Organic-inorganic hybrid perovskite solar cells have generated wide interest due to the rapid development of their photovoltaic conversion effciencies.However,the majority of the reported devices have been fabricated ...Organic-inorganic hybrid perovskite solar cells have generated wide interest due to the rapid development of their photovoltaic conversion effciencies.However,the majority of the reported devices have been fabricated via spin coating with a device areaof<1 cm2.In this study,we fabricated a wide-bandgap formamidi-nium lead bromide(FAPbBr3)film using a cost-effective,high-yielding doctor-blade-coating process.The effects of different surfactants,such as I-α-phosphatidylcholine,polyoxyethylene sorbitan monooleate,sodium lauryl sulfonate,and hexadecyl trimethyl ammonium bromide,were studied during the printing process.Accompanying the optimization of the blading temperature,crystal sizes of over 10μm and large-area perovskite films of5cm×5 cm were obtained using this method.The printed FAPbBr3 solar cells exhibited a short-circuit current density of 8.22 mA/cm2,an open-circuit voltage of 1.175 V,and an efficiency of 7.29%.Subsequently,we replaced the gold with silver nanowires as the top electrode to prepare a semitransparent perovskite solar cell with an average transmittance(400-800 nm)of 25.42%,achieving a high-power efficiency of 5.11%.This study demonstrates efficient doctor-blading printing for preparing large-area FAPbBr3 films that possess high potential for applications in building integrated photovoltaics.展开更多
The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind powe...The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind power continues to expand,the disposal of waste wind turbine blades(WWTB)has emerged as a significant challenge.These blades are predominantly composed of epoxy resin(EP)polymers,carbon fibers(CFs),and glass fibers(GFs).Improper disposal not only exacerbates environmental concerns but also leads to the loss of valuable resources,particularly carbon-based materials.Pyrolysis technology,a versatile and environmentally sustainable method for resource recovery,has garnered considerable attention in the context of WWTB disposal.This work presents a comprehensive review of the pyrolytic recycling of WWTB,focusing on the principles and classifications of pyrolysis technology,key factors influencing the pyrolysis process,as well as the pyrolysis methods,equipment,products,and their applications.Through an in-depth analysis of the current research on the pyrolytic recycling of WWTB,this review identifies critical unresolved issues in the field and provides a forward-looking perspective on emerging research trends.展开更多
Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft ...Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft flight at conventional rotational speeds in the Martian atmosphere.In this paper,we employ the Particle Swarm Optimization(PSO)algorithm to search for the control points of the Bezier curve,completing the parameterization of the airfoil upper and lower curves based on these control points.In order to directly enhance the lift-to-drag ratio of the airfoil at high angles of attack,the NSGA-II algorithm is utilized to optimize the lift-to-drag ratio of NACA 6904 at a=17.5°,Ma=0.43,Re=7600,and CLF 5605 at a=15°,Ma=0.7,Re=7481,respectively.The two-dimensional RANS(Reynolds Average NavierStokes)and k-ωSST turbulence models are employed in the optimization process by CFD to predict the lift and drag characteristics of the airfoil in a Martian environment.Under simulated Mars atmospheric conditions(pressure of 1380 Pa,test temperature of 24°C,equivalent Mars atmospheric density at the surface of 0.0162 g/cm~3),the airfoil after optimized is subjected to rotor lift-drag characteristic tests where a single-rotor lift-drag characteristic test bench is employed for verification.The experimental results demonstrate that the RB-TB-II blade,which is obtained by optimizing the airfoil based on the RB-SWQ-I blade,exhibits a 19.6%increase in Power Loading(PL)and a 20.4%increase in Figure of Merit(FM)compared with the RB-SWQ-I blade.Based on the results of airfoil optimization,increasing the camber at the leading edge of the airfoil under high angles of attack contributes to an improved lift-to-drag ratio.展开更多
A Hybrid Free-Form Deformation(HFFD)method is developed to improve shape preservation in mesh deformation for perforated surfaces,which traditional Free-Form Deformation(FFD)techniques struggle to handle effectively.T...A Hybrid Free-Form Deformation(HFFD)method is developed to improve shape preservation in mesh deformation for perforated surfaces,which traditional Free-Form Deformation(FFD)techniques struggle to handle effectively.The proposed method enables high-fidelity parameterized deformation for both flat and curved perforated surfaces while maintaining mesh quality with minimal geometric distortion.To evaluate its effectiveness,comparative studies between HFFD and conventional FFD methods are conducted,demonstrating superior performance in mesh quality and geometric fidelity.The HFFD-based framework is further applied to the Multidisciplinary Design Optimization(MDO)of a double-wall turbine blade leading edge.Results indicate an 11.6%increase in cooling efficiency and a 16.21%reduction in maximum stress.Additionally,compared to traditional geometry-based parameterization in MDO,the HFFD approach improves model processing efficiency by 84.15%and overall optimization efficiency by20.05%.These findings demonstrate HFFD's potential to significantly improve complex engineering design optimization by achieving precise shape preservation and improving computational efficiency.展开更多
Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operati...Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operation masks fault features,severely impairing the fault diagnosis performance of deep learning models.Second,current blade fault diagnosis often relies on single-sensor data,resulting in limited monitoring dimensions and ability to comprehensively capture complex fault states.To address these issues,a multi-sensor fusion-based wind turbine blade fault diagnosis method is proposed.Specifically,a CNN-Transformer Coupled Feature Learning Architecture is constructed to enhance the ability to learn complex features under noisy conditions,while a Weight-Aligned Data Fusion Module is designed to comprehensively and effectively utilize multi-sensor fault information.Experimental results of wind turbine blade fault diagnosis under different noise interferences show that higher accuracy is achieved by the proposed method compared to models with single-source data input,enabling comprehensive and effective fault diagnosis.展开更多
To address challenges in wind turbine blade defect detection models,primarily due to insufficient feature extraction capabilities and the difficulty of deploying models on drone-type edge devices,this study proposes a...To address challenges in wind turbine blade defect detection models,primarily due to insufficient feature extraction capabilities and the difficulty of deploying models on drone-type edge devices,this study proposes a wind turbine blade defect detection model,WtCS-YOLO11,that incorporates multiscale feature extraction and an attention mechanism.Firstly,the cross-stage partial with two kernels and a wavelet convolution module(C3k2_WTConv)is proposed by introducing wavelet convolution into the module.The cross-stage partial with two kernels(C3k2)module in the necking network is replaced with the C3k2_WTConv module to increase the model’s receptive field,enable multiscale feature extraction,and reduce computational parameter usage.Second,the convolutional block attention module(CBAM)is proposed and applied to the neck network,integrating channel and spatial attention,allowing the model to focus on essential features and enhance its ability to detect large targets.In addition,the model employs shape-aware intersection over union(Shape-IoU),which focuses on the shape and scale of bounding boxes,and combines the normalized Wasserstein distance(NWD)to calculate bounding box similarity,thereby improving the accuracy of bounding-box regression.In this study,a dataset for wind turbine blade defect detection was constructed covering six defect categories.The experimental results showed that the precision(P),recall(R),and mean average precision at the intersection over union threshold of 0.5(mAP50)for the WtCS-YOLO11 model were 84.4%,86.9%,and 89.7%,respectively.Compared to the baseline You Only Look Once 11(YOLO11)model,P,R,and mAP50 improved by 5.9%,2.5%,and 2.4%,respectively,with virtually no increase in computational complexity or parameter count.WtCS-YOLO11 improved the precision measurement accuracy.Its model size and computational complexity are suitable for deployment on edge devices,and it achieves high inference speed,meeting the application requirements for real-time wind turbine blade defect detection.展开更多
Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-...Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-tional image-processing pipelines struggle with scalability and robustness,and recent deep learning methods remain sensitive to class imbalance and acquisition variability.This paper introduces TurbineBladeDetNet,a convolutional architecture combining dual-attention mechanisms with multi-path feature extraction for detecting five distinct blade fault types.Our approach employs both channel-wise and spatial attention modules alongside an Albumentations-driven augmentation strategy to handle dataset imbalance and capture condition variability.The model achieves 97.14%accuracy,98.65%precision,and 98.68%recall,yielding a 98.66%F1-score with 0.0110 s inference time.Class-specific analysis shows uniformly high sensitivity and specificity;lightning damage reaches 99.80%for sensitivity,precision,and F1-score,and crack achieves perfect precision and specificity with a 98.94%F1-score.Comparative evaluation against recent wind-turbine inspection approaches indicates higher performance in both accuracy and F1-score.The resulting balance of sensitivity and specificity limits both missed defects and false alarms,supporting reliable deployment in routine unmanned aerial vehicle(UAV)inspection.展开更多
