Testing Of Wind Turbine Blades Research Articles

Development of the test method for wind turbine blade subcomponent under combined bending and torsion loads

The conventional full-scale wind turbine blade testing method is unable to study the detailed structural response of blades' key subcomponents under complex loads. Therefore, developing an efficient and reliable blade subcomponent testing method is of great significance for investigating the structural characteristics of blades. This paper develops an innovative blade subcomponent test method framework, which is capable of studying the structural response under combined bending and torsion load conditions. A high-fidelity finite element model corresponding to the framework that considers nonlinear factors is established. This study further investigated the influence of boundary conditions on the results. The results showed that the test method proposed in this paper is reasonable, and the experiment based on this method is successfully conducted. The contact nonlinearity and size effects will affect the accuracy of the test results, which can be avoided by adjusting the size of the clamp.

Design Method of Full-scale Fatigue Test Load for Wind Turbine Blade

The blade is one of the key components of a wind turbine, and the alternating fatigue load is the main factor leading to the fatigue failure of wind turbine blades. The accuracy of load determines the accuracy of the wind turbine blade test. Based on the equivalent torque time history data from the wind load acting on the blade root, the load of the two-dimensional matrix is obtained by using data compression technology and a rain flow counting algorithm. According to the capture matrix of load data, the frequency of various design loading cases and the distribution of wind speed, the symmetrical load spectrum is calculated and compiled. The fatigue load of a wind turbine blade is calculated for a certain type of 2MW blade, which lays a foundation for the design and test of a wind turbine blade fatigue loading system.

Research on infrared nondestructive testing and thermal effect analysis of small wind turbine blades under natural excitation

In recent years, with the increase of wind power generation and the rapid growth of the number of wind turbines installed, the safety monitoring of wind turbine blades has also attracted wide attention. To further study the thermal effect of wind turbine damaged blades under natural excitation in summer in northern China, based on the outdoor infrared non-destructive testing of wind turbine blades, a numerical simulation of wind turbine blades with wear damage is carried out by using the fluid solid heat transfer theory in COMSOL multi-physical field coupling software. The best detection light condition is obtained, in which the detection effect of wear damage is the best when the light intensity reaches 1000 W.m−2 or above at noon. The simulation results are basically in agreement with the experimental results. And compared with the previous physical modeling method using natural convection heat transfer coefficient to replace wind speed, the physical modeling method considering wind speed and air humidity is more consistent with the experimental results, the maximum error value was decreased by 7.46 %, which verifies the rationality of the model and the feasibility of the method. In addition, the blade works in the natural environment for a long time, the thermal stress will have a significant impact on its fatigue strength, so on the basis of this model, the coupling analysis, and then analyze the change of thermal stress in different wind speed. With the increase of wind speed, the temperature on the blade surface gradually decreases and the wind pressure gradually increases. Because the influence of temperature on the stress is greater than that of wind pressure, the stress also shows a gradual downward trend.

A morphological filtering-based strain data processing method for biaxial fatigue testing of wind turbine blades

Biaxial fatigue testing is an effective way to verify the performance of large wind turbine blades. The test process will generate a large amount of transient strain data, which needs to be peak detection to control the loading system and provided it to third-party organizations for type certification. Peak detection is challenging due to the long test cycle and severe signal noise pollution. The objective of this article is to propose a strain data processing method based on morphological filtering. It is found that morphological filtering + three-point smoothing has a better filtering effect. In addition, a peak detection algorithm is designed and proved its effectiveness. In order to validate the proposed method, a principle prototype of biaxial fatigue testing is built for testing. The results show that the method can not only effectively filter out noise, but also accurately and quickly detect the strain peaks, improve the efficiency of damage calculation and effectively control the test process. The method can also be used in the practical engineering field to process strain data generated during fatigue testing of wind turbine blades and improve overall testing efficiency.

