Test system and test method for verifying hybrid model test method of floating wind turbine

Abstract

A test system and test method for verifying a floating wind turbine hybrid model experiment method, comprising a wind load prediction module and a motion simulator for simulating a surge, the motion simulator being provided with a motion catcher for capturing motion parameters of the motion simulator, the motion catcher being electrically connected with a data collector for receiving the motion parameters collected by the motion catcher; the data collector being electrically connected with the wind load prediction module, the wind load prediction module being provided with a wind condition simulation software for converting real-time data of the data collector; the wind load prediction module being electrically connected with a rotor thrust executor for receiving data of the wind condition simulation software; compared with the prior art, the prediction effect of the wind load prediction module of the floating wind turbine hybrid model experiment method can provide reasonable and accurate rotor thrust by comparing the output data of the wind load prediction module with the measured data of the load sensor.

Description

Technical Field

[0001] This invention relates to the field of offshore wind power generation technology, and specifically to a test system and test method for verifying the experimental method of a hybrid model of a floating wind turbine. Background Technology

[0002] Unlike traditional fixed offshore wind turbines, "floating wind turbines" replace fixed foundations with floating foundations, allowing the turbine to "float" on the water surface. Floating wind turbines are actually complex coupled dynamic systems. Numerical solution tools have made various assumptions and simplifications in their development, making it impossible to fully simulate the dynamics of floating wind turbines in complex environments.

[0003] Numerical calculation results for floating wind turbines can only be used as a reference in the design phase. The validity and reliability of the calculation results are difficult to guarantee, and they cannot be directly applied to engineering as reliable results. Therefore, model tests are essential in the design process and for verification purposes.

[0004] In experimental studies of floating wind turbine models, there is a lack of implementation methods in the laboratory that can overcome the scale conflict between the Froude and Reynolds scales. Real-time hybrid testing is the most feasible method to overcome the scale conflict.

[0005] Hybrid model experiments for floating wind turbines refer to a method of dividing the physical system under study into at least two substructures: a physical substructure tested experimentally at the model scale and a numerical substructure simulated by a computer. These two parts interact in real time through a network of sensors and actuators.

[0006] Hybrid model experiments on floating wind turbines are described in the following literature: D. Olinger, E. DeStefano, E. Murphy, K. Naqvi, and G. Tryggvason, "Scale-model experiments on floating windturbine platforms," ​​in 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, 2012, p. 375. This study investigated the dynamic response of floating wind turbine generators through model experiments. A 100:1 scale model was placed in a water tank, and the responses of the tension leg platform (TLP) and Spar buoy model were studied using a wireless data acquisition system, employing accelerometers, inclinometers, and video measurements.

[0007] Chinese Patent No. CN113654756A discloses an active real-time hybrid model test method for offshore floating wind turbines, including the following steps: establishing a state-space model of the time-domain motion of the floating wind turbine foundation; establishing a state-space model of the anchor chain unit; based on the aforementioned two state-space models, establishing a response state-space model of the coupled motion of the floating wind turbine foundation; establishing the motion control equations of the actuators describing the transformation relationship between the motion state of the floating wind turbine foundation and the motion of a multi-degree-of-freedom robot; using a multi-degree-of-freedom robot to track the motion at the cross-section of the wind turbine tower base in real time; designing a contoured wind turbine model; conducting wind tunnel tests, measuring the load on the contoured wind turbine model and inputting it into the response state-space model; real-time measurement, real-time tracking, and real-time iteration.

[0008] The two experimental methods mentioned above require the establishment of corresponding scale models for testing, which results in high costs in actual use and high accuracy requirements for the scale models, which is time-consuming and labor-intensive. At the same time, the prediction effect of the existing wind load prediction module is difficult to estimate, and the prediction accuracy of the wind load prediction module cannot be verified. Summary of the Invention

[0009] The present invention aims to overcome the deficiencies in the prior art and provide a test system and test method that is cost-effective, reliable, easy to operate, and simple in structure for verifying experimental methods of floating wind turbine hybrid models.

