ABSTRACT FROM AUTHOR]

The leading-edge erosion of a wind turbine blade was tested using a whirling arm rain erosion tester, whose rotation rate is considerably higher than that of a full-scale wind turbine owing to the scale effect. In this study, we assessed the impact pressure of droplets on a wet surface of wind turbine blades using numerical simulation of liquid droplet impact by solving the Navier–Stokes equations combined with the volume-of-fluid method. This was conducted in combination with an estimation of liquid film thickness on the rotating blade using an approximate solution of Navier–Stokes equations considering the centrifugal and Coriolis forces. Our study revealed that the impact pressure on the rain erosion tester exceeded that on the wind turbine blade, attributed to the thinner liquid film on the rain erosion tester than on the wind turbine blade caused by the influence of centrifugal and Coriolis forces. This indicates the importance of correcting the influence of liquid-film thickness in estimating the impact velocity of droplets on the wind turbine blade. Furthermore, we demonstrated the correction procedure when estimating the impact velocity of droplets on the wind turbine blade. [ABSTRACT FROM AUTHOR]

Durable elastomeric deicing coatings were developed for the anti-icing and deicing of wind turbine blades in this study. Our developed deicing coatings demonstrated extremely low ice adhesion strength (~15 kPa). Silica was added to enhance the icephobic surfaces' durability. The life of the deicing coating with silica was extended by 1.2 times. After 168 h of xenon lamp irradiation, there were no significant changes in the chemical composition of the coatings. Due to the increasing roughness and the decreasing tensile modulus, the contact angle of the aged coatings decreased by 14°. Further outdoor research was carried out on a wind farm for two months to investigate the influence of natural insolation and wind erosion on the elastic deicing coatings. The aged coating still maintained a high hydrophobicity and low ice adhesion strength. The contact angle stabilized at 107°, and the ice adhesion strength was 75% lower than that of the uncoated wind turbine blade. The elastomeric deicing coatings had three advantages: a lagging freezing time, low ice accumulation, and a short icing/deicing cycle. The results of field experiments on the naturally aged coatings showed that the freezing time of the coated blade was delayed by 20 min, and the ice on the coated blade was 29% thinner than that on the uncoated blade. [ABSTRACT FROM AUTHOR]

The wind energy sector faces a persistent challenge in developing sustainable solutions for decommissioned Wind Turbine Blades (WTB). This study utilises Lifecycle Assessment (LCA) to evaluate the gate-to-gate carbon footprint of high-profile disposal and recycling methods, aiming to determine optimal strategies for WTB waste treatment in the UK. While this article analyses the UK as a case study, the findings are applicable to, and intended to inform, recycling strategies for WTB waste globally. Long-term sustainability depends heavily on factors like evolving energy grids and changing WTB waste compositions and these must be considered for robust analysis and development strategy recommendations. In the short to medium term, mechanical recycling of mixed WTB waste is sufficient to minimise Global Warming Potential (GWP) due to the scarcity of carbon fibre in WTB waste streams. Beyond 2040, carbon fibre recycling becomes crucial to reduce GWP. The study emphasises the importance of matching WTB sub-structure material compositions with preferred waste treatment options for the lowest overall impact. Future development should focus on the extraction of carbon fibre reinforced polymer (CFRP) structures in WTB waste streams, commercialising large-scale CFRP structure recycling technologies, establishing supply chains, and validating market routes for secondary carbon fibre products. In parallel, scaling up low-impact options, like mechanical recycling, is vital to minimise WTB waste landfilling. Developing viable applications and cost-effective market routes for mechanical recyclates is necessary to displace virgin glass fibres, while optimising upstream recycling processes based on product requirements. [ABSTRACT FROM AUTHOR]

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.