Spiral pile foundations,as a promising type of foundation,are of significant importance for the development of offshore wind energy,particularly as it moves toward deeper waters.This study conducted a physical experim...Spiral pile foundations,as a promising type of foundation,are of significant importance for the development of offshore wind energy,particularly as it moves toward deeper waters.This study conducted a physical experiment on a three-spiral-pile jacket foundation under deep-buried sandy soil conditions.During the experiment,horizontal displacement was applied to the structure to thoroughly investigate the bearing characteristics of the three-spiral-pile jacket foundation.This study also focused on analyzing the bearing mechanisms of conventional piles compared with spiral piles with different numbers of blades.Three different working conditions were set up and compared,and key data,such as the horizontal bearing capacity,pile shaft axial force,and spiral blade soil pressure,were measured and analyzed.The results show the distinct impacts of the spiral blades on the compressed and tensioned sides of the foundation.Specifically,on the compressed side,the spiral blades effectively enhance the restraint of the soil on the pile foundation,whereas on the tensioned side,an excessive number of spiral blades can negatively affect the structural tensile performance to some extent.This study also emphasizes that the addition of blades to the side of a single pile is the most effective method for increasing the bearing capacity of the foundation.This research aims to provide design insights into improving the bearing capacity of the foundation.展开更多
To facilitate the low-noise design of tandem lift bodies as applied in aeroengines and aircraft,the acoustic features of tandem blades are investigated by wind-tunnel experiments.This is further specialized for the ro...To facilitate the low-noise design of tandem lift bodies as applied in aeroengines and aircraft,the acoustic features of tandem blades are investigated by wind-tunnel experiments.This is further specialized for the rotating blades applied in contra-rotating open rotors under the concept of frozen-rotor.A 70-channel phased microphone array and nine high-precision free-field microphones are employed.The beamforming method,enhanced by a source filtering technique,is employed to locate noise sources,providing insights into the source patterns of blade-blade interaction noise concerning flow speed,blade spacing,and aft blade clipping.The results show the following:(A)Sources of tandem-blade noise exist in the form of concentrated source clusters,resulting in two major clusters:the mid-span interaction noise and the tip-induced noise.(B)These source clusters tend to separate as flow speed or blade spacing increases.(C)By increasing blade spacing,the band-pass filtered overall sound pressure level is reduced by 2.9 dB.(D)A two-phase noise suppression pattern is observed with blade clipping,resulting in a total reduction of 3.0 dB for the interaction noise through the removal of tip-induced noise sources and the replacement of mid-span noise sources.Based on these findings,suggestions concerning blade spacing and clipping are discussed.展开更多
Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.Howev...Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.展开更多
Accurate measurement of helicopter rotor motion parameters(flap,lead-lag,torsion,and azimuth angles)is essential for rotor blade design,helicopter dynamics modeling,and flight safety and health monitoring.However,the ...Accurate measurement of helicopter rotor motion parameters(flap,lead-lag,torsion,and azimuth angles)is essential for rotor blade design,helicopter dynamics modeling,and flight safety and health monitoring.However,the existing methods face challenges in testing equipment installation,calibration,and data transmission,resulting in limited reports on real-time in-flight measurements of blade motion parameters.This paper proposes a non-contact optoelectronic method based on two-dimensional position-sensitive detectors for in-flight measurement and a ground calibration system to obtain real-time rotor motion parameters during helicopter flight.The proposed method establishes the time evolution relationship of rotor motion parameters and verifies the performance of the in-flight measurement system regarding measurement resolution and accuracy through the construction of a blade motion posture experimental platform.The proposed method has been applied to the flight measurement of a medium-sized single-rotor helicopter,and the obtained results have been compared with theoretical analysis outcomes.Furthermore,this paper examines the characteristics of blade motion parameters during flight and discusses the challenges and potential solutions for measuring rotor motion parameters during helicopter flight using the proposed method.展开更多
Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the random...Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the randomness of structural parameters,working condition and vibration environment are considered for fatigue life predication and reliability assessment.First,the lowcycle fatigue problem is modelled as stochastic static system with random parameters,while the high-cycle fatigue problem is considered as stochastic dynamic system under random excitations.Then,to deal with the two failure modes,the novel Direct Probability Integral Method(DPIM)is proposed,which is efficient and accurate for solving stochastic static and dynamic systems.The probability density functions of accumulated damage and fatigue life of turbine blade for low-cycle and high-cycle fatigue problems are achieved,respectively.Furthermore,the time–frequency hybrid method is advanced to enhance the computational efficiency for governing equation of system.Finally,the results of typical examples demonstrate high accuracy and efficiency of the proposed method by comparison with Monte Carlo simulation and other methods.It is indicated that the DPIM is a unified method for predication of random fatigue life for low-cycle and highcycle fatigue problems.The rotational speed,density,fatigue strength coefficient,and fatigue plasticity index have a high sensitivity to fatigue reliability of engine turbine blade.展开更多
Thermal barrier coatings(TBCs)are extensively utilized in aero-engines and heavy-duty gas turbines due to their outstanding properties,including low thermal conductivity,corrosion,high-temperature oxidation,and wear r...Thermal barrier coatings(TBCs)are extensively utilized in aero-engines and heavy-duty gas turbines due to their outstanding properties,including low thermal conductivity,corrosion,high-temperature oxidation,and wear resistance.The rising thrust-to-weight ratio and service temperature in engine hot sections have presented a significant challenge in TBC's materials,structure,and preparation process;it is one of the current research hotspots in the aviation field.This paper reviews the recent advancement in turbine blade TBCs.It focuses on the TBC's structure,deposition mechanism and the key performance evaluation indexes for TBCs applied to turbine blades.Finally,the future research field of TBCs for turbine blades is also be prospected.展开更多
Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization proces...Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization processes lead to different order of crystallization dynamics within the perovskite thin film,resulting in the differences of additive distribution.We then tailor-designed an additive molecule named 1,3-bis(4-methoxyphenyl)thiourea to obtain films with fewer defects and holes at the buried interface,and prepared perovskite solar cells with a certified efficiency of 23.75%.Furthermore,this work also demonstrates an efficiency of 20.18%for the large-area perovskite solar module(PSM)with an aperture area of 60.84 cm^(2).The PSM possesses remarkable continuous operation stability for maximum power point tracking of T_(90)>1000 h in ambient air.展开更多
Anti-aliasing spectrum analysis is essential for rotor blade condition monitoring based on Blade Tip Timing(BTT).The Multiple Signal Classification(MUSIC)algorithm,which exploits the orthogonality between signal and n...Anti-aliasing spectrum analysis is essential for rotor blade condition monitoring based on Blade Tip Timing(BTT).The Multiple Signal Classification(MUSIC)algorithm,which exploits the orthogonality between signal and noise subspaces,has been successfully applied for this purpose.However,conventional subspace selection methods relying on fixed thresholds are sensitive to variations in large eigenvalues.Furthermore,the complex disturbances during rotor operation and measurement complicate the identification of blade vibration characteristics.To overcome these challenges,this paper proposes Adaptive Subspace Separation(ASS)and Local Spectral Centroid(LSC)methods to improve the adaptability of subspace selection and the stability of frequency identification,respectively.The impacts of overestimating and underestimating the subspace dimensions on MUSIC's performance are derived mathematically.Simulation and experiments demonstrate the effectiveness of proposed approaches:ASS offers more accurate and stable subspace dimension selection and tracking,while LSC reduces the standard deviation of estimated frequencies by 30 percent.展开更多
Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like freq...Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like frequency from such signals is possible,achieving high-precision vibration parameters remains challenging.This paper proposed a novel two-stage off-grid estimation method.It leverages a unique array layout(coprime array)to obtain a regular augmented covariance matrix.Subsequently,parameters in the matrix are recovered using the sparse iterative covariance-based estimation method based on covariance fitting criteria.Finally,high-precision estimates of imprecise parameters are obtained using unconditional maximum likelihood estimation,effectively eliminating the effects of basis mismatch.Through substantial numerical and experimental validation,the proposed method demonstrates significantly higher accuracy compared to classical BTT parameter estimation methods,approaching the lower bound of unbiased estimation variance.Furthermore,due to its immunity to frequency gridding,it can track minor frequency deviations,making it more suitable for indicating blade condition.展开更多
基金supported by the National Key Research and Development Plan(No.2017YFE0131900)the National Natural Science Foundation of China(Grant Nos.51672202 and 21875178)J.Z.thanks the support from the"Chutian Scholar Program" of Hubei Province,China.