[0010] To achieve the above-mentioned objectives, the present invention adopts the following technical solution: a test system for verifying the experimental method of a hybrid floating wind turbine, comprising a wind load prediction module and a motion simulator for simulating surges. The motion simulator is equipped with a motion capture device for capturing motion parameters of the motion simulator, and the motion capture device is electrically connected to a data acquisition device for receiving the motion parameters collected by the motion capture device. The data acquisition device is electrically connected to the wind load prediction module, and the wind load prediction module is equipped with wind condition simulation software for converting real-time data from the data acquisition device. The wind load prediction module is electrically connected to a rotor thrust actuator for receiving data from the wind condition simulation software, and the rotor thrust actuator is equipped with a load sensor for measuring rotor thrust.

[0011] As a preferred embodiment of the present invention, the motion simulator includes an active turntable and a positioning seat disposed on one side of the active turntable. The positioning seat is provided with a slide rail corresponding to the active turntable, and a slider is provided in the slide rail for sliding connection. The active turntable is provided with a connecting rod connected to the slider.

[0012] In a preferred embodiment of the present invention, the connecting rod is rotatably connected to the active turntable, and the positioning seat is provided with a limiting telescopic rod for restricting the rotation of the connecting rod.

[0013] As a preferred embodiment of the present invention, the active turntable is provided with a DC motor that drives the active turntable to rotate.

[0014] As a preferred embodiment of the present invention, the motion capture device includes a matrix camera and a sensor corresponding to the matrix camera.

[0015] As a preferred embodiment of the present invention, the motion simulator is further provided with a displacement sensor for comparing the measurement error of the motion capture device.

[0016] As a preferred embodiment of the present invention, the rotor thrust actuator is provided with a speed regulator for controlling rotor thrust.

[0017] The test method for validating the experimental method of the hybrid model of floating wind turbines, based on the test system for validating the experimental method of the hybrid model of floating wind turbines, includes the following steps:

[0018] Step A: Simulate the wind speed of the entire wind field using wind simulation software, and pre-store the simulation data in the wind load prediction module;

[0019] Step B: Turn on the motion simulator, simultaneously start the motion capture device to capture the motion parameters of the motion simulator, and send the captured motion parameters of the motion simulator to the data acquisition device;

[0020] Step C: Input the motion parameters from the motion simulator connected to the data acquisition unit into the wind load prediction module;

[0021] Step D: Run the wind condition simulation software of the wind load prediction module to perform real-time calculations on the real-time data received by the wind load prediction module and generate corresponding thrust commands.

[0022] Step E: Transmit the thrust command to the rotor thrust actuator;

[0023] Step F: The load sensor measures the magnitude of the rotor thrust of the rotor thrust actuator and compares this rotor thrust magnitude with the thrust command issued by the wind load prediction module.

[0024] In a preferred embodiment of the present invention, step B includes a displacement sensor for measuring the motion parameters of the motion simulator, and the motion parameters measured by the displacement sensor are compared with the motion parameters measured by the motion capture device to obtain the error of the motion parameters.

[0025] As a preferred embodiment of the present invention, the model scale parameters obtained by the motion capture device from the motion simulator are converted into full scale according to the Froude scale conversion rule and input into the wind load prediction module. The full-scale wind load parameters predicted by the wind load prediction module are converted into motion simulator scale again according to the Froude scale conversion rule and then used as control signals, which are executed on the motion simulator by the control system of the actuator.

[0026] Compared with the prior art, the beneficial effect of the present invention is that by comparing the output data of the wind load prediction module with the measurement data of the load sensor, it verifies whether the prediction effect of the wind load prediction module of the floating wind turbine hybrid model experimental method can provide reasonable and accurate rotor thrust.