In recent trends, a rising demand for renewable energy has driven wind turbines to larger proportions, where lighter blade designs are often adopted to reduce the costs associated with logistics and production. This causes modern utility-scale wind turbine blades to be inherently more flexible, and their amplified aeroelastic sensitivity results in complex multi-physics reactions to variant atmospheric conditions, including dynamic patterns of aerodynamic loading at the rotor and vortex structure evolutions within the wake. In this paper, we analyze the influence of inflow variance for wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs' Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex wake interactions for a range of flexible NRT blade variations, operating in differing conditions of variant atmospheric flow. CODEF solutions of turbine operation in Steady-In-The-Average (SITA) wind conditions are compared to SITA wind conditions featuring a controlled gust-like pulse overimposed, to isolate the effects of typical wind fluctuations. Finally, simulations of realistic time-varying wind conditions from SWiFT meteorological tower measurements are compared to the solutions of SITA wind conditions. These increasingly complex atmospheric inflow variations are tested to show the differing effects evoked by various patterns of spatiotemporal atmospheric flow fluctuations. An analysis is presented for solutions of wind turbine aeroelastic response and vortex wake evolution, to elucidate the consequences of variant inflow, which pertain to wind turbine dynamics at an individual and farm-collective scale. The comparisons of simulated farm flow for SITA and measured fluctuating wind conditions show that certain regions of the wake contain up to a 12% difference in normalized axial velocity, due to the introduction of wind fluctuations. The findings of this study prove valuable for practical applications in wind farm control and optimization strategies, with particular significance for modern utility-scale wind power plants operating in variant atmospheric conditions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mechanical Strength / Jixie Qiangdu is the property of Zhengzhou Research Institute of Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Offshore wind turbines operating in frigid and humid climates may encounter icing on the blade surface. This phenomenon adversely impacts the aerodynamic efficiency of the turbine, consequently diminishing power generation efficacy. Investigating the distribution characteristics of icing on the blade surface is imperative. Hence, this study undertook icing wind tunnel tests on segments of DU25 airfoil, a prevalent type for offshore wind turbines, to examine such characteristics as different chord lengths and angles of attack. The results show a simultaneous increase in the blade icing area and growth rate of the net icing area with augmenting the chord length and angles of attack. The total icing area rate decreases by a factor of two when the chord length is doubled. The relative positioning of icing and the average icing thickness remain consistent across the airfoil blades with varying chord lengths. Comparing the icing shapes on blades of varying scales shows a similarity ranging from 84.06% to 88.72%. The results of this study provide insight into the icing characteristics of offshore wind turbines. [ABSTRACT FROM AUTHOR]

A wireless monitoring system based on piezoelectric energy harvesting (PEH) is presented to provide fatigue data of wind turbine blades in operation. The system comprises three subsystems, each respectively providing the following functions: (i) the conversion of mechanical to electric energy by exploiting the bistable vibration of a composite beam with piezoelectric patches in post-buckling, (ii) harvesting the converted energy by means of a modified, commercial, off-the-shelf (COTS) circuit to feed a LiPo battery and (iii) the battery-powered acquisition and wireless transmission of sensory signals to the cloud to be elaborated upon by the end-user. The system was verified with ground tests under representative operation conditions, which demonstrated the fulfillment of the design requirements. The measurements indicated that the system provided 23% of the required power for fully autonomous operation when subjected to white noise base excitation of 1 g acceleration in the range of 1–20 Hz. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Drainage & Irrigation Machinery Engineering / Paiguan Jixie Gongcheng Xuebao is the property of Editorial Department of Drainage & Irrigation Machinery Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

As wind turbine blade length increases, reconciling lightweight design with strength necessitates continuous advancements in process technology. The impact of three different process technologies–vacuum-assisted resin transfer moulding (VARTM), prepreg, and pultrusion–on the properties of wind turbine blade composite spar caps was investigated using scanning electron microscopy, dynamic mechanical analysis, differential scanning calorimetry, thermogravimetric analysis, and static and fatigue testing. The results demonstrated that the fibre weight content and 0° tensile modulus of the VARTM and pultrusion composites increased as compared to those of the prepreg samples. Subsequently, the properties of a 94-m blade were analysed using the Ansys Composite PrepPost (ACP) and static structure modules in Ansys simulations, and the weights of the spar cap were compared with test data of materials under different process technologies. The results showed that the masses of the spar cap of a 94-m blade in the pultrusion, VARTM, and prepreg processes were 7965, 9170, and 9942 kg, respectively. The quantitative influence rules on the weight of the wind turbine blade spar cap prepared through different process technologies were formulated. The findings of this study are promising and are expected to aid the development of wind turbine blade process technologies. [ABSTRACT FROM AUTHOR]

This study uses an icing model, combining heat transfer with fluid flow and considering the roughness effect, to investigate the influence of liquid water content (LWC) and droplet median volume diameter (MVD) on the ice distribution and anti-icing heat estimation of a wind turbine blade airfoil through the numerical approach. The findings indicate that the simulated ice distribution can have excellent agreement with experimental data. Owing to variations of droplet collection efficiency and heat flux, the increase in LWC and MVD will amplify the fluctuations in ice accretion distribution, which will be prone to ice horns. Owing to high LWC increasing water film flow range, the jumping point of anti-icing heat flux is closer to the trailing edge. Owing to large MVD increasing droplet collection efficiency, the quantity of ice accumulation through solidification ascends to demand higher anti-icing heat flux. The peak anti-icing heat flux is more evidently influenced by LWC than that by MVD, due to the variations in heat flux, induced by water film evaporation and solidification. The findings offer valuable insights into the flow and heat transfer physics for wind turbine anti/de-icing design.

