Scale test device for wind power blade flutter research under natural wind

Abstract

The invention provides a scaling test device for wind power blade flutter research under natural wind, which belongs to a wind turbine blade flutter test, and is characterized by comprising a wind turbine scaling model consisting of a wind turbine main body, a control system and a monitoring device, the wind turbine main body comprises a foundation, a tower and blades, the control system is used for controlling the rotating speed of the wind turbine, and the rotating speed of the corresponding wind turbine scaling model under the incoming flow wind speed is obtained according to the similarity criterion to achieve rotating speed adjustment of the wind turbine; the monitoring device is used for monitoring the wind speed of natural wind and performing non-contact monitoring on the flutter state of the scaling blade; the control system comprises a variable pitch device, a yaw device, a servo motor and a controller. The monitoring device comprises an anemograph, a wind direction sensor, a high-speed camera and a six-component balance; the problem that the actual blade flutter change cannot be reflected in the natural wind state can be solved.

Description

Technical Field

[0001] The present invention belongs to the flutter test of wind turbine blades, and more particularly, relates to a scaled test device for studying the flutter of wind power blades under natural wind. Background Art

[0002] Using a scaled model for testing is one of the main methods for studying the flutter of wind power blades. In the existing research on the flutter of scaled blade models, almost all are single blades fixed upright in a wind tunnel for testing. This kind of test has the following problems: First, the pre-twist of the cross-section of the wind power blade is designed according to the relative wind speed. The vertically fixed blade has no rotational motion, only the absolute wind speed of the air flow in the wind tunnel, so the surface flow characteristics are very different from those of the actual blade. Second, the wind tunnel air flow cannot reflect the turbulence and randomness of natural wind.

[0003] Currently, the flutter test device for the scaled model of wind power blades is as Figure 1 shown. The blade root is fixed in the wind tunnel. The air flow velocity in the wind tunnel is monitored by a hot-wire anemometer, and the flutter morphology of the blade is observed by a high-speed camera. The six-component balance measures the blade root reaction force to reflect the flutter time-domain signal, which can be converted into a frequency-domain signal through Fourier transform. The air flow velocity of the blade under this kind of wind tunnel test condition is as Figure 2 shown, with the same magnitude and direction. While the air flow velocity of the blade under natural wind conditions is as Figure 3 shown, which is the resultant wind speed of the oncoming wind speed v0 and the relative wind speed v r generated by rotation, with different magnitudes and directions. It can be seen that the existing test device has the problem that it cannot combine the actual blade flutter changes under the natural wind state due to the above situation. Summary of the Invention

[0004] In view of this, the present invention provides a scaled test device for studying the flutter of wind power blades under natural wind, which can solve the problem of not being able to combine the actual blade flutter changes under the natural wind state.

[0005] The present invention is implemented as follows:

[0006] The present invention provides a scaled test device for studying the flutter of wind power blades under natural wind, which includes a scaled wind turbine model composed of a wind turbine main body, a control system, and a monitoring device. The wind turbine main body includes a foundation, a tower, and blades. The control system is used to control the rotational speed of the wind turbine, and the rotational speed of the wind turbine is adjusted by obtaining the rotational speed of the corresponding scaled wind turbine model under the oncoming wind speed according to the similarity criterion. The monitoring device is used to monitor the natural wind speed and perform non-contact monitoring of the flutter morphology of the scaled blades.

[0007] Based on the above technical solution, the scaled test device for studying the flutter of wind power blades under natural wind of the present invention can also be improved as follows:

[0008] Among them, the blade adopts a scaled-down model of the IEA 15MW wind turbine blade; to construct a scaled-down model similar to the response of the original blade, the following aerodynamic scaling criteria are constructed. The basic similarity ratios for the aerodynamic similarity of wind turbine blades include the Strouhal number (St), Froude number (Fr), Euler number (Eu), and Reynolds number (Re), and there are the following rules:

[0009] (1) If the body force is only gravity, Fr and Eu can be equivalent;

[0010] (2) Fr and Re cannot be satisfied simultaneously;

[0011] (3) When Re is greater than 4×10 5 , self-similarity is satisfied.