[0027] Meanwhile, the quality of the captured motion parameters is studied by comparing the motion parameters captured by the motion capture device with the measurements from the displacement sensor. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the system composition of the present invention;

[0029] Figure 2 This is a schematic diagram of the testing method of the present invention;

[0030] Figure 3 This is a schematic diagram of the structure of a motion simulator;

[0031] Figure 4 This is a data comparison chart between the motion capture device and the displacement sensor;

[0032] Figure 5 This is a comparison chart of the output data from the wind load prediction module and the measurement data from the load sensor;

[0033] Figure 6 This is a mass statistics chart of the rotor thrust actuator and load sensor;

[0034] Figure 7 This is a data comparison chart of Example 1;

[0035] Figure 8 This is a data comparison chart of Example 2;

[0036] Figure 9 This is a data comparison chart from Example 3;

[0037] Reference numerals: 1. Motion simulator; 11. Active turntable; 12. Positioning seat; 13. Slide rail; 14. Slider; 15. Connecting rod; 16. Limiting telescopic rod; 2. Motion capture device; 3. Data acquisition device; 4. Displacement sensor; 5. Wind condition simulation software; 6. Wind load prediction module; 7. Rotor thrust actuator; 8. Load sensor. Detailed Implementation

[0038] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0039] like Figures 1-9 As shown, the test system for verifying the experimental method of the hybrid model of floating wind turbines includes a wind load prediction module 6 and a motion simulator 1 for simulating surges. The motion simulator 1 is equipped with a motion capture device 2 for capturing motion parameters of the motion simulator 1. The motion capture device 2 is electrically connected to a data acquisition device 3 for receiving the motion parameters collected by the motion capture device 2. The data acquisition device 3 is electrically connected to the wind load prediction module 6. The wind load prediction module 6 is equipped with wind condition simulation software 5 for converting real-time data from the data acquisition device 3. The wind load prediction module 6 is electrically connected to a rotor thrust actuator 7 for receiving data from the wind condition simulation software 5. The rotor thrust actuator 7 is equipped with a load sensor 8 for measuring rotor thrust.

[0040] The wind load prediction module 6 predicts real-time wind load data (such as rotor thrust, tail fin aerodynamic force, blade tip motion, root load, etc.) based on the changes in the hydrodynamic response of the floating wind turbine physical model. In this benchmark test method, the hydrodynamic motion of the simplified floating wind turbine physical model is provided by the self-made motion simulator 1.

[0041] The motion capture device 2 includes a matrix camera and a corresponding sensor. The motion capture device 2 can capture the motion parameters of the motion simulator 1, such as the surge input of the motion simulator 1.

[0042] The wind simulation software 5 covers turbulence models with different wind speeds and conditions. The wind load prediction module 6 has a prediction algorithm to predict the wind load corresponding to the motion simulator 1 when a certain surge is generated.

[0043] The rotor thrust actuator 7 is used to receive the predicted value sent by the wind load prediction module 6 as a control signal. Through corresponding control means (PWM, PID, ESC control, etc.), the rotor thrust actuator 7 is applied to realize the real-time simulation of the response wind load.

[0044] The load sensor 8 is used to measure the wind load (rotor thrust, tail fin aerodynamic force, blade tip motion, root load, etc.) output by the wind load prediction module 6, and to make real-time predictions of the wind load on the motion simulator 1.

[0045] The readings of load sensor 8 consist of two parts: acceleration force and rotor thrust at model scale. The real-time acceleration force needs to be removed from the readings of rotor thrust sensor, and the reference mass of rotor thrust actuator 7 and rotor thrust sensor should be taken into account.

[0046] The motion simulator 1 includes an active turntable 11 and a positioning seat 12 disposed on one side of the active turntable 11. The positioning seat 12 is provided with a slide rail 13 corresponding to the active turntable 11. The slide rail 13 is provided with a slider 14 that is slidably connected, and the active turntable 11 is provided with a connecting rod 15 that is connected to the slider 14.

