Turbine Blade Surface Research Articles

Preparation and anti-icing performance of liquid lubricant micro-nano composite coating based on modified nano-SiO2

Lubricant coating is an efficient method for preventing ice formation on the surface of wind turbine blades. However, lubricants are frequently lost during the freezing and deicing cycles, along with the migration of frost or ice. As a result, developing a lubricating anti-icing coating with high wear resistance and stability is critical for resolving the icing problem on fan blades. In this paper, 3-Aminopropyltriethoxysilane (KH-550) coupling agent was used to modify the nano-SiO2 particles to construct the micro-nano rough surface of the coating. Then, liquid paraffin lubricant was injected to obtain a new type of self-supplemented lubricating micro-nano composite coating, and its mechanical wear resistance and anti-icing performance were explored. The experimental results show that the contact angle of the liquid lubricating liquid micro-nano composite coating is still >105° and the sliding angle is <15° after 50 wear tests, showing good ice repellency, indicating that its wear resistance is enhanced. According to the standard ISO 2049, the mechanical adhesion reaches grade 0, showing good mechanical stability. The ice adhesion of the composite coating is 85.6% lower than that of the unlubricated sample, and the mechanical interlock between ice and the rough surface was greatly reduced. In comparison to the non-lubricating liquid coating, the micro-nano composite coating effectively extends the total freezing time of water droplets, reaching 821 s and demonstrating good anti-icing performance.

Using optical flow algorithm based on dynamic illumination mode to examine defects on highly reflective turbine blade surface

Notion of optical flow literally refers to the displacements of intensity patterns. In that sense, extracting interested information from 2D scene is analogy to modulation/demodulation in random signal processing. To address the limitations presented in computer vision based on static image, we propose a novel metal component defect detection method, specified as the instance of turbine blade surface detection, using optical flow estimation.To start the specified pattern recognition in 2D presentation, we modulate the brightness constancy assumption equation as illumination varying model, by sampling the second image with function whose frequency was chosen according to the Nyquist sampling theorem, and a sinusoidal factor was introduced as an additive factor. This tunable channel based on 2D image transfers intensity features into optical modes. Then, we implement optical flow estimation on two sequential images. Experimental results reveal grayscale space shows completness in representing the optical modes of turbine blade with various kinds of surface characteristics. By modifying the index of information content, we propose quantitative index to evaluate the performance of our method. Evaluation reveals optical flow algorithm is qualified to examine defects on highly reflective turbine blade, and our method extends the application of optical flow.

FEATURES OF GEOMETRIC SURFACES AND METHODS OF THEIR COMPUTER MODELING

This paper is devoted to the topical issue of studying the shapes of geometric surfaces in terms of descriptive geometry and their computer modeling. Definitions of algebraic and geometric surfaces are given. The analysis of features and parameters of surfaces for their classification into the main groups that are most common in practice is performed. The main methods of setting surfaces used in practice, depending on the shape of the surface and the task are given. Analytical, kinematic and frame methods of setting surfaces have been studied. The analytical method is presented on the basis of a conical surface of rotation; the canonical equation of the surface is analyzed, its correspondence for the upper and lower cone cavities is shown. The conical surface is graphically displayed in the AutoCAD graphics system. The peculiarities of the kinematic method of surface formation, which is presented on the example of the surface of rotation, made in the graphics system AutoCAD, and the surface of a straight hyperboloid, the drawing of which is made in the system COMPASS-3D. Examples of practical use of simulated surfaces are given. Enough attention is paid to the study of frame surfaces. A complex drawing of the surface of a cylinder given by a linear framework is given. The three-line frame of the ship's surface, which is formed by waterlines, frames and buttocks, is presented in detail. Simulated frame surface of an axial gas turbine blade is presented in the AutoCAD system. Algorithms and methods of geometric modeling of surfaces in graphic systems AutoCAD and KOMPAS-3D are given. Geometric models of some surfaces have been developed: straight helicoid, single-cavity hyperboloid, hyperbolic paraboloid, surface with return edge, etc. Examples of practical implementation of simulated surfaces are given.