[0012] Therefore, the Re number needs to satisfy self-similarity, and

[0013] where:

[0014] λ t = 1 / λ f (2)

[0015] Considering the relative velocity of the wind turbine blade, pre-twist is designed for the airfoils at different spanwise positions to achieve the sectional angle of attack with the optimal lift-to-drag ratio under rated conditions. On the basis of keeping the aerodynamic shape of the blade unchanged, in order to ensure that the blade pitch angle remains unchanged, the following relationship needs to be satisfied:

[0016] λ u = λ l λ ωrot (3)

[0017] where, λ ωrot is the blade speed ratio scale; Equation (1) is the common criterion for blade aerodynamic similarity. There are four variables in the two equations, which is an uncertain system; after introducing Equations (2) and (3), it is transformed into a deterministic system.

[0018] Among them, the control system includes a pitch control device, a yaw control device, a servo motor, and a controller.

[0019] The beneficial effect of adopting the above improvement scheme is that the pitch control device and the yaw control device are controlled by the controller according to the wind speed and wind direction measured by the anemometer and wind direction sensor.

[0020] Furthermore, the monitoring device includes an anemometer, a wind direction sensor, a high-speed camera, and a six-component balance.

[0021] Furthermore, the pitch control device is used to control the blade to achieve the following control effects:

[0022] (1) 3 m / s to 6.98 m / s: The minimum rotor speed. As the wind speed increases, the blade pitch angle gradually decreases to 0°.

[0023] (2) 6.98 m / s to 10.58 m / s: The optimal tip speed ratio. As the wind speed increases, the pitch angle remains 0°, and the rotational speed and torque increase proportionally.

[0024] (3) 10.58 m / s to 25 m / s: The controller adjusts the blade pitch angle to increase, keeping the blade lift constant, and thus maintaining a constant rotational speed.

[0025] (4) Greater than 25 m / s: Braking to ensure the safety of the wind turbine.

[0026] Furthermore, the foundation is buried below the ground surface and serves as the support foundation for the entire device. The foundation is fixedly connected to the bottom of the tower through bolts to ensure the verticality and stability of the tower. The top of the tower is connected to the wind turbine hub through a flange, and blades are installed on the hub. The root of the blade is connected to the hub through bolts, and the pitch control device is arranged inside the hub.

[0027] Furthermore, the servo motor is connected to the transmission shaft inside the tower through a coupling to drive the hub to rotate. The servo motor is connected to the controller through an electric control signal line to receive the rotational speed command.

[0028] Furthermore, the pitch control device drives the rotation of the blade root through an electric actuator; the yaw device meshes with the flange at the top of the tower through a gear set to adjust the horizontal angle of the hub.

[0029] Furthermore, the anemometer is fixedly installed at the top of the tower, and the wind direction sensor is fixedly installed on the side of the tower. The controller is used to receive the real-time data of the anemometer and the wind direction sensor; and send control commands to the servo motor, the pitch control device, and the yaw device through the RS485 bus.

[0030] Furthermore, the six-component balance is embedded between the connection flange of the blade root and the hub, and its surface is in direct contact with the blade root.

[0031] Furthermore, the visual recognition method for non-contact monitoring of the blade flutter morphology by the monitoring device includes the following steps:

[0032] S10: Record a video with a frame rate of 1000 Hz through a high-speed camera and extract the video frame by frame.

[0033] S20: Based on the neural network, identify and record the position of the blade in each frame image, and the time-domain response of the blade displacement can be obtained. If the displacement is too large, it is determined that the blade has fluttered, and record the wind speed and flutter frequency at this time.

[0034] S30: By taking the first and second derivatives of the time-domain response of the blade displacement, the time-domain response curves of the velocity and acceleration can be obtained;

[0035] S40: By performing a Fourier transform on the time-domain response curve of the acceleration, the frequency response of the blade and characteristics such as the natural frequency of the blade can be obtained.