文摘Organic-inorganic hybrid perovskite solar cells have generated wide interest due to the rapid development of their photovoltaic conversion effciencies.However,the majority of the reported devices have been fabricated via spin coating with a device areaof<1 cm2.In this study,we fabricated a wide-bandgap formamidi-nium lead bromide(FAPbBr3)film using a cost-effective,high-yielding doctor-blade-coating process.The effects of different surfactants,such as I-α-phosphatidylcholine,polyoxyethylene sorbitan monooleate,sodium lauryl sulfonate,and hexadecyl trimethyl ammonium bromide,were studied during the printing process.Accompanying the optimization of the blading temperature,crystal sizes of over 10μm and large-area perovskite films of5cm×5 cm were obtained using this method.The printed FAPbBr3 solar cells exhibited a short-circuit current density of 8.22 mA/cm2,an open-circuit voltage of 1.175 V,and an efficiency of 7.29%.Subsequently,we replaced the gold with silver nanowires as the top electrode to prepare a semitransparent perovskite solar cell with an average transmittance(400-800 nm)of 25.42%,achieving a high-power efficiency of 5.11%.This study demonstrates efficient doctor-blading printing for preparing large-area FAPbBr3 films that possess high potential for applications in building integrated photovoltaics.
基金Supported by the National Natural Science Foundation of China(22468035,22468036,22368038,22308048)the Natural Science Foundation of Inner Mongolia(2024QN02018,2025MS02030)+2 种基金First-class Discipline Research Special Project of Inner Mongolia(YLXKZX-NGD-045)Inner Mongolia Autonomous Region Postgraduate Research Innovation Project(KC2024047B)Research Foundation for Introducing High-level Talents in Inner Mongolia Autonomous Region。
文摘The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind power continues to expand,the disposal of waste wind turbine blades(WWTB)has emerged as a significant challenge.These blades are predominantly composed of epoxy resin(EP)polymers,carbon fibers(CFs),and glass fibers(GFs).Improper disposal not only exacerbates environmental concerns but also leads to the loss of valuable resources,particularly carbon-based materials.Pyrolysis technology,a versatile and environmentally sustainable method for resource recovery,has garnered considerable attention in the context of WWTB disposal.This work presents a comprehensive review of the pyrolytic recycling of WWTB,focusing on the principles and classifications of pyrolysis technology,key factors influencing the pyrolysis process,as well as the pyrolysis methods,equipment,products,and their applications.Through an in-depth analysis of the current research on the pyrolytic recycling of WWTB,this review identifies critical unresolved issues in the field and provides a forward-looking perspective on emerging research trends.
基金supported by the National Key R&D Program of China(No.2024YFC3015804)the Basic Science Center Program for“Space Robot Intelligent Manipulation”,China(No.T2388101)。
文摘Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft flight at conventional rotational speeds in the Martian atmosphere.In this paper,we employ the Particle Swarm Optimization(PSO)algorithm to search for the control points of the Bezier curve,completing the parameterization of the airfoil upper and lower curves based on these control points.In order to directly enhance the lift-to-drag ratio of the airfoil at high angles of attack,the NSGA-II algorithm is utilized to optimize the lift-to-drag ratio of NACA 6904 at a=17.5°,Ma=0.43,Re=7600,and CLF 5605 at a=15°,Ma=0.7,Re=7481,respectively.The two-dimensional RANS(Reynolds Average NavierStokes)and k-ωSST turbulence models are employed in the optimization process by CFD to predict the lift and drag characteristics of the airfoil in a Martian environment.Under simulated Mars atmospheric conditions(pressure of 1380 Pa,test temperature of 24°C,equivalent Mars atmospheric density at the surface of 0.0162 g/cm~3),the airfoil after optimized is subjected to rotor lift-drag characteristic tests where a single-rotor lift-drag characteristic test bench is employed for verification.The experimental results demonstrate that the RB-TB-II blade,which is obtained by optimizing the airfoil based on the RB-SWQ-I blade,exhibits a 19.6%increase in Power Loading(PL)and a 20.4%increase in Figure of Merit(FM)compared with the RB-SWQ-I blade.Based on the results of airfoil optimization,increasing the camber at the leading edge of the airfoil under high angles of attack contributes to an improved lift-to-drag ratio.
基金supported by the National Science and Technology Major Project,China(No.2017-II-0006-0019)the National Natural Science Foundation of China(No.52375266)the Shaanxi Science Foundation for Distinguished Young Scholars,China(No.2022JC-36)。
文摘A Hybrid Free-Form Deformation(HFFD)method is developed to improve shape preservation in mesh deformation for perforated surfaces,which traditional Free-Form Deformation(FFD)techniques struggle to handle effectively.The proposed method enables high-fidelity parameterized deformation for both flat and curved perforated surfaces while maintaining mesh quality with minimal geometric distortion.To evaluate its effectiveness,comparative studies between HFFD and conventional FFD methods are conducted,demonstrating superior performance in mesh quality and geometric fidelity.The HFFD-based framework is further applied to the Multidisciplinary Design Optimization(MDO)of a double-wall turbine blade leading edge.Results indicate an 11.6%increase in cooling efficiency and a 16.21%reduction in maximum stress.Additionally,compared to traditional geometry-based parameterization in MDO,the HFFD approach improves model processing efficiency by 84.15%and overall optimization efficiency by20.05%.These findings demonstrate HFFD's potential to significantly improve complex engineering design optimization by achieving precise shape preservation and improving computational efficiency.