Acoustic-based method for identifying surface damage to wind turbine blades by using a convolutional neural network

Damage to the surface of the blades of a large wind turbine may lead to catastrophic blade failure. Although numerous methods have been proposed for detecting surface damage to wind turbine blades, many of them involve laboratory tests because of the difficulty in acquiring data from a commercial wind farm. This lack of data variety is an obstacle to the development of machine learning approaches for identifying the aforementioned damage. Therefore, we developed a damage detection method for wind turbine blade surfaces that is based on the physical correlation between surface conditions and acoustic signals of operating wind turbines under realistic environmental conditions. In the preprocessing stage of the aforementioned method, the short-time Fourier transform and smoothing techniques are used to analyze real-time spectrograms and the rotor speed. The derived spectrogram and rotor speed are then input into a convolutional neural network (CNN) to classify the wind turbine blade surfaces into two classes: turbines with at least one or no damaged blade. The CNN proposed in this paper is a hybrid network containing a masking module and residual classifier. The masking module suppresses redundant information in the spectrogram, and the residual classifier quantifies the difference between the masked spectrogram and a standard spectrogram. The proposed CNN can be easily trained on a small dataset with a few trainable parameters by using the physical characteristics in the residual classifier. The proposed damage detection method was evaluated using the operational noise of commercial wind turbines; according to the results, this method outperformed approaches proposed in previous studies and exhibited an accuracy of 97.11%.

Fault identification of fan blade based on improved ResNet-18

With the continuous development of the wind industry, wind turbine blade failure causes wind turbine shutdown, which damages the revenue of wind power. In order to more effectively detect the damage on the surface of wind turbine blade. By comparing ResNet-18 /50, VGG-19 and GoogLeNet models, ResNet-18 has the advantages of short training time and high accuracy. Therefore, ResNet-18 convolutional neural network is selected as the basic network, and a deep learning training and detection model is built based on MATLAB. In order to further optimize the model, multiple convolution kernel is selected for the main branch of residual structure of ResNet-18 to extract features, and add 3×3 pool layer, it is used to improve the learning ability of the model. In addition, Aadm, Sgdm and Rmsprop optimization algorithms are added to further improve the robustness of the model. Experiments show that the classification and recognition accuracy of the improved ResNet-18 model for fan blades is 94.17%, which is 2.5% higher than that of the original model. The improved ResNet-18 model has good recognition effect,it improves a faster and more accurate solution for fan blade surface damage identification in complex weather environment.

SOD‐YOLO: A Small Target Defect Detection Algorithm for Wind Turbine Blades Based on Improved YOLOv5

AbstractEarly and effective detection of wind turbine blade (WTB) surface defects can avoid complex and expensive repair problems and serious safety hazards. The traditional target detection methods have the problems of insufficient detection capability, long model inference time and low recognition accuracy for small targets and long strip defects in WTB datasets. This paper proposes a high‐precision model SOD‐YOLO for WTB surface defect detection based on UAVs image analysis of YOLOv5. First, the WTB images are preprocessed by foreground segmentation and Hough transform to build the WTB defect dataset. Then, a micro‐scale detection layer is added to the original YOLOv5, and the K‐means algorithm is used to re‐cluster anchors and add the CBAM attention mechanism to each feature fusion layer to reduce the loss of feature information for small target defects and other defects. In addition, to improve the detection efficiency, the channel pruning algorithm is used to reduce the model size. The experimental results show that the average accuracy (mAP) of the SOD‐YOLO algorithm on the WTB dataset reaches 95.1%, which is 7.82% better than YOLOv5, and the FPS is 28.3% better. Therefore, SOD‐YOLO is able to detect small target defects and other defects quickly and effectively.