[0036] Compared with the prior art, the beneficial effects of a scaled-down test device for studying the flutter of wind turbine blades under natural wind provided by the present invention are as follows: By adding a pre-twist angle to the aerodynamic shape design of the blade, it is ensured that the airfoil sections at each spanwise position are at the optimal angle of attack under the rated wind speed. In order to ensure the similarity of the aerodynamic characteristics between the scaled-down blade test and the actual blade, the present invention formulates a similarity criterion; placing the test device under natural wind conditions can ensure that the turbulence intensity and randomness of the incoming wind are the same as the actual situation; by monitoring the natural wind speed with an anemometer and based on the aerodynamic similarity criterion proposed in the present invention, the rotational speed of the servo motor corresponding to the natural wind speed is matched through a controller to achieve a natural wind test. The advantages compared with a wind tunnel test are high authenticity and low cost. Description of the Drawings

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments of the present invention. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0038] Figure 1 Schematic diagram of a wind tunnel test device for a scaled-down model of a wind turbine blade in the background art;

[0039] Figure 2 Schematic diagram of the air flow velocity of the blade under wind tunnel test conditions in the background art;

[0040] Figure 3 Schematic diagram of the air flow velocity of the blade under natural wind conditions in the background art;

[0041] Figure 4 Schematic diagram of the structure of a scaled-down test device for studying the flutter of wind turbine blades under natural wind;

[0042] In the drawings, the list of components represented by each reference numeral is as follows:

[0043] 10. Wind turbine main body; 101. Tower; 102. Blade; 11. Pitch control device; 12. Yaw control device; 13. Servo motor; 14. Controller; 15. Anemometer; 16. High-speed camera; 17. Six-component balance. Detailed Embodiments

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention.

[0045] As Figure 4 shown, it is the first embodiment of a scaled-down test device for studying the flutter of a wind turbine blade under natural wind provided by the present invention. In this embodiment, it includes a scaled-down model of a wind turbine composed of a wind turbine main body 10, a control system, and a monitoring device. The wind turbine main body includes a foundation, a tower 101, and blades 102. The control system is used to control the rotational speed of the wind turbine, and the rotational speed of the scaled-down model of the wind turbine corresponding to the incoming flow wind speed is obtained according to the similarity criterion to achieve the adjustment of the rotational speed of the wind turbine; the monitoring device is used to monitor the natural wind speed and perform non-contact monitoring of the flutter morphology of the scaled-down blades.

[0046] Among them, in the above technical solution, the blades use a scaled-down model of IEA 15MW wind turbine blades; to construct a scaled-down model similar to the response of the original blades, the following pneumatic scaling criteria are constructed. The basic similarity ratios of the aerodynamic similarity of wind turbine blades include the Strouhal number (St), the Froude number (Fr), the Euler number (Eu), and the Reynolds number (Re), and there are the following rules:

[0047] (1) If the body force is only gravity, Fr and Eu can be equivalent;

[0048] (2) Fr and Re cannot be satisfied simultaneously;

[0049] (3) When Re is greater than 4×10 5 , self-similarity is satisfied.

[0050] Therefore, the Re number needs to satisfy self-similarity, and

[0051] where

[0052] λ t = 1 / λ f (2)

[0053] Considering the relative velocity of the wind turbine blade, pre-twisting is designed for the airfoils at different spanwise positions to achieve the sectional angle of attack with the optimal lift-drag ratio under the rated condition. On the basis of keeping the aerodynamic shape of the blade unchanged, in order to ensure that the blade pitch angle remains unchanged, the following relationship needs to be satisfied:

[0054] λ u = λ l λ ωrot (3)

[0055] Among them, λ ωrotIt is the blade speed ratio scale. Equation (1) is a common criterion for blade aerodynamic similarity. There are four variables in the two equations, which form an uncertain system. By introducing Equations (2) and (3), it is transformed into a deterministic system. On this basis, the aerodynamic similarity ratio of the wind turbine can be determined, as shown in Table 1; where L is the proportional constant of the length ratio scale.

[0056] Table 1 Aerodynamic Similarity Ratio of Wind Turbine

[0057] Scale Similarity ratio <![CDATA[λ l > 1:L <![CDATA[λ u > 1:1 <![CDATA[λ t > 1:L <![CDATA[λ f > L:1 <![CDATA[λ ωrot > L:1

[0058] Among them, in the above technical solution, the control system includes a pitch device 11, a yaw device 12, a servo motor 13, and a controller 14.

[0059] Furthermore, in the above technical solution, the monitoring device includes an anemometer 15, a wind direction sensor, a high-speed camera 16, and a six-component balance 17.