基金supported by the China Three Gorges Corporation(No.NBZZ202300860)the National Natural Science Foundation of China(No.52275104)the Science and Technology Innovation Program of Hunan Province(No.2023RC3097).
文摘Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operation masks fault features,severely impairing the fault diagnosis performance of deep learning models.Second,current blade fault diagnosis often relies on single-sensor data,resulting in limited monitoring dimensions and ability to comprehensively capture complex fault states.To address these issues,a multi-sensor fusion-based wind turbine blade fault diagnosis method is proposed.Specifically,a CNN-Transformer Coupled Feature Learning Architecture is constructed to enhance the ability to learn complex features under noisy conditions,while a Weight-Aligned Data Fusion Module is designed to comprehensively and effectively utilize multi-sensor fault information.Experimental results of wind turbine blade fault diagnosis under different noise interferences show that higher accuracy is achieved by the proposed method compared to models with single-source data input,enabling comprehensive and effective fault diagnosis.
基金supported in part by the Science and Technology Research Project of Henan Province under grants 242102240040 and 222102210087in part by the Training Plan for Young Backbone Teachers at Undergraduate Universities in Henan Province under grant 2024GGJS155.
文摘To address challenges in wind turbine blade defect detection models,primarily due to insufficient feature extraction capabilities and the difficulty of deploying models on drone-type edge devices,this study proposes a wind turbine blade defect detection model,WtCS-YOLO11,that incorporates multiscale feature extraction and an attention mechanism.Firstly,the cross-stage partial with two kernels and a wavelet convolution module(C3k2_WTConv)is proposed by introducing wavelet convolution into the module.The cross-stage partial with two kernels(C3k2)module in the necking network is replaced with the C3k2_WTConv module to increase the model’s receptive field,enable multiscale feature extraction,and reduce computational parameter usage.Second,the convolutional block attention module(CBAM)is proposed and applied to the neck network,integrating channel and spatial attention,allowing the model to focus on essential features and enhance its ability to detect large targets.In addition,the model employs shape-aware intersection over union(Shape-IoU),which focuses on the shape and scale of bounding boxes,and combines the normalized Wasserstein distance(NWD)to calculate bounding box similarity,thereby improving the accuracy of bounding-box regression.In this study,a dataset for wind turbine blade defect detection was constructed covering six defect categories.The experimental results showed that the precision(P),recall(R),and mean average precision at the intersection over union threshold of 0.5(mAP50)for the WtCS-YOLO11 model were 84.4%,86.9%,and 89.7%,respectively.Compared to the baseline You Only Look Once 11(YOLO11)model,P,R,and mAP50 improved by 5.9%,2.5%,and 2.4%,respectively,with virtually no increase in computational complexity or parameter count.WtCS-YOLO11 improved the precision measurement accuracy.Its model size and computational complexity are suitable for deployment on edge devices,and it achieves high inference speed,meeting the application requirements for real-time wind turbine blade defect detection.
文摘Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-tional image-processing pipelines struggle with scalability and robustness,and recent deep learning methods remain sensitive to class imbalance and acquisition variability.This paper introduces TurbineBladeDetNet,a convolutional architecture combining dual-attention mechanisms with multi-path feature extraction for detecting five distinct blade fault types.Our approach employs both channel-wise and spatial attention modules alongside an Albumentations-driven augmentation strategy to handle dataset imbalance and capture condition variability.The model achieves 97.14%accuracy,98.65%precision,and 98.68%recall,yielding a 98.66%F1-score with 0.0110 s inference time.Class-specific analysis shows uniformly high sensitivity and specificity;lightning damage reaches 99.80%for sensitivity,precision,and F1-score,and crack achieves perfect precision and specificity with a 98.94%F1-score.Comparative evaluation against recent wind-turbine inspection approaches indicates higher performance in both accuracy and F1-score.The resulting balance of sensitivity and specificity limits both missed defects and false alarms,supporting reliable deployment in routine unmanned aerial vehicle(UAV)inspection.