Real-time detection of damage evolution and failure of EB-PVD thermal barrier coatings using an environmental simulator with high-temperature and high-speed rotation

Thermal barrier coatings (TBCs) are key to improving aero-engine performance. The lifetime assessment of TBCs in a simulation environment is an essential consideration for successful application. Environmental simulators for rotor blade TBCs are still scarce, largely owing to the difficulty in obtaining real-time TBC failure data in extreme environments. In this work, an environmental simulator with high-speed rotation and gas thermal shock characteristics was developed and tested. High-temperature resistant strain gauges and thermocouples were fixed onto the surface of turbine blades by a flame-sprayed Al2O3 layer. The damage evolution and failure mechanism of TBCs were analysed by the real-time detection of strain damage and temperature field. The results reveal only a little fluctuation in the temperature distribution of the TBC surface (122 °C) under the synergistic effect of high-speed rotation and thermal shock, and the strain at each measuring point is tensile. During thermal cycling tests of the TBCs, the strain at a specific point varied from 0.21% to 0.79%. The final thermal shock life was determined to be 156 cycles, thus proving that the coating enables good thermal shock resistance. The spalled area was mainly distributed from the suction surface to the leading edge, and TBC failure could be attributed to crack initiation and propagation caused by the impact of the high-temperature flame and accumulation of fatigue load. The present work paves the way for coating preparation process optimisation and real service performance evaluation.

Unsteady flow simulations in two-stage turbines of a rocket turbopump to estimate blade structural soundness for fatigue

Abstract This study first aims at detailed investigations of three-dimensional unsteady flow field in the reference and optimized rocket turbine stages by performing time-accurate flow simulations based on Transient Blade Row (TBR) method or Time Transformation (TT) method in a commercial software ANSYS CFX. Although TT method is believed to enable relatively low-cost unsteady flow simulation, detailed comparisons between TT method-based and conventional unsteady flow simulations are made before TT method application to Fluid-Structural Interaction (FSI) problem. This study then makes an attempt to conduct structural analyses of the 1st and 2nd stage turbine blades under the influence of unsteady fluid forces caused by rotor-stator interaction predicted by TT method-based flow simulations. The structural analyses are executed by use of MSC Nastran. In this study, two materials are adopted as blade material. After the Fourier-series decomposition of the calculated unsteady pressure distributions, the unsteady pressure information is mapped onto the FEM (Finite Element Method)-modeled turbine blade surface as exciting aerodynamic loading. The frequency response analyses are then performed to calculate alternating stresses of the blade, from which the maximum magnitudes of alternating stress are obtained so as to discuss the rotor blade fatigue life.

Large-Eddy Simulation of the Boundary Layer Development in a Low-Pressure Turbine Cascade With Passive Flow Control

The boundary layer development on a low-pressure turbine blade surface modified by recessed dimples, U-grooves, and rectangular grooves has been investigated through the large-eddy simulations. The simulations are performed at a Reynolds number of 50,000 (based on the inlet velocity and axial chord length) and extremely low freestream turbulence conditions. The characteristic parameters of the boundary layer are used to estimate the development of the boundary layer, and spectral analysis has also been performed to identify the dominant frequency of shedding vortices. The results of simulations indicate that three surface modifications all reduce the profile losses by restraining the separation bubble size. However, the grooves and dimples show different mechanisms in inhibiting laminar separation. Grooves tend to promote the formation of spanwise vortices, which is more difficult to break into turbulence. A high-speed shedding vortex is induced by the particular 3D structure of dimple, and its shedding frequency is nearly twice the Kelvin–Helmholtz (K-H) instability frequency. The interaction between the shedding vortices and the K-H vortices promotes the breakdown process of the spanwise vortices, which leads to an earlier transition of the boundary layer at a low disturbance level. The current study reveals the different mechanisms of dimples and grooves and shows the great potential of dimples for flow control in low-pressure turbines. Besides, the flow structures inside the dimples with adverse pressure gradients are also explored.

Study on the Modeling Method and Influencing Parameters of Sandblasting Process for Blade Grinding

Grinding the surface of wind turbine blades is one of the key production processes before its service. In order to solve the problem of high labor cost and low precision in manual grinding wheel grinding of wind turbine blades, the sandblasting process for blade grinding is proposed. The best parameters of sandblasting process applied to wind turbine blades are investigated by simulation. In this study, the simulation model of sandblasting process is established, and the fluid analysis of blades’ grinding using sandblasting process is carried out with the variables of blasting pressure, abrasive diameter, and blast distance. Simulation results show that the best parameters are 0.7 MPa for blasting pressure, 500 mm for spraying distance, and 0.4 mm for abrasive diameter. Finally, the tensile test is carried out on the samples’ grind by the traditional grinding process and sandblasting process. The results show that the paint surface grind by sandblasting process can bear a higher load. This study proves the feasibility of the sandblasting process in the composite materials’ grinding of wind turbine blades.