[0060] Furthermore, in the above technical solution, the pitch device is used to control the blade to achieve the following control effects:

[0061] (1) 3 m / s to 6.98 m / s: The minimum rotor speed. As the wind speed increases, the blade pitch angle gradually decreases to 0°;

[0062] (2) 6.98 m / s to 10.58 m / s: The optimal tip speed ratio. As the wind speed increases, the pitch angle remains 0°, and the speed and torque increase proportionally;

[0063] (3) 10.58 m / s to 25 m / s: The controller adjusts the blade pitch angle to increase, so that the blade lift remains unchanged, and then the speed is kept constant;

[0064] (4) Greater than 25 m / s: Brake to ensure the safety of the wind turbine.

[0065] Furthermore, in the above technical solution, the foundation is buried below the ground surface and serves as the support foundation for the entire device. The foundation is fixedly connected to the bottom of the tower through bolts to ensure the verticality and stability of the tower; the top of the tower is connected to the wind turbine hub through a flange, and blades are installed on the hub; the root of the blade is connected to the hub through bolts, and the pitch device is arranged inside the hub.

[0066] Furthermore, in the above technical solution, the servo motor is connected to the transmission shaft inside the tower through a coupling to drive the hub to rotate. The servo motor is connected to the controller through an electric control signal line to receive the speed command.

[0067] Furthermore, in the above technical solution, the pitch device drives the root of the blade to rotate through an electric actuator; the yaw device meshes with the flange at the top of the tower through a gear set to adjust the horizontal angle of the hub.

[0068] Further, in the above technical solution, the anemometer is fixedly installed at the top of the tower, the wind direction sensor is fixedly installed on the side of the tower, and the controller is used to receive the real-time data of the anemometer and the wind direction sensor; and send control instructions to the servo motor, the pitch device, and the yaw device through the RS485 bus.

[0069] Among them, the control instructions include rotational speed control adjustment instructions, pitch angle control adjustment instructions, and yaw angle control adjustment instructions.

[0070] Among them, further, the anemometer and the wind direction sensor are installed according to the requirements of GB / T35221-2017 (Code for Surface Meteorological Observation).

[0071] Further, in the above technical solution, the six-component balance is embedded between the connecting flange of the blade root and the hub, and its surface is in direct contact with the blade root.

[0072] Through the above settings, it is used to achieve controlling the rotational speed of the wind turbine by the servo motor. The rotational speed of the scaled-down wind turbine model corresponding to the oncoming wind speed is obtained by constructing similarity criteria. Therefore, the rotation of the wind turbine is not a free rotation under the action of natural wind lift, but is rotated by the control of the servo motor, and then simulates the actual blade flutter change under the natural wind state.

[0073] Further, a high-speed camera is used to achieve non-contact monitoring of the flutter morphology of the scaled-down blade. It can make the analysis results of visual recognition be compared and complemented with the six-component balance located at the blade root, so as to ensure the accuracy of the test results.

[0074] Further, in the above technical solution, the visual recognition method for the non-contact monitoring of the blade flutter morphology by the monitoring device includes the following steps:

[0075] S10: Record a video with a frame rate of 1000Hz through a high-speed camera, and extract the video frame by frame;

[0076] Among them, the specific steps of S10 include:

[0077] The first step, through video recording, when the blade is running normally, start the high-speed camera and set the frame rate to 1000Hz to start recording the video. The recording time is determined according to actual needs, and a video of several minutes or even longer can be recorded to cover the movement of the blade under different working conditions.

[0078] The second step: After the video recording is completed, use video processing software (such as Adobe Premiere Pro, FFmpeg, etc.) to extract the video frame by frame. For example, using the FFmpeg command-line tool, extract the video as image files at a rate of 1 frame per second, and the extraction frame rate can be set according to actual needs.

[0079] S20: Identify the positions of the blades in each frame of the image based on a neural network and record them, then the time-domain response of the blade displacement can be obtained. If the displacement is too large, it is determined that the blade undergoes flutter, and record the wind speed and flutter frequency at this time.

[0080] Among them, the specific steps of S20 include:

[0081] The first step is to collect a large amount of image data containing different blade positions and motion states through neural network training. These data should cover images of the blades under different conditions such as normal operation and flutter. Neural network architectures such as convolutional neural networks (CNNs), such as AlexNet, VGGNet, ResNet, etc. are selected. Taking ResNet as an example, it has the characteristic of residual learning, which can effectively solve the problems of gradient disappearance and gradient explosion in deep networks and improve the training effect of the model. Use the collected image data to train the neural network by setting corresponding training parameters such as learning rate and number of iterations. Through training, the neural network can accurately identify the positions of the blades in the images.