[0047] The slide rail 13 is fixedly mounted on the positioning seat 12, and the positioning seat 12 has a positioning block for clamping the slide rail 13. The slider 14 is embedded and slidably connected to the slide rail 13. A connecting pin is provided between the connecting rod 15 and the active turntable 11. The connecting pin is rotatably connected to the active turntable 11, and the connecting pin is slidably connected to the connecting rod 15. A groove is also formed on the connecting rod 15 along the length direction of the connecting rod 15, and the connecting pin is slidably connected in the groove.

[0048] The active turntable 11 is equipped with a DC motor that drives the active turntable 11 to rotate. The connecting rod 15 is rotatably connected to the active turntable 11, and the positioning seat 12 is equipped with a limiting telescopic rod 16 for limiting the rotation of the connecting rod 15. The connecting rod 15 is perpendicular to the slide rail 13, and the connecting rod 15 is also perpendicular to the limiting telescopic rod 16. The limiting telescopic rod 16 is parallel to the slide rail 13. Under the action of the limiting telescopic rod 16, when the active turntable 11 rotates, it ensures that the connecting rod 15 is always perpendicular to the slide rail 13, and the connecting rod 15 performs reciprocating translational motion, thereby generating the required surge.

[0049] The displacement of slider 13 can be controlled by changing the connection position between connecting rod 15 and active turntable 11, thereby controlling the reciprocating translation size of connecting rod 15 and thus controlling the surge size.

[0050] The motion simulator 1 is also equipped with a displacement sensor 4 for comparing the measurement error of the motion capture device 2. The displacement sensor 4 is an LVDT displacement sensor.

[0051] The rotor thrust actuator 7 is equipped with a speed regulator to control the rotor thrust. The electronic speed regulator receives signals from the receiver through current input. Based on the signals, it makes appropriate "control" on the current and then outputs the "controlled" current to the motor, thereby controlling and adjusting the speed of the rotor thrust actuator 7 to control it to generate the corresponding rotor thrust.

[0052] Speed ​​controllers can generate actuators using control strategies such as PWM, PID, and ESC. For example, an ESC electronic speed controller can be used to control the speed of a small fan, thereby controlling the corresponding rotor thrust.

[0053] The test system for validating the experimental method of the hybrid model of floating wind turbines includes the following steps:

[0054] Step A: Simulate the wind speed of the entire wind field using wind simulation software 5, and pre-store the simulation data in the wind load prediction module 6. The wind speed, wind direction, turbulent wind, etc. generated by the wind field simulation software 5 are pre-stored in the wind load prediction module 6.

[0055] Step B: The motion capture device 2 is connected to the data acquisition device 3. The motion simulator 1 is turned on, and the motion capture device 2 is started synchronously to capture the motion parameters of the motion simulator 1 and transmit the captured motion parameters of the motion simulator 1 to the data acquisition device 3.

[0056] The motion capture system 2 supports real-time data acquisition and transmission, and can accurately capture the motion parameters of the motion simulator 1. It can quickly and accurately transmit the motion data of surge displacement and surge velocity to the data acquisition unit 3. The X1 motion capture camera can be used to acquire the motion parameters of the motion simulator 1, and the output signal is a digital signal.

[0057] Displacement sensor 4 measures the motion parameters of motion simulator 1. The motion parameters measured by displacement sensor 4 are compared with those measured by motion capture device 2 to obtain the error of the motion parameters. Displacement sensor 4 is an LVDT displacement sensor connected to motion simulator 1. An SDVH8B pneumatic LVDT displacement sensor can be used. Pneumatic displacement sensors have excellent performance and are suitable for high-precision and high-repeatability measurements in quality control and metrology applications. The LVDT displacement sensor is used to measure the motion parameters generated by motion simulation, thereby studying the motion capture quality of the motion capture system.

[0058] Step C: Input the motion parameters of the motion simulator 1 connected to the data acquisition unit 3 into the wind load prediction module 6. The data acquisition unit 3 consists of Spike2 and CED smart laboratory interface. Spike2 can generate stimulus sequences and complex experimental controls in real time during data acquisition using the embedded output sequencer and CED1401 interface. In order to ensure accuracy, the digital and analog output timing is directly controlled by 1401 without relying on the host.

