Raindrop speed control method and system for wind power blade corrosion resistance test

Abstract

The invention relates to the technical field of wind power blades, in particular to a raindrop speed control method and system for a wind power blade corrosion resistance test, and the method comprises the steps: determining the target range of the raindrop speed based on the operation environment of a wind power blade, and building a target parameter model for controlling the raindrop speed; on the basis of the target parameters, the raindrop speed is adjusted to be close to the target range by adjusting and controlling the raindrop generation mode and the initial power; the speed and the external environment condition in the raindrop movement process are monitored in real time, and corresponding dynamic data are obtained; based on data monitored in real time, the raindrop speed is dynamically adjusted through a control algorithm; a feedback mechanism is introduced, and periodic optimization is performed by adjusting the raindrop speed in real time and based on feedback of historical data. According to the invention, the problems of low raindrop speed control precision, insufficient dynamic adjustment capability and lack of a real-time feedback mechanism in the prior art are effectively solved, and the accuracy and stability of the test are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbine blades, and in particular to a raindrop velocity control method and system for a wind turbine blade corrosion resistance test. Background Art

[0002] Wind turbine blades are exposed to a complex natural environment during long-term operation. Especially on rainy days, the continuous impact of raindrops can cause wear and corrosion on the blade surface, thus affecting its service life and the overall performance of the wind turbine. Therefore, corrosion resistance testing of wind turbine blades by simulating raindrop erosion has become an important research method.

[0003] However, the existing raindrop erosion test has many problems in controlling the raindrop velocity. First, the control accuracy is low. It is difficult for traditional injection systems or air pressure regulation to achieve precise control of raindrop velocity, especially under complex conditions, where the velocity fluctuates greatly. Second, the existing technology lacks dynamic adjustment capabilities and cannot adjust the raindrop velocity in real time according to changes in the external environment (such as wind speed, air pressure, etc.), resulting in poor instability and repeatability of the test results. In addition, there is a lack of effective feedback adjustment mechanism, and it is impossible to monitor and adjust the raindrop velocity in real time, which makes it difficult to correct the velocity deviation in time, affecting the accuracy and reliability of the test. Summary of the invention

[0004] The present invention provides a raindrop velocity control method and system for a wind turbine blade corrosion resistance test, thereby effectively solving the problems pointed out in the background technology.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A raindrop velocity control method for a wind turbine blade corrosion resistance test, comprising:

[0007] Based on the operating environment of wind turbine blades, the target range of raindrop velocity is determined, and a target parameter model for controlling raindrop velocity is established;

[0008] Based on the target parameters, the raindrop speed is adjusted to a range close to the target by regulating the raindrop generation method and initial power;

[0009] Monitor the speed and external environmental conditions of raindrops in real time and obtain corresponding dynamic data;

[0010] Based on real-time monitoring data, the control algorithm is used to dynamically adjust the raindrop speed. When the external environment changes, the raindrop speed control strategy is adjusted to perform multiple iterations of speed adjustment.

[0011] A feedback mechanism is introduced to adjust the raindrop speed in real time and perform periodic optimization based on feedback from historical data. According to the needs of different stages of the experiment, rough regulation is carried out in the early stage and fine adjustment is implemented in the critical stage.

[0012] Furthermore, based on the operating environment of the wind turbine blades, a target range of raindrop velocity is determined, and a target parameter model for controlling the raindrop velocity is established, including:

[0013] Collect external meteorological data and wind turbine blade operating parameters in the wind turbine blade operating environment;

[0014] Calculating the initial velocity range of raindrops under different external conditions based on the collected external meteorological data;

[0015] Based on the external meteorological data, analyzing the influence of external environmental factors on the raindrop velocity, calculating the change of the raindrop velocity under different conditions, and evaluating the relative velocity change between the blade and the raindrop;

[0016] Based on the environmental data, initial raindrop velocity and blade motion characteristics, a multi-dimensional target parameter model for controlling raindrop velocity is established, and the model is verified and optimized.

[0017] Furthermore, the calculation formula of the terminal velocity of the raindrop is:

[0018]

[0019] Where v is the terminal velocity of the raindrop, that is, the maximum velocity reached by the raindrop when falling in the air, m is the mass of the raindrop, g is the acceleration of gravity, ρ is the air density, A is the windward cross-sectional area of ​​the raindrop, and C is the windward cross-sectional area of ​​the raindrop. d is the air resistance coefficient.