Experimental demonstration of strain-based damage method for optimized fatigue testing of wind turbine blades

A method for optimized testing of wind turbine blades under cyclic loading is experimentally demonstrated in this paper. The method uses continuous linear optimization to find the best combination of different uniaxial and multiaxial test blocks to achieve material-based damage targets across the blade and minimize test time. By applying the method on a real commercial wind turbine blade and comparing it with a standard fatigue test performed on a blade of the same type, the present work shows that improved fatigue tests can be obtained in terms of both accuracy and total test time.

Reliability Analysis of CFRP-Packaged FBG Sensors Using FMEA and FTA Techniques

Carbon fiber-reinforced plastics (CFRP)-packaged fiber Bragg grating (FBG) sensors are widely used in full-scale structural testing of wind turbine blades (WTBs). However, the specific process to make CFRP-packaged FBG sensors, such as packaging, bonding, welding, etc., are mainly manually operated, and no unified standard or rule has been formed yet. Non-standard specific processes, coupled with complex stress distribution, unstable working environments, etc., result in the CFRP-packaged FBG sensors having various failures with time, resulting in inaccurate measurements. Thus, the need to carry out related failure analysis is urgent. This paper therefore performed a reliability analysis for CFRP-packaged FBG sensors using failure mode and effects analysis (FMEA) and fault tree analysis (FTA) techniques. The results provide an important basis towards analyzing performance degradation and functional failures for CFRP-packaged FBG sensors.

Optimized method for multi-axial fatigue testing of wind turbine blades

An optimized method for testing wind turbine blades under fatigue is suggested. With this method, material-based damage targets along the blade are reached by applying an optimal combination of different uni- and multi-axial test blocks. The combination of test blocks is found using continuous linear optimization. Aeroelastic simulations are carried out to estimate both target and test strain-based damage in the blade. By applying the proposed method to a commercial wind turbine blade, the presented analysis illustrates that improved fatigue tests compared to current standard fatigue tests can be obtained in terms of both accuracy and total test time.

Improving accuracy of dual-axial resonance fatigue testing for wind turbine blades by using predicted equivalent test loads caused by combined loading

The dual-axial resonance fatigue test provides for accurate and efficient testing of wind turbine blades through optimizations. However, the existing dual-axial test optimization does not yield an accurate test design because it compares the test loads that correspond to the mode shapes with the target loads that are aligned to the local chord axes. Therefore, this paper proposes equivalent applied loads to predict the flatwise and edgewise test loads by transferring the mode shapes to the local chord axes and using the linear damage accumulation rule. The application of the equivalent applied loads helps the dual-axial test optimization yield satisfactory test schemes without much additional computing time.

PSO-BP Neural Network-Based Strain Prediction of Wind Turbine Blades

The full-scale static testing of wind turbine blades is an effective means to verify the accuracy and rationality of the blade design, and it is an indispensable part in the blade certification process. In the full-scale static experiments, the strain of the wind turbine blade is related to the applied loads, loading positions, stiffness, deflection, and other factors. At present, researches focus on the analysis of blade failure causes, blade load-bearing capacity, and parameter measurement methods in addition to the correlation analysis between the strain and the applied loads primarily. However, they neglect the loading positions and blade displacements. The correlation among the strain and applied loads, loading positions, displacements, etc. is nonlinear; besides that, the number of design variables is numerous, and thus the calculation and prediction of the blade strain are quite complicated and difficult using traditional numerical methods. Moreover, in full-scale static testing, the number of measuring points and strain gauges are limited, so the test data have insufficient significance to the calibration of the blade design. This paper has performed a study on the new strain prediction method by introducing intelligent algorithms. Back propagation neural network (BPNN) improved by Particle Swarm Optimization (PSO) has significant advantages in dealing with non-linear fitting and multi-input parameters. Models based on BPNN improved by PSO (PSO-BPNN) have better robustness and accuracy. Based on the advantages of the neural network in dealing with complex problems, a strain-predictive PSO-BPNN model for full-scale static experiment of a certain wind turbine blade was established. In addition, the strain values for the unmeasured points were predicted. The accuracy of the PSO-BPNN prediction model was verified by comparing with the BPNN model and the simulation test. Both the applicability and usability of strain-predictive neural network models were verified by comparing the prediction results with simulation outcomes. The comparison results show that PSO-BPNN can be utilized to predict the strain of unmeasured points of wind turbine blades during static testing, and this provides more data for characteristic structural parameters calculation.