Wind energy plays a significant role as a sustainable and renewable energy source. This paper deals with ANSYS to set up computational fluid dynamics (CFD) and structural analysis and then apply for use them to wind turbine (WT) blades. The present paper selected General Electric's (GE) horizontal axis wind turbine (HAWT) for 1.5 MW of renewable energy and focused on using the ANSYS package to calculate the tip velocity, pressure, power coefficient, deflection, flap-wise, and edge-wise deformation values. The simulation analysis considered three independent variables: wind speeds of (7, 10, 12, 15, and 20 m/s), blade position of (90, 180, 270, and 360⁰), and Five composite materials of (Carbon-Epoxy, E-Glass, S-Glass, Kevlar, and Technora). The shear stress transport (SST) turbulence was employed. The results show a good agreement between the tip velocity, power coefficient values, and the numerical simulation. The Epoxy E-Glass material exhibits the maximum blade deflection of 1.6363 m, while the Kevlar material has the minimum deflection of 0.41277 m. At a 90o angle, the Epoxy E-Glass material shows a maximum blade deflection of 1.4918 m, whereas the Kevlar material has a minimum deflection of 0.37381 m at a 270o angle. These findings highlight the importance of considering wind conditions and their effects on blade performance and structural integrity in wind turbine design and operation.

Wind power generation system is one of the most important components of new energy power system. However, lightning disasters seriously threaten the safe and stable operation of wind turbine blades. In order to protect wind turbine blades from lightning, different types of lightning receptors are developed. In this paper, lightning discharge experiments of wind turbine blades are carried out to study the lightning protection effects of tip, side, and metal mesh receptors. The lightning discharge processes of wind turbine blades with different receptors are observed and the lightning protection failure rates are recorded. Electric field simulations have been done to analyze the lightning discharge mechanism and discuss the lightning protection optimization methods of wind turbine blades, which can give references for the lightning protection design of wind power generation system.

INTRODUCTION: As a renewable and clean use of energy, wind power generation has a very important role in the new energy generation industry. For the many parts of various wind turbines, the safety and reliability of wind turbine blades are very important. OBJECTIVES: The energy spectrum simulation algorithm included in the wavelet analysis method is used to simulate and analyzewind turbine blade damage, to verify the correctness and validity of wind turbine blade damage analysis. METHODS: Matlab simulation is used to introduce the experiments related to the static and dynamic detection of fiber grating sensors, analyze the signal characteristics of the wind turbine blade when it is damaged by the impact, and provide a basis for the analysis of the external damage of large wind turbine blade. RESULTS: The main results obtained in this paper are the following. By analyzing the decomposition of wavelet packets, the gradient change of wavelet impact energy spectrum before and after the wavelet damage was obtained and compared with the histogram, and the impact energy spectrum of each three-dimensional wavelet energy packet in the image was compared and analyzed, which can well realize the recognition of wavelet damage gradient for solid composite materials. CONCLUSION: With the help of Matlab simulation to collect the impact response signal, using the wavelet packet energy spectrum method to analyze the signal, can derive the characteristics of wind turbine blade damage.