[0020] Furthermore, based on the target parameters, the raindrop velocity is adjusted to a close target range by regulating the raindrop generation method and initial power, including:

[0021] According to the target parameter model, the nozzle diameter, the spray pressure or the droplet generating device is adjusted to generate raindrops with a predetermined size and mass, and the generation frequency of the raindrops is controlled;

[0022] According to the target speed range, the air pressure or the dynamic parameters of the injection device are adjusted to give the raindrops an initial speed to reach the target speed range;

[0023] By adjusting the falling height of raindrops, gravity is used to accelerate raindrops;

[0024] During the falling process of raindrops, airflow is applied, and the speed of raindrops is adjusted by adjusting the wind speed and airflow direction.

[0025] The speed of raindrops is monitored in real time, and the raindrop generation parameters, initial dynamics and airflow regulation parameters are adjusted according to the monitoring results.

[0026] Furthermore, the speed of raindrops and external environmental conditions during their movement are monitored in real time, and corresponding dynamic data are obtained, including:

[0027] Dynamically collect the speed of raindrops and external environmental parameters, including but not limited to the speed of raindrops, wind speed, air pressure and humidity;

[0028] Based on the collected data, the speed of raindrops in motion and its changes affected by external environmental conditions are continuously monitored;

[0029] The collected data is processed and analyzed to determine the difference between the raindrop velocity and the target velocity range. The relevant parameters are adjusted according to the analysis results to control the raindrop velocity to be within the predetermined range.

[0030] Furthermore, based on the real-time monitoring data, the control algorithm is used to dynamically adjust the raindrop speed, and when the external environment changes, the raindrop speed control strategy is adjusted to perform multiple iterations of speed adjustment, including:

[0031] Analyze the speed of raindrops and external environmental parameters in real time to identify the difference between the current speed and the target speed range;

[0032] Based on the analysis results, the control algorithm is used to dynamically adjust the raindrop speed and adjust the relevant parameters to match the target speed;

[0033] When the external environmental parameters change, the data is updated, the parameters of the control algorithm are adjusted, and the adjustment process of the raindrop speed is repeated;

[0034] Through multiple iterative adjustments, the raindrop velocity control strategy is continuously optimized under the condition of external environmental fluctuations until the raindrop velocity always approaches the target range under different conditions.

[0035] Furthermore, a feedback mechanism is introduced to adjust the raindrop speed in real time and perform periodic optimization based on the feedback of historical data, including:

[0036] Based on the real-time monitoring of raindrop velocity and environmental conditions, the deviation between the current raindrop velocity and the predetermined target velocity is analyzed and immediate adjustments are made;

[0037] Store real-time monitoring data, adjustment parameters and environmental condition data to generate historical data sets;

[0038] By periodically analyzing the historical data set, applying the optimization algorithm, evaluating the effectiveness of each parameter, extracting the regulation mode related to environmental changes, and optimizing the control algorithm;

[0039] The control strategy is dynamically updated by combining the dual feedback mechanism of instant feedback and historical data optimization.

[0040] Furthermore, according to the needs of different stages of the experiment, rough regulation is carried out in the early stage and fine adjustment is implemented in the key stage, including:

[0041] In the initial stage of the test, a rough adjustment is made by adjusting the raindrop generation method, the jet power and the airflow parameters so that the raindrop speed falls within the allowable interval of the target speed range. The adjustment does not perform fine processing on individual variables.

[0042] Monitor the speed of raindrops and external environmental parameters in real time to determine whether the speed of raindrops is within the target speed range, and make necessary rough adjustments to relevant parameters when there is a large deviation;

[0043] When the test enters the critical stage, the adjustment range is gradually reduced according to the monitoring data, and the air flow speed, direction and injection pressure are finely adjusted. The critical stage includes the precise testing stage, the extreme environment simulation stage and the key parameter measurement stage.

[0044] A raindrop velocity control system for a wind turbine blade corrosion test, the system comprising:

[0045] The parameter model building module determines the target range of raindrop velocity based on the operating environment of wind turbine blades and establishes a target parameter model for controlling raindrop velocity. The raindrop velocity initial adjustment module adjusts the raindrop velocity to a range close to the target range by regulating the raindrop generation method and initial power based on the target parameters.

[0046] The dynamic data acquisition module monitors the speed and external environmental conditions of raindrops in real time and acquires the corresponding dynamic data;

[0047] The data iteration adjustment module dynamically adjusts the raindrop speed using the control algorithm based on the real-time monitoring data, and adjusts the raindrop speed control strategy when the external environment changes, and performs multiple iterations of speed adjustment;

[0048] The feedback mechanism optimization module introduces a feedback mechanism to perform periodic optimization by instantly adjusting the raindrop speed and based on the feedback of historical data. According to the needs of different stages of the experiment, rough regulation is performed in the early stage and fine adjustment is implemented in the critical stage.