[0059] Step D: Run the wind condition simulation software 5 of the wind load prediction module 6, perform real-time calculations on the real-time data received by the wind load prediction module 6, and generate corresponding thrust commands.

[0060] The model scale parameters captured by the motion capture device 2 and obtained from the motion simulator 1 are converted into full scale according to the Froude scale conversion rule and input into the wind load prediction module 6. The full-scale wind load parameters predicted by the wind load prediction module 6 are converted into the scale of the motion simulator 1 again according to the Froude scale conversion rule and then used as control signals. These signals are then executed on the motion simulator 1 by the control system of the actuator.

[0061] The wind simulation software 5 obtains the wind simulator of TurbSim software and stores the full wind field (such as wind speed, wind direction, turbulent wind, etc.) generated by numerical simulation in the wind load prediction module 6.

[0062] Step E: Transmit the thrust command to the rotor thrust actuator 7, and use the ESC electronic speed controller to control the speed of the small fan, thereby controlling and adjusting the rotor thrust actuator 7 to generate the corresponding rotor thrust.

[0063] Step F: Load sensor 8 measures the magnitude of rotor thrust of rotor thrust actuator 7 and compares the magnitude of rotor thrust with the thrust command issued by wind load prediction module 6.

[0064] By comparing the output of the wind load prediction module 6 with the measurement of the load sensor 8, the prediction effect of the wind load prediction module of the floating wind turbine hybrid model experimental method can be verified to provide reasonable and accurate rotor thrust.

[0065] According to one embodiment of the present invention, given a surge input of a self-made motion simulator, data between 60 and 130 seconds is selected for further analysis to avoid transient reactions.

[0066] To verify the benchmark test method of the wind load prediction module of the floating wind turbine hybrid model experimental method, the readings of the load sensor need to be read. The reference mass needs to be determined and surge is only allowed when the rotor thrust actuator 7 is turned off. In this experimental example, the reading of the load sensor 8 is only the acceleration force.

[0067] Acceleration force can be described by Newton's second law, as shown by the equation F. referred =M referred *a

[0068] F referred The acceleration 'a' is as follows:

[0069] F referred =|F max |sin(ωt+ϕ1)

[0070] a=|a max |sin(ωt+ϕ2)

[0071] In the formula, ω is the angular frequency of the motion simulator.

[0072] Ignoring phase difference, the initial force caused by mass can be described as M referred =|F max |÷|a max |

[0073] The reference mass distribution is obtained as F max and a maxFor each cycle, the reference mass is calculated to obtain the mean and variance of each test. Based on the statistical calculation of the experimental data, the recommended range of reference mass is 820-830g.

[0074] The reference mass is constant, contributed by the rotor thrust actuator and the load sensor, and is within the recommended range. According to one embodiment of the invention, the mass of the rotor thrust actuator and the load sensor is 820g.

[0075] In the benchmark test method for verifying the prediction effect of the wind load prediction module 6 in the experimental method of the floating wind turbine hybrid model, the reading of the load sensor 8 is read, and the magnitude of the rotor thrust is obtained after removing the acceleration force.

[0076] Example 1:

[0077] First, the wind dataset generated using TurbSim is stored in the wind load prediction module 6, with the wind speed set to 8 m / s. A surge input v1 is simulated using a motion simulator 1. An integrated motion capture device 2, combined with a displacement sensor 4, measures the motion generated by the motion simulator 1 to study the motion capture quality of the motion capture device 2. The surge displacement and velocity, along with the wind speed, are input into the wind load prediction module 6. The model scale parameters obtained from the motion simulator 1, monitored by the load sensor 8, are converted to full-scale parameters according to the Froude scale transformation rule and then input into the wind load prediction module 6. The full-scale wind load parameters predicted by the wind load prediction module 6 are again converted to the motion simulator 1 scale according to the Froude scale transformation rule and then used as control signals. These signals are executed by the actuator control system on the motion simulator 1. The rotor thrust actuator 7 is controlled by ESC speed control. The wind load output from the wind load prediction module 6 is read from the load sensor 8. The measurement results show good agreement with the output results of the wind load prediction module 6. Figure 7 The results are given.