Although epoxy resin has been extensively used in the field of wind turbine blades, polyurethane has attracted much attention in recent years, due to its potential value of better fatigue resistance, lower processing viscosity and higher strength than epoxy resin blades. Herein, we construct a dense cross-linking structure in polyurethane (PU) based on different amounts of hydroxypropyl methacrylate (HPMA) with low processing viscosity and excellent mechanical properties. By increasing the content of HPMA, the thermal stability of PU is enhanced, but the micro-morphology does not change significantly. When the content of HPMA is 50 g (in 200 g copolymer), the PU sample PH-50 exhibits a viscosity of 70 MPa·s and a gelation time of 120 min at 25 °C, which is sufficient to complete processes like pouring and filling. By post-curing the PH-50 at 80 °C for 2 h, the heat distortion temperature can reach 72 °C, indicating the increase of temperature resistance. The PU copolymers also have excellent mechanical and dynamic thermo-mechanical properties due to the cross-linking structure between PU chains and poly-HPMA chains. Additionally, the PU copolymer has excellent compatibility with various glass fiber fabrics (GFF), showing a good match in the vacuum infusion experiment and great properties in the mechanical test. By compounding PH-50 with GFF, the composite with high strength is easily prepared for a wind turbine blade in various positions. The tensile strengths of the composites are all over 1000 MPa in the 0° direction. Such composites are promising for the future development of wind turbine blades that meet the stringent requirements for outstanding processing and mechanical properties. [ABSTRACT FROM AUTHOR]

The study of damage mechanisms for wind turbine blades is important. Generally, modal localization tends to accelerate structural damage. This is a new approach to studying these damage mechanisms for wind turbine blades through modal localization theory. Therefore, this paper investigates whether modal localization phenomena exist in wind turbine blades, as well as the impact of different forms of detuning on modal localization. Based on perturbation theory, a mechanism for mode localization is described quantitatively using the degree of detuning, the degree of mode density, and the mode assurance criterion. A finite element model for wind turbine blades was established using ANSYS software (R15.0), and three detuning cases were simulated by changing the density, elastic modulus, and installation angles of the blades. Moreover, an improved mode localization factor is proposed to quantitatively evaluate the degree of mode localization in wind turbine blades. The numerical results indicate that the degree of modal localization increases with an increasing degree of detuning, but the increase in modal localization gradually slows. Finally, the detuning modal shape composition, which includes harmonic components, is analyzed. The results show that the closer the composition of the detuning modes is, the stronger the degree of mode localization. [ABSTRACT FROM AUTHOR]

To address challenges in the detection of wind turbine blade damage images, characterized by complex backgrounds and multiscale feature distribution, we propose a method based on an enhanced YOLOV8 model. Our approach focuses on three key aspects: First, we enhance the extraction of small target features by integrating the CBAM attention mechanism into the backbone network. Second, the feature fusion process is refined using the Weighted Bidirectional Feature Pyramid Network (BiFPN) to replace the path aggregation network (PANet). This modification prioritizes small target features within the deep features and facilitates the fusion of multiscale features. Lastly, we improve the loss function from CIoU to EIoU, enhancing sensitivity to small targets and the perturbation resistance of bounding boxes, thereby reducing the gap between computed predictions and real values. Experimental results demonstrate that compared with the YOLOV8 model, the CBAM-BiFPN-YOLOV8 model exhibits improvements of 1.6%, 1.0%, 1.4%, and 1.1% in precision rate, recall rate, mAP@0.5, and mAP@0.5:.95, respectively. This enhanced model achieves substantial performance improvements comprehensively, demonstrating the feasibility and effectiveness of our proposed enhancements at a lower computational cost. [ABSTRACT FROM AUTHOR]

Bushing-insert connections have emerged as efficient blade root connection designs. Bushing-insert connections with fibre-reinforced plastic (FRP) wedge-sticks enhance the strength and stability of the blade root, prevent stress concentration at the blade root, and improve the service life and reliability of the blade. However, studies on the failure mechanisms of the FRP wedge-sticks in bushing-insert connections are scarce. Hence, in this study, the influence of the FRP wedge-stick on the structural performance of the blade root was analysed by changing the slope of the FRP wedge-stick's inclined surface at a constant thickness. The finite element method, sample testing, and full-size blade testing method were employed, and structural verification was conducted using an 84.5 m blade. The results reveal that the contact area of the inclined surface can be increased by reducing the slope of the FRP wedge-stick. This increase in area reduces the stress transmitted to each node of the FRP wedge-stick and blade root, prevents delamination of the FRP wedge-stick and blade root, and enhances the reliability of the blade root connection. [ABSTRACT FROM AUTHOR]