GA-BP Neural Network-Based Strain Prediction in Full-Scale Static Testing of Wind Turbine Blades

This paper proposes a strain prediction method for wind turbine blades using genetic algorithm back propagation neural networks (GA-BPNNs) with applied loads, loading positions, and displacement as inputs, and the study can be used to provide more data for the wind turbine blades’ health assessment and life prediction. Among all parameters to be tested in full-scale static testing of wind turbine blades, strain is very important. The correlation between the blade strain and the applied loads, loading position, displacement, etc., is non-linear, and the number of input variables is too much, thus the calculation and prediction of the blade strain are very complex and difficult. Moreover, the number of measuring points on the blade is limited, so the full-scale blade static test cannot usually provide enough data and information for the improvement of the blade design. As a result of these concerns, this paper studies strain prediction methods for full-scale blade static testing by introducing GA-BPNN. The accuracy and usability of the GA-BPNN prediction model was verified by the comparison with BPNN model and the FEA results. The results show that BPNN can be effectively used to predict the strain of unmeasured points of wind turbine blades.

Measurement theory of test bending moments for resonance-type fatigue testing of a full-scale wind turbine blade

To date, the predominant number of accidents in wind farms has been due to blade failure; a failure rate of 1:184 per year. To prevent this frequent failure, the fatigue life of a wind turbine blade should be evaluated accurately. Fatigue testing of a wind turbine blade larger than several tens of meters in length exploits resonance that causes nonsymmetrical bending of the blade. However, a conventional approach for measuring test bending moments has brought about large deviations between the measured results, with the maximum deviation generally being between 10% and 15% as a rule of thumb. This study developed a measurement theory of test bending moments for resonance-type fatigue testing of a wind turbine blade. The theory can handle biaxial test bending moments that occur during single-axial fatigue testing, reducing the deviations between the measured results by about 1/5 for the flapwise fatigue test and by about 4/7 for the lead-lag fatigue test of a 3 MW wind turbine blade 59.5 m in length. This study makes a significant step forward in alleviating blade failure in wind farms by the accurate evaluation of a blade’s fatigue life in design.

Selecting and testing of wind turbine blades of the local-wood growing fastly on local wind characteristics

The total potential of wind energy in Indonesia reaches 144 GW. This wind energy potential is dominated by small wind speeds ranging from 4-6 m / s and about 113 GW. This is the reason why the development of small-scale wind powerplant is more feasible to be developed in Indonesia. The characteristics of local wind and geographical conditions of Indonesia which is an archipelagic country are fundamental in designing wind power and utilizing of local materials. This study aims to get local fast-growing wood of wind turbines blades in Indonesia, which has the best physical and mechanical properties of wood, and is tested computationally on certain airfoils and shows a uniform distribution of stress. The types of wood are tested in this study were Sengon (Albizia chinensis), Jabon (Antocephalus cadamba), and Balsa (Ochroma Rowlee grandiflorum). The test covers the basic properties of the wood, physical and mechanical properties. The test results showed that Jabon have density 0.34 was the best compared to Sengon (0.24) and balsa (0.18). The best dimensional stability (T/R Ratios) are Jabon (1.97), sengon (2.19) and balsa (2.84), respectively. With the highest density result and the lowest dimensional stability value, mechanical testing of Jabon wood shows the best mechanical properties. The simulation result using Q-Blade software was obtained airfoil NACA 4415 most suitable for local wind characteristics, and got the low value of stress and distribution color uniformly on each wood.