Research on surface damage detection of wind turbinebladebased on machine vision

Abstract The research of wind turbine blade surface damage identification is of great significance to reduce the risk of wind turbine operation. Aiming at the limitation of manual inspection based damage detection, this paper takes the wind turbine as the object of identification and detection, takes the advanced machine detection method as the research content. In order to realize the task of identification and detection of turbine blade damage, an image classification system of turbine blade based on convolution neural network is proposed. In this paper, the convolution neural network (CNN) based damage identification system is compared with the support vector machine (SVM) based damage identification system. The experimental results show that the CNN based damage identification system has stronger generalization ability and higher classification accuracy in the case of randomly dividing experimental sample data.

Multiparameter Optimization to Improve the Erosion Resistance of Coating by Finite Element Simulation

Abstract Finite element method (FEM) was used to study the stress peak of stress S11 (radial stress component in X-axis) on the steam turbine blade surface of four typical erosion-resistant coatings (Fe2B, CrN, Cr3C2–NiCr and Al2O3–13%TiO2). The effect of four parameters, such as impact velocity, coating thickness, Young's modulus, and Poisson's ratio on the stress peak of stress S11 was analyzed. Results show that the position of tensile stress peak and compressive stress peak of stress S11 is far away from the impact center point with the increase of impact velocity. When coating thickness is equal to or greater than 10 μm, the magnitude of tensile stress peak of stress S11 on the four coating surfaces does not change with the coating thickness at different impact velocities. When coating thickness is equal to or greater than 2 μm, the magnitude of tensile stress peak of stress S11 of four coatings shows a trend of increasing first and then decreasing with the increase of Young's modulus. Meanwhile, the larger the Poisson's ratio, the smaller the tensile stress peak of stress S11. After optimization, when coating thickness is 2 μm, Poisson's ratio is 0.35 and Young's modulus is 800 GPa, the Fe2B coating has the strongest erosion resistance under the same impact conditions, followed by Cr3C2–NiCr, CrN, and the Al2O3–13%TiO2 coating, Al2O3–13%TiO2 coating has the worst erosion resistance.

Numerical Investigation of Surface Wettability Induced Liquid Water Flow on the Surface of Wind Turbine Blades

Numerical Investigation of Surface Wettability Induced Liquid Water Flow on the Surface of Wind Turbine Blades

Simulation and Experimental Study on the Ultrasonic Micro-Vibration De-Icing Method for Wind Turbine Blades

In cold and humid regions, ice accretion sometimes develops on the blades of wind turbines. Blade icing reduces the power generation of the wind turbine and affects the safe operation of the wind farm. For this paper, ultrasonic micro-vibration was researched as an effective de-icing method to remove ice from the wind turbine blade surface and improve the efficiency of wind turbine power generation. A blade segment with NACA0018 airfoil and the hollow structure at the leading edge was designed. The modal analysis of the blade was simulated by ANSYS, and the de-icing vibration mode was selected. Based on the simulation results, the blade segment sample with PZT patches was machined, and its natural frequencies were measured with an impedance analyzer. A return-flow icing wind tunnel system, and a device used to measure the adhesive strength of ice covering the airfoil blade, were designed and manufactured. The experiments on the adhesive strength of the ice were carried out under the excitation of the ultrasonic vibration. The experimental results show that the adhesive strength of the ice, which was generated under the dynamic flow field condition, was lower than the ice generated by water under the static flow field condition. Under the excitation of the ultrasonic vibration, the adhesive strength of the ice decreased. When the excitation frequency was 21.228 kHz, the adhesive strength was the lowest, which was 0.084 MPa. These research findings lay the theoretical and experimental foundations for researching in-depth the application of the ultrasonic de-icing technology to wind turbines.