基金The National Natural Science Foundation of China(No.52171274).
文摘Spiral pile foundations,as a promising type of foundation,are of significant importance for the development of offshore wind energy,particularly as it moves toward deeper waters.This study conducted a physical experiment on a three-spiral-pile jacket foundation under deep-buried sandy soil conditions.During the experiment,horizontal displacement was applied to the structure to thoroughly investigate the bearing characteristics of the three-spiral-pile jacket foundation.This study also focused on analyzing the bearing mechanisms of conventional piles compared with spiral piles with different numbers of blades.Three different working conditions were set up and compared,and key data,such as the horizontal bearing capacity,pile shaft axial force,and spiral blade soil pressure,were measured and analyzed.The results show the distinct impacts of the spiral blades on the compressed and tensioned sides of the foundation.Specifically,on the compressed side,the spiral blades effectively enhance the restraint of the soil on the pile foundation,whereas on the tensioned side,an excessive number of spiral blades can negatively affect the structural tensile performance to some extent.This study also emphasizes that the addition of blades to the side of a single pile is the most effective method for increasing the bearing capacity of the foundation.This research aims to provide design insights into improving the bearing capacity of the foundation.
基金supported by grants from the National Natural Science Foundation of China(Nos.12102451,12072186)the National Science and Technology Major Project,China(No.J2019-II-0006-0026)AVIC Aerodynamics Research Institute,China(No.XFX20220201).
文摘To facilitate the low-noise design of tandem lift bodies as applied in aeroengines and aircraft,the acoustic features of tandem blades are investigated by wind-tunnel experiments.This is further specialized for the rotating blades applied in contra-rotating open rotors under the concept of frozen-rotor.A 70-channel phased microphone array and nine high-precision free-field microphones are employed.The beamforming method,enhanced by a source filtering technique,is employed to locate noise sources,providing insights into the source patterns of blade-blade interaction noise concerning flow speed,blade spacing,and aft blade clipping.The results show the following:(A)Sources of tandem-blade noise exist in the form of concentrated source clusters,resulting in two major clusters:the mid-span interaction noise and the tip-induced noise.(B)These source clusters tend to separate as flow speed or blade spacing increases.(C)By increasing blade spacing,the band-pass filtered overall sound pressure level is reduced by 2.9 dB.(D)A two-phase noise suppression pattern is observed with blade clipping,resulting in a total reduction of 3.0 dB for the interaction noise through the removal of tip-induced noise sources and the replacement of mid-span noise sources.Based on these findings,suggestions concerning blade spacing and clipping are discussed.
基金Supported by the National Natural Science Foundation of China(Nos.52222904 and 52309117)China Postdoctoral Science Foundation(Nos.2022TQ0168 and 2023M731895).
文摘Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.
基金the funding provided by the National Helicopter Development Project of China。
文摘Accurate measurement of helicopter rotor motion parameters(flap,lead-lag,torsion,and azimuth angles)is essential for rotor blade design,helicopter dynamics modeling,and flight safety and health monitoring.However,the existing methods face challenges in testing equipment installation,calibration,and data transmission,resulting in limited reports on real-time in-flight measurements of blade motion parameters.This paper proposes a non-contact optoelectronic method based on two-dimensional position-sensitive detectors for in-flight measurement and a ground calibration system to obtain real-time rotor motion parameters during helicopter flight.The proposed method establishes the time evolution relationship of rotor motion parameters and verifies the performance of the in-flight measurement system regarding measurement resolution and accuracy through the construction of a blade motion posture experimental platform.The proposed method has been applied to the flight measurement of a medium-sized single-rotor helicopter,and the obtained results have been compared with theoretical analysis outcomes.Furthermore,this paper examines the characteristics of blade motion parameters during flight and discusses the challenges and potential solutions for measuring rotor motion parameters during helicopter flight using the proposed method.
基金supports of the National Natural Science Foundation of China(Nos.12032008,12102080)the Fundamental Research Funds for the Central Universities,China(No.DUT23RC(3)038)are much appreciated。
文摘Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the randomness of structural parameters,working condition and vibration environment are considered for fatigue life predication and reliability assessment.First,the lowcycle fatigue problem is modelled as stochastic static system with random parameters,while the high-cycle fatigue problem is considered as stochastic dynamic system under random excitations.Then,to deal with the two failure modes,the novel Direct Probability Integral Method(DPIM)is proposed,which is efficient and accurate for solving stochastic static and dynamic systems.The probability density functions of accumulated damage and fatigue life of turbine blade for low-cycle and high-cycle fatigue problems are achieved,respectively.Furthermore,the time–frequency hybrid method is advanced to enhance the computational efficiency for governing equation of system.Finally,the results of typical examples demonstrate high accuracy and efficiency of the proposed method by comparison with Monte Carlo simulation and other methods.It is indicated that the DPIM is a unified method for predication of random fatigue life for low-cycle and highcycle fatigue problems.The rotational speed,density,fatigue strength coefficient,and fatigue plasticity index have a high sensitivity to fatigue reliability of engine turbine blade.