Refinement of defect detection in the contact and non-contact ultrasonic non-destructive testing of wind turbine blade using guided waves

The guided waves are widely used for the inspection of many composite structures as they can travel up to long distance along the thickness of the structure. Most of the times, the experimental investigations standalone is not able to locate and size the damages or defects due to dispersive, superimposed and scattered guided wave modes. Hence signal refinement of ultrasonic guided wave signals is required for identifying and characterizing the defects. In this work, disbond type defects presented on different locations of the segment of the wind turbine blade are estimated by applying the signal refinement techniques after experimental analysis. The experiment was carried out on a 1005 x 870 mm segment of wind turbine blade manufactured using a composite glass fiber reinforced plastic material. Two defects on the trailing edge (with diameter 15 and 25 mm) and three defects on the main spar (with diameters 25, 51 and 81 mm) of the WTB segment were investigated. The combination of macro fiber composite transducer, contact type and air-coupled transducers were used to transmit and receive the ultrasonic guided waves. The signal processing techniques are applied to the experimental signals for the estimation and characterization of defects.

Research on Automatic Positioning System of Ultrasonic Testing of Wind Turbine Blade Flaws

Ultrasonic testing technology has been used essentially in non-destructive testing of wind turbine blades. However, it is fact that the ultrasonic flaw detection method has inefficiently employed in recent years. This is because the testing result will illustrate a small deviation due to the artificial, environmental and technical factors. Therefore, it is an urgent technical demand for engineers to test the various flaws efficiently and quickly. An automatic positioning system has been designed in this paper to record the moving coordinates and the target distance in real time. Simultaneously, it could launch and acquire the sonic wave automatically. The ADNS-3080 optoelectronic chip is manufactured by Agilent Technologies Inc, which is also utilized in the system. With the combination of the chip, the power conversion module and the USB transmission module, the collected data can be transmitted from the upper monitor to the hardware that could process and control the data through software programming. An experiment has been designed to prove the reliability of automotive positioning system. The result has been validated by comparing the result collected form LABVIEW and actual plots on Perspex plane, it concludes that the system possesses high accuracy and magnificent meanings in practical engineering.

Similitude analysis of thin-walled composite I-beams for subcomponent testing of wind turbine blades

In this study, the I-beam structure of a utility-scale blade is used as the basis for the design of a small-scale subcomponent emulating the same type of structural element of a utility-scale wind turbine blade. Governing equations for the bending of a shear deformable thin-walled composite I-beam are considered. Similitude theory is applied to derive the corresponding scaling laws. Accuracy of the derived scaling laws in predicting the strain and displacement fields of the full-scale I-beam is considered as a design criterion for small-scale I-beams. Both complete and partial similarity cases are discussed. A novel approach is proposed to design partially similar scaled I-beams with totally different layups from those of the full-scale I-beam. Using the proposed technique, scaled-down composite I-beams are designed that predict the strain and displacement fields of their full-scale parent I-beam with very good accuracy.

Signal processing methods to improve the Signal-to-noise ratio (SNR) in ultrasonic non-destructive testing of wind turbine blade

Ultrasonic non-destructive testing (NDT) methods are being used quite effectively nowadays, but the multilayered structure of composite materials results in the serious problem in the detection of defects/flaws. The resulting ultrasonic signal is often noisy and denoising of this signal is necessary in order to extract useful information so that faults can be detected, located and sized. Currently, there is a high demand for automatic ultrasonic signal processing techniques to not only remove the need for manual flaw detection and assessment, but also increase the accuracy, reliability and repeatability of the non-destructive evaluation. There are various signal processing techniques which can be used in ultrasonic measurements and selection of appropriate method is one of the major key factors in the field of ultrasonic testing of composite materials. In the presented work, the sample of wind turbine blade (WTB) manufactured using glass fiber reinforced plastic (GFRP) was investigated using ultrasonic NDT in order to estimate the artificially made disbond type defects of 15 mm and 25 mm diameter on the trailing edge. The transmitting and receiving transducers were fixed on movable panel at distance of 50 mm and guided waves (GW) were received at each one millimeter step along the scanning distance of 500 mm. The measurement is performed using low-frequency (LF) ultrasonic system which was developed by Ultrasound Institute of Kaunas University of Technology. Various signal processing techniques were applied to overcome the structural noise and/or extract the information about the defects. The three most promising signal processing techniques: cross-correlation methods, wavelet transform (WT) and Hilbert-Huang (HHT) transform were discussed and compared in the process of defects estimation.