[0082] The second step is blade position identification. Input the images extracted frame by frame in step S10 into the trained neural network. Through the calculation and analysis of the neural network, determine the position information of the blades in each frame of the image. Record the position coordinates of the blades in each frame of the image (such as the x and y coordinates in the image coordinate system), and form a sequence of the blade position changing with time according to the time sequence of the frames, that is, the time-domain response of the blade displacement.

[0083] The third step is flutter determination. Set a displacement threshold. When the blade displacement exceeds this threshold, it is determined that the blade undergoes flutter. For example, according to the design parameters of the blade and the displacement range during normal operation, set a displacement threshold, such as a certain proportion of the maximum allowable displacement of the blade. When it is determined that the blade undergoes flutter, record the wind speed and flutter frequency at this time. The wind speed can be measured in real time by an installed anemometer, and the flutter frequency can be obtained by analyzing the time-domain response of the blade displacement.

[0084] S30: Take the first and second derivatives of the time-domain response of the blade displacement to obtain the time-domain response curves of velocity and acceleration.

[0085] Among them, the specific steps of S30 include:

[0086] The first step is data preprocessing. Preprocess the time-domain response data of the blade displacement, such as removing noise and filling in missing data. Filtering algorithms (such as Gaussian filtering, median filtering, etc.) can be used to smooth the data to reduce the influence of noise on the subsequent derivative results.

[0087] Step 2: First-order derivative to obtain velocity. According to numerical calculation methods, perform a first-order derivative on the time-domain response of the blade displacement.

[0088] Preferably, the finite difference method is adopted. For the discrete displacement data sequence x(t), its velocity v(t) at time t can be approximately expressed as where Δt is the time interval. By performing the above calculation on the displacement data sequence, the time-domain response data sequence of velocity is obtained.

[0089] Step 3: Second-order derivative to obtain acceleration. Perform a second-order derivative on the obtained time-domain response data sequence of velocity.

[0090] Preferably, the finite difference method is also adopted. The acceleration a(t) can be approximately expressed as Through calculation, the time-domain response data sequence of acceleration is obtained.

[0091] Step 4: Plot curves based on the time-domain response data sequences of velocity and acceleration.

[0092] Preferably, use data visualization tools (such as Matplotlib, Origin, etc.) to plot the time-domain response curves of velocity and acceleration; when plotting the curves, the abscissa is time, and the ordinates are velocity and acceleration respectively, intuitively showing the changes of blade velocity and acceleration over time.

[0093] S40: Perform a Fourier transform on the time-domain response curve of acceleration to obtain the frequency response of the blade, as well as characteristics such as the natural frequency of the blade.

[0094] Among them, the specific steps of S40 include:

[0095] Step 1: Process the time-domain response curve of acceleration using the Fourier transform algorithm.

[0096] Preferably, for the discrete acceleration time-domain response data sequence a(t), the fast Fourier transform (FFT) algorithm can be used. For example, the fft function provided by the NumPy library in Python can be conveniently used for fast Fourier transform. Through Fourier transform, the acceleration data in the time domain is converted into frequency-domain data, obtaining the spectrum of acceleration.

[0097] Step 2: Frequency response analysis. According to the obtained acceleration spectrum, analyze the frequency response of the blade. The frequency response represents the response of the blade to acceleration at different frequencies. In the spectrum, the amplitude and phase information of different frequency components can be observed, so as to understand the vibration characteristics of the blade at different frequencies.

[0098] Step 3: Natural frequency determination. In the frequency response, find the peak positions in the spectrum. The frequencies corresponding to these peaks are the natural frequencies of the blade.

[0099] Among them, the natural frequency is the vibration characteristic of the blade itself. By determining the natural frequency, it is possible to evaluate whether the blade has resonance, providing an important reference for the design and operation of the blade.

[0100] Furthermore, the analysis results of visual recognition can be compared and complemented with the six-component balance located at the blade root to ensure the accuracy of the results.

[0101] The specific steps are as follows:

[0102] Step 1: Six-component balance data acquisition. According to the six-component balance installed at the blade root, collect the force and moment data that the blade receives during operation in real time, including the forces in the three coordinate axis directions and the moments around the three coordinate axis directions.

[0103] Step 2: Data comparison. Compare the information such as blade displacement, velocity, and acceleration obtained by visual recognition with the time-domain data collected by the six-component balance.