基金supported by the National Natural Science Foundation of China(Grant No.52271087).
文摘Thermal barrier coatings(TBCs)are extensively utilized in aero-engines and heavy-duty gas turbines due to their outstanding properties,including low thermal conductivity,corrosion,high-temperature oxidation,and wear resistance.The rising thrust-to-weight ratio and service temperature in engine hot sections have presented a significant challenge in TBC's materials,structure,and preparation process;it is one of the current research hotspots in the aviation field.This paper reviews the recent advancement in turbine blade TBCs.It focuses on the TBC's structure,deposition mechanism and the key performance evaluation indexes for TBCs applied to turbine blades.Finally,the future research field of TBCs for turbine blades is also be prospected.
基金supported by National Natural Science Foundation of China(62104082)Guangdong Basic and Applied Basic Research Foundation(2022A1515010746,2022A1515011228,and 2022B1515120006)the Science and Technology Program of Guangzhou(202201010458).
文摘Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization processes lead to different order of crystallization dynamics within the perovskite thin film,resulting in the differences of additive distribution.We then tailor-designed an additive molecule named 1,3-bis(4-methoxyphenyl)thiourea to obtain films with fewer defects and holes at the buried interface,and prepared perovskite solar cells with a certified efficiency of 23.75%.Furthermore,this work also demonstrates an efficiency of 20.18%for the large-area perovskite solar module(PSM)with an aperture area of 60.84 cm^(2).The PSM possesses remarkable continuous operation stability for maximum power point tracking of T_(90)>1000 h in ambient air.
基金supported by the National Natural Science Foundation of China(Nos.52405088 and 92360306)the Postdoctoral Fellowship Program of CPSF,China(No.GZC20241446)+2 种基金the Natural Science Basic Research Program of Shaanxi,China(No.2024JC-YBMS-402)the Fundamental Research Funds for the Central Universities,CHD(No.300102254102)the Foundation of Beilin District,China(No.GX2455)。
文摘Anti-aliasing spectrum analysis is essential for rotor blade condition monitoring based on Blade Tip Timing(BTT).The Multiple Signal Classification(MUSIC)algorithm,which exploits the orthogonality between signal and noise subspaces,has been successfully applied for this purpose.However,conventional subspace selection methods relying on fixed thresholds are sensitive to variations in large eigenvalues.Furthermore,the complex disturbances during rotor operation and measurement complicate the identification of blade vibration characteristics.To overcome these challenges,this paper proposes Adaptive Subspace Separation(ASS)and Local Spectral Centroid(LSC)methods to improve the adaptability of subspace selection and the stability of frequency identification,respectively.The impacts of overestimating and underestimating the subspace dimensions on MUSIC's performance are derived mathematically.Simulation and experiments demonstrate the effectiveness of proposed approaches:ASS offers more accurate and stable subspace dimension selection and tracking,while LSC reduces the standard deviation of estimated frequencies by 30 percent.
基金the National Natural Science Foundation of China(Nos.52105117,52222504&51875433)the Funds for Distinguished Young talent of Shaanxi Province,China(No.2019JC-04)。
文摘Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like frequency from such signals is possible,achieving high-precision vibration parameters remains challenging.This paper proposed a novel two-stage off-grid estimation method.It leverages a unique array layout(coprime array)to obtain a regular augmented covariance matrix.Subsequently,parameters in the matrix are recovered using the sparse iterative covariance-based estimation method based on covariance fitting criteria.Finally,high-precision estimates of imprecise parameters are obtained using unconditional maximum likelihood estimation,effectively eliminating the effects of basis mismatch.Through substantial numerical and experimental validation,the proposed method demonstrates significantly higher accuracy compared to classical BTT parameter estimation methods,approaching the lower bound of unbiased estimation variance.Furthermore,due to its immunity to frequency gridding,it can track minor frequency deviations,making it more suitable for indicating blade condition.