[0078] Example 2:

[0079] First, the wind dataset generated using TurbSim is stored in the wind load prediction module 6, with the wind speed set to 12 m / s. A surge input v2 is simulated using a motion simulator 1. An integrated motion capture device 2, combined with a displacement sensor 4, measures the motion generated by the motion simulator 1 to study the motion capture quality of the motion capture device 2. The surge displacement and velocity, along with the wind speed, are input into the wind load prediction module 6. The model scale parameters obtained from the motion simulator 1, monitored by the load sensor 8, are converted to full-scale parameters according to the Froude scale transformation rule and then input into the wind load prediction module 6. The full-scale wind load parameters predicted by the wind load prediction module 6 are again converted to the motion simulator 1 scale according to the Froude scale transformation rule and then used as control signals. These signals are executed by the actuator control system on the motion simulator 1. The rotor thrust actuator 7 is controlled by ESC speed control. The wind load output from the wind load prediction module 6 is read from the load sensor 8. The measurement results show good agreement with the output results of the wind load prediction module 6. Figure 8 The results are given.

[0080] Example 3:

[0081] First, the wind dataset generated using TurbSim is stored in the wind load prediction module 6, with the wind speed set to 16 m / s. A surge input v3 is simulated using a motion simulator 1. An integrated motion capture device 2, combined with a displacement sensor 4, measures the motion generated by the motion simulator 1 to study the motion capture quality of the motion capture device 2. The surge displacement and velocity, along with the wind speed, are input into the wind load prediction module 6. The model scale parameters obtained from the motion simulator 1, monitored by the load sensor 8, are converted to full-scale parameters according to the Froude scale transformation rule and then input into the wind load prediction module 6. The full-scale wind load parameters predicted by the wind load prediction module 6 are again converted to the motion simulator 1 scale according to the Froude scale transformation rule and then used as control signals. These signals are executed by the actuator control system on the motion simulator 1. The rotor thrust actuator 7 is controlled by ESC speed control. The wind load output from the wind load prediction module 6 is read from the load sensor 8. The measurement results show good agreement with the output results of the wind load prediction module 6. Figure 9 The results are given.

[0082] When the wind speeds are 8 m / s, 12 m / s and 16 m / s respectively, the measurement results of the load sensor 8 are in good agreement with the output results of the wind load prediction module 6, which verifies that the wind load prediction module 6 of the floating wind turbine hybrid model experimental method can provide reasonable and accurate rotor thrust.

[0083] According to one embodiment of the present invention, the measurement results of the load sensor and the prediction results of the artificial intelligence wind load prediction module are in good agreement, and the characteristics of the test bench for verifying the prediction effect of the wind load prediction module of the floating wind turbine hybrid model experimental method can provide reasonable and accurate rotor thrust.

[0084] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention; therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0085] Although this document uses numerous reference numerals from the figures, such as motion simulator 1, active turntable 11, positioning seat 12, slide rail 13, slider 14, connecting rod 15, limiting telescopic rod 16, motion capture device 2, data acquisition device 3, displacement sensor 4, wind condition simulation software 5, wind load prediction module 6, rotor thrust actuator 7, and load sensor 8, the possibility of using other terms is not excluded. These terms are used merely for the convenience of describing and explaining the essence of the invention; interpreting them as any additional limitation would contradict the spirit of the invention.