[0104] Preferably, verify the accuracy of the visual recognition results by analyzing the relationship between the blade displacement and the force applied. If there are significant differences between the two sets of data, analyze possible reasons such as measurement errors and model assumptions.

[0105] Step 3: Result complementation. Complement the data of visual recognition and the six-component balance according to the comparison results.

[0106] The following is a specific application example:

[0107] In a laboratory environment, to study the flutter characteristics of a wind turbine blade under natural wind conditions, an experimental system that simulates the natural wind environment and restores the true flutter state of the wind turbine blade needs to be constructed. By introducing the aerodynamic scaling criterion, the wind wheel speed and pitch device are controlled by a servo motor to reproduce the effect of natural wind on the blade on the scaled-down experimental model, so as to carry out blade flutter monitoring research more safely and efficiently and provide a reference for the design and operation of actual wind turbines.

[0108] First, construct a scaled-down model of the wind turbine. Use a servo motor to control the rotation speed of the wind wheel (hub and blades). The wind wheel rotation speed is determined according to the proposed aerodynamic scaling criterion, as shown in Table 1.

[0109] Furthermore, through the application of this model to the simulation test under natural wind conditions, it also includes a pitch system, which can reflect the operating conditions of the actual blade.

[0110] Among them, the pitch control device is installed on the hub and used to connect the blades. It adopts the electric pitch control system of Moog Company. The pitch angle adjustment range is 0° - 90°, the adjustment accuracy is 0.1°, and the maximum adjustment speed can reach 15° / s. It can quickly and accurately change the pitch angle of the blades, and is equipped with a high-precision angle sensor to real-time feedback the pitch angle data.

[0111] Among them, the monitoring device selects the Phantom v211 high-speed camera with a frame rate set at 1000Hz, a resolution of 1280×800, and a pixel size of 12μm×12μm; installs the 81000 type high-precision ultrasonic anemometer of Young Company with a measurement accuracy of ±0.1m / s and a measurement range of 0 - 60m / s; installs the Kistler 9357B type six-component balance at the blade root with a force measurement accuracy of ±0.1%FS and a torque measurement accuracy of ±0.2%FS, which is used to measure the force and torque on the blade.

[0112] After determining the aerodynamic scaling parameters, start assembling the test device:

[0113] Bury the foundation below the ground as the support foundation for the entire device. Fix it to the bottom of the tower through bolts to ensure the verticality and stability of the tower. The top of the tower is connected to the wind turbine hub through a flange, and the blades are installed on the hub; the blade root is connected to the hub through the pitch control device. The servo motor is connected to the transmission shaft inside the tower through a coupling to drive the hub to rotate, and the electric control signal wire is connected to the controller to receive the rotation speed instruction. Install the pitch control device so that the pitch control device can drive the blade root to rotate through the electric actuator. The yaw device is installed by meshing with the flange at the top of the tower through a gear set to adjust the horizontal angle of the hub. The controller is used to receive the real-time data of the anemometer (installed on the top of the tower) and the wind direction sensor (installed on the side of the tower). Send control instructions to the servo motor, pitch control device, and yaw device through the RS485 bus. The anemometer and the wind direction sensor are installed around the test device according to the requirements of GB / T 35221 - 2017 (Code for Surface Meteorological Observation). The six-component balance is embedded between the connection flange of the blade root and the hub, directly contacting the blade root.

[0114] After the device is assembled, start the motor to control the wind turbine rotation speed to simulate the natural wind speed:

[0115] According to the relationship between the wind turbine rotation speed and the wind speed determined by the collected wind speed information combined with the aerodynamic scaling specification formulated in Table 1, start the servo motor to make the wind turbine rotate. Real-time monitor the data of the wind speed sensor. If the wind speed deviation exceeds ±0.1m / s, fine-tune the motor rotation speed through the rotation speed controller with an adjustment step of 10rpm to make the air flow speed generated by the wind turbine stable at the target value.