A novel method of strain - bending moment calibration for blade testing

A new method of interpreting strain data in full scale static and fatigue tests has been implemented as part of the Offshore Renewable Energy Catapult's ongoing development of biaxial fatigue testing of wind turbine blades. During bi-axial fatigue tests, it is necessary to be able to distinguish strains arising from the flapwise motion of the blade from strains arising from the edgewise motion. The method exploits the beam-like structure of blades and is derived using the equations of beam theory. It offers several advantages over the current state of the art method of calibrating strain gauges.

Large-area photogrammetry based testing of wind turbine blades

An optically based sensing system that can measure the displacement and strain over essentially the entire area of a utility-scale blade leads to a measurement system that can significantly reduce the time and cost associated with traditional instrumentation. This paper evaluates the performance of conventional three dimensional digital image correlation (3D DIC) and three dimensional point tracking (3DPT) approaches over the surface of wind turbine blades and proposes a multi-camera measurement system using dynamic spatial data stitching. The potential advantages for the proposed approach include: (1) full-field measurement distributed over a very large area, (2) the elimination of time-consuming wiring and expensive sensors, and (3) the need for large-channel data acquisition systems. There are several challenges associated with extending the capability of a standard 3D DIC system to measure entire surface of utility scale blades to extract distributed strain, deflection, and modal parameters. This paper only tries to address some of the difficulties including: (1) assessing the accuracy of the 3D DIC system to measure full-field distributed strain and displacement over the large area, (2) understanding the geometrical constraints associated with a wind turbine testing facility (e.g. lighting, working distance, and speckle pattern size), (3) evaluating the performance of the dynamic stitching method to combine two different fields of view by extracting modal parameters from aligned point clouds, and (4) determining the feasibility of employing an output-only system identification to estimate modal parameters of a utility scale wind turbine blade from optically measured data. Within the current work, the results of an optical measurement (one stereo-vision system) performed on a large area over a 50-m utility-scale blade subjected to quasi-static and cyclic loading are presented. The blade certification and testing is typically performed using International Electro-Technical Commission standard (IEC 61400-23). For static tests, the blade is pulled in either flap-wise or edge-wise directions to measure deflection or distributed strain at a few limited locations of a large-sized blade. Additionally, the paper explores the error associated with using a multi-camera system (two stereo-vision systems) in measuring 3D displacement and extracting structural dynamic parameters on a mock set up emulating a utility-scale wind turbine blade. The results obtained in this paper reveal that the multi-camera measurement system has the potential to identify the dynamic characteristics of a very large structure.

Initiation of trailing edge failure in full-scale wind turbine blade test

The reliability and accuracy of a numerical shell model simulation and its predictive capabilities with existing failure criteria are compared to experiments of a 34m long blade tested to ultimate failure. Strengths and weaknesses of in-plane failure criteria are highlighted and the geometrical non-linear buckling effect of the trailing edge under combined loading, and how it affects the ultimate strength of a blade in a trailing-edge failure dominated load direction were investigated. The study details the interaction between trailing edge buckling on damage onset and sandwich panel failure. The numerically applied fracture mechanics approaches showed good agreement with the experimental results.

Investigation of Wind Turbine Blades with Tubercles

This paper describes the testing of wind turbine blades with tubercles in two different ways: outdoor testing and flow visualization. In the outdoor testing, the tubercle pitch was varied for turbine blade lengths of 30 cm, 40 cm, and 50 cm. The pitch-to-length ratio of approximately 1/10 to 1/16 produced the most power output. In flow visualization, both tubercle pitch and amplitude were varied. Vortices created behind the tubercles were shown to increase lift by minimizing flow separation.