Claims

1. A test method for a test system used to verify the experimental method of a hybrid model of a floating wind turbine, comprising a wind load prediction module (6) and a motion simulator (1) for simulating surges, characterized in that, The motion simulator (1) is equipped with a motion capture device (2) for capturing motion parameters of the motion simulator (1). The motion capture device (2) is electrically connected to a data acquisition device (3) for receiving motion parameters collected by the motion capture device (2). The data acquisition device (3) is electrically connected to a wind load prediction module (6). The wind load prediction module (6) is equipped with wind condition simulation software (5) for converting real-time data from the data acquisition device (3). The wind load prediction module (6) is electrically connected to a rotor thrust actuator (7) for receiving data from the wind condition simulation software (5). The rotor thrust actuator (7) is equipped with a load sensor (8) for measuring rotor thrust. The process includes the following steps: Step A: Simulate the wind speed of the entire wind field using wind simulation software (5), and store the simulation data in advance in the wind load prediction module (6); Step B: Start the motion simulator (1), and simultaneously start the motion capture device (2) to capture the motion parameters of the motion simulator (1), and send the captured motion parameters of the motion simulator (1) to the data acquisition device (3). Step C: Input the motion parameters of the motion simulator (1) connected to the data acquisition unit (3) into the wind load prediction module (6); Step D: Run the wind condition simulation software (5) of the wind load prediction module (6) to perform real-time calculation on the real-time data received by the wind load prediction module (6) and generate corresponding thrust commands; Step E: Transmit the thrust command to the rotor thrust actuator (7); Step F: The load sensor (8) measures the magnitude of the rotor thrust of the rotor thrust actuator (7) and compares the magnitude of the rotor thrust with the thrust command issued by the wind load prediction module (6).

2. The test method of the test system for verifying the experimental method of the hybrid model of a floating wind turbine according to claim 1, characterized in that, In step B, a displacement sensor (4) is provided to measure the motion parameters of the motion simulator (1). The motion parameters measured by the displacement sensor (4) are compared with the motion parameters measured by the motion capture device (2) to obtain the error of the motion parameters.

3. The test method of the test system for verifying the experimental method of the hybrid model of a floating wind turbine according to claim 1, characterized in that, The model scale parameters captured by the motion capture device (2) and obtained from the motion simulator (1) are converted into full scale according to the Froude scale conversion rule and input into the wind load prediction module (6). The full-scale wind load parameters predicted by the wind load prediction module (6) are converted into the motion simulator (1) scale again according to the Froude scale conversion rule and then used as control signals. The control system of the actuator is then executed on the motion simulator (1).

4. The test method of the test system for verifying the experimental method of the hybrid model of a floating wind turbine according to claim 1, characterized in that, The motion simulator (1) includes an active turntable (11) and a positioning seat (12) located on one side of the active turntable (11). The positioning seat (12) is provided with a slide rail (13) corresponding to the active turntable (11). The slide rail (13) is provided with a slider (14) that is slidably connected. The active turntable (11) is provided with a connecting rod (15) that is connected to the slider (14).

5. The test method of the test system for verifying the experimental method of the hybrid model of a floating wind turbine according to claim 4, characterized in that, The connecting rod (15) is rotatably connected to the active turntable (11), and the positioning seat (12) is provided with a limiting telescopic rod (16) for limiting the rotation of the connecting rod (15).

6. The test method of the test system for verifying the experimental method of the hybrid model of a floating wind turbine according to claim 4, characterized in that, The active turntable (11) is equipped with a DC motor that drives the active turntable (11) to rotate.

7. The test method of the test system for verifying the experimental method of the hybrid model of a floating wind turbine according to claim 1, characterized in that, The motion capture device (2) includes a matrix camera and a sensor corresponding to the matrix camera.

8. The test method of the test system for verifying the experimental method of the hybrid model of a floating wind turbine according to claim 1, characterized in that, The motion simulator (1) is also equipped with a displacement sensor (4) for comparing the measurement error of the motion capture device (2).

9. The test method of the test system for verifying the experimental method of the hybrid model of a floating wind turbine according to claim 1, characterized in that, The rotor thrust actuator (7) is equipped with a speed regulator to control the rotor thrust.

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