Wind turbines in cold and humid regions face significant icing challenges. Heating is considered an efficient strategy to prevent ice accretion over the turbine's blade surface. An ice protection system is required to minimize freezing of the runback water at the back of the blade and the melting state of the ice on the blade; the law of re-freezing of the runback water is necessary for the design of wind turbine de-icing systems. In this paper, a wind tunnel test was conducted to investigate the de-icing process of a static heated blade under various rime icing conditions. Ice shapes of different thicknesses were obtained by spraying water at 5 m/s, 10 m/s, and 15 m/s. The spray system was turned off and different heating fluxes were applied to heat the blade. The de-icing state and total energy consumption were explored. When de-icing occurred in a short freezing time, the ice layer became thin, and runback water flowed out (pattern I). With an increase in freezing time at a low wind speed, the melting ice induced by the dominant action of inertial force moved backward due to the reduction in adhesion between the ice and blade surface (pattern II). As wind speed increased, it exhibited various de-icing states, including refreezing at the trailing edge (pattern III) and ice shedding (pattern IV). The total energy consumption of ice melting decreased as the heat flux increased and the ice melting time shortened. At 5 m/s, when the heat flux was q = 14 kW/m2, the energy consumption at EA at tδ = 1 min, 5 min, and 7 min were 0.33 kJ, 0.55 kJ, and 0.61 kJ, respectively. At 10 m/s, when the heat flux was q = 14 kW/m2, the energy consumption at EA at tδ = 1 min, 3 min, and 5 min were 0.77 kJ, 0.81 kJ, and 0.80 kJ, respectively. Excessive heat flow density increased the risk of the return water freezing; thus, the reference de-icing heat fluxes of 5 m/s and 10 m/s were 10 kW/m2 and 12 kW/m2, respectively. This paper provides an effective reference for wind turbine de-icing. [ABSTRACT FROM AUTHOR]

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Wind turbine blades in excessive wind conditions present extreme deflection problems. For this reason, an analysis of the structural response of composite reinforced box beams is developed. For this purpose, reinforced box beams were fabricated to improve the bending strength in the flapwise direction of the wind turbine blades. The box beams were analyzed with three-dimensional models using the Finite Element Method (FEM) and validated with bending tests at four-points and two-points. The box beam meets the characteristics of lightness and mechanical strength. Experimental four-point bending results showed that reinforced cross-sections decrease displacements by 30.09% and increase their stiffness to 43.41% for a box beam without structural reinforcement. In addition, the two-point bending results showed a difference of 18.98% between the displacements of the beams with structural reinforcements. In the FEM analysis, a maximum error of 11.24% was obtained when correlating the maximum displacement value with the experimental results of the beams. [ABSTRACT FROM AUTHOR]

The efficient damage detection of the wind turbine blade (WTB), the core part of the wind power, is very improtant to wind power. In this paper, an improved YOLOv7 model is designed to enhance the performance of surface damage detection on WTBs based on the low-quality unmanned aerial vehicle (UAV) images. (1) An efficient channel attention (ECA) module is imbeded, which makes the network more sensitive to damage to decrease the false detection and missing detection caused by the low-quality image. (2) A DownSampling module is introduced to retain key feature information to enhance the detection speed and accuracy which are restricted by low-quality images with large amounts of redundant information. (3) The Multiple attributes Intersection over Union (MIoU) is applied to improve the inaccurate detection location and detection size of the damage region. (4) The dynamic group convolution shuffle transformer (DGST) is developed to improve the ability to comprehensively capture the contours, textures and potential damage information. Compared with YOLOv7, YOLOv8l, YOLOv9e and YOLOv10x, this experiment’s results show that the improved YOLOv7 has the optimal detection performance synthetically considering the detection accuracy, the detection speed and the robustness.

The leading-edge erosion of a wind turbine blade was tested using a whirling arm rain erosion tester, whose rotation rate is considerably higher than that of a full-scale wind turbine owing to the scale effect. In this study, we assessed the impact pressure of droplets on a wet surface of wind turbine blades using numerical simulation of liquid droplet impact by solving the Navier–Stokes equations combined with the volume-of-fluid method. This was conducted in combination with an estimation of liquid film thickness on the rotating blade using an approximate solution of Navier–Stokes equations considering the centrifugal and Coriolis forces. Our study revealed that the impact pressure on the rain erosion tester exceeded that on the wind turbine blade, attributed to the thinner liquid film on the rain erosion tester than on the wind turbine blade caused by the influence of centrifugal and Coriolis forces. This indicates the importance of correcting the influence of liquid-film thickness in estimating the impact velocity of droplets on the wind turbine blade. Furthermore, we demonstrated the correction procedure when estimating the impact velocity of droplets on the wind turbine blade.