Вплив технології виготовлення випаровуємих катодів на якість іонно-плазмових покриттів лопаток турбін

The article considers coatings deposited on turbine blades via plasma vapor deposition (PVD) method with Ni-Cr-Al-Y cathodes obtained using powder metallurgy (PM) and electron beam remelting process (EBMR). The study analyzes the effect of cathodes manufacturing techniques on surface roughness of rotor turbine blades. Task: to examine a microstructure and chemical composition of the considered cathodes; to quantify a droplet phase of a heat-resistant coating of turbine blades subdivided into size-fractions. Methods used optical microscopy, SEM-analysis. Next results were obtained. In the microstructure of two cathodes under study, it is revealed γ-solid solution with intermetallic Ni-Cr-Al and yttrium-based phases. Simultaneously, distribution of the yttrium phase in the PM-cathode more uniform in compare with EBMR-cathode. Metallographic studies showed that yttrium phase in the structure of the PM-cathode is highly-dispersed, with sizes up to 5 microns, and due to structural and dimensional heredity received during cathode hot isostatic pressing compaction. The structure of the cathode obtained using EBMR-process is a series of the conglomerates of intermetallic phases, with more than 50 microns long, which are branched out on volume. The compliance of the chemical composition of the cathodes under study to requirements of the specifications is established. After the coating deposition on turbine blades by a PVD-method with cathodes under study, were not observed any coating delamination, and their thickness corresponded to the specifications. With a distribution analysis of droplet phase on the turbine blade surface were established that coatings with PM-cathode have been characterized by complete absence of a 65 microns droplet phase, and has half less 25…45 microns droplet phase compared with the EBMR-cathode. Conclusions. The coating with PM-cathode has smaller droplet phase on the turbine blade surface and as a result improved their roughness and gas path surface state. The use of PM in the production of the cathodes for protective coatings provides stable performance of installation and provides long-term operation time of cathodes, compared with the EBMR-cathodes.

CFD-Based In-Depth Investigation of the Effects of the Shape and Layout of a Vortex Generator on the Aerodynamic Performance of a Multi-MW Wind Turbine

Thick airfoils are conventionally adopted in the blade root region of a wind turbine to ensure structural safety under extreme conditions, despite the resulting power loss. To prevent this loss, a passive flow control device known as a vortex generator (VG) is installed at the starting point of the stall to control the flow field near the wall of the suction surface. In this study, we used computational fluid dynamics (CFD) to investigate the aerodynamic characteristics induced as a result of the shape and layout of the VG on a multi-MW wind turbine blade. The separated and vortical flow behavior on the suction surface of the wind turbine blade equipped with VGs was captured by the Reynolds-averaged Navier–Stokes (RANS) steady-flow simulation. The parametric sensitivity study of the VG shape parameters such as the chord-wise length, height, and interval of the fair of VGs was conducted using thick DU airfoil on the blade inboard area. Based on these results, the response surface method (RSM) was used to investigate the influence of the design parameters of the VG. Based on the CFD results, the VG design parameters were selected by considering the lift coefficient and vorticity above the trailing edge. The maximum vorticity from the trailing edge of the selected VG and the lift coefficient were 55.7% and 0.42% higher, respectively, than the average. The selected VG design and layout were adopted for a multi-MW wind turbine and reduced stall occurrence in the blade root area, as predicted by the simulation results. The VG improved the aerodynamic performance of the multi-MW wind turbine by 2.8% at the rated wind speed.

Effect of perfluoropolyether and the micro nano structure of ZnO on anti icing performance of fluorinated organic superhydrophobicity coatings on wind turbine blade surface