[0116] During the test, adjust the pitch angle through the pitch control device to simulate the natural wind state:

[0117] Specifically, the data collected by the monitoring device of the pitch device is controlled by the controller to implement the following instructions:

[0118] (1) When the wind speed is in the range of 3 m / s to 6.98 m / s: At this time, the rotor has the minimum speed, which gradually increases with the wind speed, and the blade pitch angle is gradually reduced to 0°;

[0119] (2) When the wind speed is in the range of 6.98 m / s to 10.58 m / s: At this time, it is the optimal tip speed ratio. As the wind speed gradually increases, the pitch angle is maintained at 0°, and the speed and torque increase in proportion;

[0120] (3) When the wind speed is in the range of 10.58 m / s to 25 m / s: At this time, the controller adjusts the blade pitch angle to increase, so that the blade lift remains unchanged, and then the speed is kept constant;

[0121] (4) When the wind speed is greater than 25 m / s: Brake in time to ensure the safety of the wind turbine.

[0122] Furthermore, monitor and collect data on blade flutter;

[0123] The high-speed camera records the blade motion video at a frame rate of 1000 Hz, and the shooting duration is the duration of each working condition plus a 10-second buffer time. After shooting, use the FFmpeg software to extract the video frame by frame and save it as a PNG format image file.

[0124] Input the frame-by-frame images into a pre-trained ResNet-50 neural network model (trained on a dataset containing 20,000 images of different blade positions, with a training accuracy of 98.5%) to identify the blade position and obtain the time-domain response of the blade displacement.

[0125] Perform Gaussian filtering preprocessing on the blade displacement data using a third-order Butterworth low-pass filter (cutoff frequency 100 Hz) to remove noise. Then use the central difference method to perform first-order and second-order derivatives with a time step of 0.001 s to obtain the time-domain response curves of velocity and acceleration.

[0126] Perform a fast Fourier transform (FFT) on the acceleration time-domain response curve, use the Hanning window function to reduce spectral leakage, analyze the frequency response of the blade, and determine the flutter frequency and natural frequency of the blade.

[0127] Synchronously collect six-component balance data with a sampling frequency of 1000 Hz, and transmit the data to the computer through the Ethernet interface for storage.

[0128] Furthermore, process and analyze the data:

[0129] All the collected data are sorted out using the Pandas library in Python, and the curves of blade displacement, velocity, and acceleration varying with time, as well as the frequency response curve, are plotted using the Matplotlib library. The time accuracy of the abscissa of the curve is 0.001 s, the displacement accuracy of the ordinate is 0.1 mm, the velocity accuracy is 0.1 m / s, and the acceleration accuracy is 0.1 m / s 2 , and the frequency accuracy is 0.01 Hz.

[0130] Analyze the flutter characteristics of the blade under different wind speeds and pitch angles, compare the visual recognition results with the six-component balance data, and use the mean square error (MSE) and relative error (RE) to evaluate the accuracy and reliability of the experimental results.

[0131] Summarize the laws according to the experimental data, establish a mathematical model between the blade flutter characteristics and the wind speed and pitch angle, and provide a basis for the design of wind turbine blades and flutter prevention.

[0132] Specifically, the principle of the present invention is as follows: Design a scaled test device for studying the flutter of wind turbine blades under natural wind, which can ensure the aerodynamic similarity with the actual wind turbine blades. By matching the servo motor speed with the wind speed, it is different from simply changing the tip speed ratio using the servo motor. By formulating the aerodynamic similarity criterion as an exact system, after the length similarity ratio is determined, other similarity scales can be determined. Equation (1) is the common criterion for blade aerodynamic similarity, and there are four variables in the two equations, which is an uncertain system. After introducing Equations (2) and (3) in the present invention, it is transformed into a determined system. The rotation speed of the wind turbine is controlled by the servo motor. The rotation speed of the scaled model of the wind turbine corresponding to the oncoming wind speed is obtained from the similarity criterion. Therefore, the rotation of the wind turbine is not a free rotation under the action of natural wind lift, but a rotation controlled by the servo motor. Non-contact monitoring of the flutter morphology of the scaled blade is carried out based on a high-speed camera. The analysis results of visual recognition can be compared and complemented with the six-component balance located at the blade root to ensure the accuracy of the results.

Claims

1. A scaled test device for the study of wind turbine blade flutter under natural wind, characterized in that, It includes a scaled - down model of a wind turbine consisting of a wind turbine main body, a control system, and a monitoring device. The wind turbine main body includes a foundation, a tower, and blades. The control system is used to control the rotational speed of the wind turbine, and the rotational speed of the scaled - down wind turbine model corresponding to the incoming flow wind speed is obtained according to the similarity criterion to achieve the regulation of the wind turbine's rotational speed. The monitoring device is used to monitor the natural wind speed and perform non - contact monitoring of the flutter morphology of the scaled - down blades.

2. The scaled test device for studying the flutter of a wind turbine blade under natural wind according to claim 1, wherein, The blades adopt a scaled - down model of IEA15MW wind turbine blades. To construct a scaled - down model with a response similar to that of the original blades, the following aerodynamic scaling criteria are constructed. The basic similarity ratios for the aerodynamic similarity of wind turbine blades include the Strouhal number (St), the Froude number (Fr), the Euler number (Eu), and the Reynolds number (Re). The following rules exist: (1) If the body force is only gravity, Fr and Eu can be equivalent. (2) Fr and Re cannot be satisfied simultaneously. (3) When Re is greater than 4×10 5 , self-similarity is satisfied. Therefore, the Re number needs to satisfy self-similarity, and Where: λ t = 1 / λ f ; λ u = λ l λ ωrot ; where λ ωrot is the blade speed ratio scale; is a common criterion for blade aerodynamic similarity. There are four variables in the two equations, which is an uncertain system. By introducing the formula λ t = 1 / λ f and λ u = λ l λ ωrot it is transformed into a deterministic system.

3. A scaled test device for studying the flutter of a wind turbine blade under natural wind according to claim 2, characterized in that, Considering the relative velocity of the wind turbine blades, pre - twist is designed for the airfoils at different spanwise positions to achieve the sectional angle of attack with the optimal lift - to - drag ratio under rated conditions. On the basis of keeping the aerodynamic shape of the blades unchanged, in order to ensure that the blade pitch angle remains unchanged, the following relationship needs to be satisfied:

4. A scaled test device for studying the flutter of a wind turbine blade under natural wind according to claim 3, characterized in that, The control system includes a pitch - control device, a yaw - control device, a servo motor, and a controller. The monitoring device includes an anemometer, a wind - direction sensor, a high - speed camera, and a six - component balance. The pitch - control device is used to control the blades to achieve the following control effects: (1) 3m / s - 6.98m / s: The minimum rotor rotational speed. As the wind speed increases, the blade pitch angle gradually decreases to 0°. (2) 6.98m / s - 10.58m / s: The optimal tip - speed ratio. As the wind speed increases, the pitch angle remains 0°, and the rotational speed and torque increase proportionally. (3) 10.58m / s - 25m / s: The controller adjusts the blade pitch angle to increase, so that the blade lift remains unchanged, and then the rotational speed is kept constant.

5. A scaled test device for the study of the flutter of a wind turbine blade under natural wind, as described in claim 4, characterized in that (4) Greater than 25m / s: Braking to ensure the safety of the wind turbine.

6. A scaled test device for the study of wind turbine blade flutter under natural wind according to claim 5, characterized in that, The foundation is buried below the ground surface and serves as the support foundation for the entire device. The foundation is fixedly connected to the bottom of the tower through bolts to ensure the verticality and stability of the tower. The top of the tower is connected to the wind turbine hub through a flange, and the blades are installed on the hub. The root of the blade is connected to the hub through bolts, and the pitch - control device is arranged inside the hub.

7. A scaled test device for studying the flutter of a wind turbine blade under natural wind according to claim 6, characterized in that The servo motor is connected to the transmission shaft inside the tower through a coupling, drives the hub to rotate, and the servo motor is connected to the controller through an electric control signal line to receive the rotational speed command.

8. A scaled test device for the study of wind turbine blade flutter under natural wind according to claim 7, characterized in that The pitch - control device drives the root of the blade to rotate through an electric actuator. The yaw - control device meshes with the flange at the top of the tower through a gear set to adjust the horizontal angle of the hub.

9. The scaled test device for studying the flutter of wind turbine blades under natural wind according to claim 8, characterized in that, The anemometer is fixedly installed at the top of the tower, and the wind - direction sensor is fixedly installed on the side of the tower.

10. A scaled test device for studying the flutter of a wind turbine blade under natural wind according to claim 9, characterized in that, The controller is used to receive the real - time data from the anemometer and the wind - direction sensor, and send control commands to the servo motor, the pitch - control device, and the yaw - control device through the RS485 bus. The six - component balance is embedded between the connecting flange of the blade root and the hub, and its surface is in direct contact with the blade root.

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