The ice coating on the blade surface of wind turbine in winter seriously affects the operation safety and power generation efficiency of wind turbine, and anti icing and deicing is an urgent technical problem. In this paper, a super-hydrophobic anti-icing coating was prepared by fluorination modification, and the effect of the addition of perfluoropolyether (PFPE) and ZnO on the performance of the coating was studied. The research results show that the addition of PFPE reduces the surface energy of the coating from 18.12 mJ m−2 at 0% to 13.22 mJ m−2 at 15%. The surface free energy has a linear relationship with the binding force of icing. With the increase of the amount of PFPE, the contact angle of the coating increases, the sliding angle decreases, and the delayed icing performance improves. When the amount of PFPE reaches 15%, the contact angle reaches the highest value of 158°, and the sliding angle is 2°; adding PFPE coating, the freezing delay time can reach 107.1 s. The addition of PFPE can effectively reduce the icing strength, and the icing bonding force of the coating is reduced to 0.59 N at 15%. The addition of a amount of ZnO can greatly change the microstructure of the coating surface, thereby changing its superhydrophobicity. The fluorinated superhydrophobicity coating modified by the addition and removal of ZnO has obvious anti-icing performance. The 6 wt% sample has the best delayed icing energy.

Experimental investigation of the full coverage film cooling effectiveness of a turbine blade with shaped holes

The film cooling effectiveness of two turbine blades at different turbulence intensities (0.62% and 16.00%) and mass flux ratios (2.91%, 5.82%, 8.73% and 11.63%) is studied by using the Pressure-Sensitive Paint (PSP) measurement technique. There are a baseline and an improved turbine blade in current work, and their film cooling hole position distribution is the same. But the hole shape on suction surface and pressure surface is changed from cylindrical hole (baseline) to laid-back fan-shaped hole (improved blade). Both blades have 5 rows of cylindrical holes at the leading edge and 4 rows of cooling-holes on the suction surface and the pressure surface. The experimental results show that the film cooling effectiveness of the improved blade is much better than the baseline. The increase in turbulence intensity will reduce the cooling effectiveness on the surface of turbine blade, but the effect of turbulence intensity becomes weaker with an increase in the mass flux ratio. Compared with the multiple rows of cylindrical holes, the cooling effectiveness of shaped holes is more influenced by the turbulence intensity at low mass flux ratio.

A multi-scale methodology of turbine blade surface recovery based on photometric stereo through fast calibrations

This paper proposed a multi-scale measurement methodology for turbine blade, which is able to evaluate the geometrical features of turbine surface in different scales. A turbine blade measurement system is designed by using LED illuminators in this work. To ensure the efficiency and the accuracy of our system during the scale transition, a fast light source calibration method is introduced with a special designed calibration target, where with only one camera snapshot, the position and the orientation of a LED can be calibrated precisely and simultaneously. A surface reconstruction algorithm via iteration is improved by analyzing the LED radiant intensity distribution. The simulation is carried out with a synthetic hyperboloid structure, where the root mean square error (RMSE) of rebuilding is lower than 1.7 µm, and the mean angular error(MAE) of normal estimation is 0.5°. System calibration is performed by using a USAF 1951 calibration target with 3 different scales with the minimum deviation below 4 µm. Experiments are implemented on the concave and the tenon of a turbine blade from civil aero engine, where the profile, the size of the cooling hole and the roughness are retrieved successfully in different scales, which shows the great potential of the proposed methodology in blade inspection applications.

Colour changing material for the estimation of flue gas radiation on the miniature gas turbine surface

The gas turbine is being used in the applications of the aircraft propulsion system and land-based power generating systems more effectively. The manufacturers should optimise the temperature of the gas turbine engine components to enhance the life span of the components. The present research work concentrates on determining the surface temperature gradient on the fabricated turbine blades using a colour changing paint based on temperature attained on the surface. A calibration database has been created, and the surface temperature has been detected based on the available colour contours on the blade surface using human vision. An image processing algorithm has also been proposed for accurate temperature measurement on the blade surface. The obtained surface temperature using colour changing paint multi-colour change 350-8 has been calibrated with the conventional measurement technique IR thermography for experimental validation. A computational fluid dynamics simulation model of the turbine blade has been simulated to predict the surface temperature of blades using analysis systems fluid dynamics for numerical validation. The experimental and numerical validation results have shown a nominal value of error, which proves that the surface temperature gradient can be easily predicted with the help of temperature indicating paint using the proposed algorithm. The study has been extended further to evaluate the amount of emissive power radiated by the flue gas on the turbine blade surface based on the temperature and the wavelength of the colour obtained for the health monitoring of the blade.