[0049] Furthermore, the parameter model building module includes:

[0050] An operating parameter collection unit collects external meteorological data in the operating environment of the wind turbine blades and operating parameters of the wind turbine blades;

[0051] An initial velocity calculation unit, which calculates the initial velocity range of raindrops under different external conditions according to the collected external meteorological data;

[0052] a speed change evaluation unit, which analyzes the influence of external environmental factors on the raindrop speed based on the external meteorological data, calculates the change of the raindrop speed under different conditions, and evaluates the relative speed change between the blade and the raindrop;

[0053] The model verification and optimization unit integrates environmental data, initial raindrop velocity and blade motion characteristics to establish a multi-dimensional target parameter model for controlling raindrop velocity, and verifies and optimizes the model.

[0054] The technical solution of the present invention can achieve the following technical effects:

[0055] It effectively solves the problems of low raindrop velocity control accuracy, insufficient dynamic adjustment capability and lack of real-time feedback mechanism in the existing technology, and significantly improves the accuracy and stability of the test. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 It is a flow chart of a raindrop velocity control method for a wind turbine blade corrosion resistance test;

[0058] Figure 2 Schematic diagram of the process for determining the target range of raindrop velocity and establishing the target parameter model;

[0059] Figure 3 A schematic diagram of the process for adjusting the raindrop velocity to a range close to the target;

[0060] Figure 4 A flow chart for real-time monitoring and obtaining corresponding dynamic data;

[0061] Figure 5 A schematic diagram of the process of dynamically adjusting the raindrop velocity based on real-time data and iteratively optimizing the control strategy;

[0062] Figure 6 A schematic diagram of the process of periodic optimization by adjusting the raindrop speed in real time and based on the feedback of historical data;

[0063] Figure 7 This is a flow chart showing different control strategies according to the needs of different stages of the experiment. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0066] Embodiment 1

[0067] like Figure 1 As shown, the present invention provides a raindrop velocity control method for a wind turbine blade corrosion resistance test, the method comprising:

[0068] S1: Based on the operating environment of wind turbine blades, determine the target range of raindrop velocity and establish a target parameter model for controlling raindrop velocity;

[0069] Specifically, by collecting meteorological data and blade operating parameters in the actual operating environment of wind turbine blades, and combining external environmental factors such as wind speed, air pressure, and temperature, an accurate target parameter model is established. The core purpose of this model is to determine the raindrop velocity range suitable for wind turbine blades when they are eroded by raindrops under actual conditions, ensuring that the test can simulate the actual situation in the natural environment, thereby making a more accurate assessment of the corrosion resistance of wind turbine blades. In addition, the model provides a basis for the subsequent dynamic adjustment of raindrop velocity, so that the raindrop velocity can be maintained within the predetermined range during different experimental stages or environmental changes, thereby enhancing the accuracy and reliability of the test.

[0070] S2: Based on the target parameters, the raindrop speed is adjusted to a range close to the target by regulating the raindrop generation method and initial power;

[0071] Specifically, first, according to the target parameter model, determine the generation method of raindrops, and generate raindrops of predetermined size and mass by adjusting the nozzle diameter, injection pressure or droplet generation device to ensure that its initial state can be close to the target speed range; then, according to the test requirements, reasonably control the generation frequency of raindrops to avoid collision or interference between raindrops, so as to ensure that each raindrop can fall independently and maintain the expected speed; after the raindrops are generated, the initial kinetic energy is given to the raindrops by adjusting the initial power, such as controlling the air pressure or the power parameters of the injection device, so that the speed is as close to the target range as possible. This adjustment process is achieved by controlling the injection pressure, airflow intensity, etc., so that the raindrops can quickly reach the expected state of motion; then, use gravity to naturally accelerate the raindrops, and by adjusting the height and path of the raindrops, the raindrop speed is gradually close to the target range, thereby reducing the dependence on external power. In some cases, in order to achieve more precise speed adjustment, an external controllable airflow can also be applied to further adjust the speed of the raindrops by adjusting the wind speed and airflow direction to ensure that the raindrops remain within the predetermined speed range during the movement.

[0072] S3: Monitor the speed and external environmental conditions of raindrops in real time and obtain corresponding dynamic data;

[0073] Specifically, the purpose of real-time monitoring of raindrop movement speed and external environmental conditions is to ensure that the raindrop speed always meets the test requirements and to cope with the impact of the external environment on the raindrop speed. By monitoring the speed and environmental data, when deviations are found, the injection device and airflow conditions can be adjusted in time to keep the raindrop speed within the target range. This process not only improves the accuracy of the test, but also optimizes the control strategy through a dynamic feedback mechanism. At the same time, the recording of monitoring data provides support for the repeatability and reliability of the test, ensuring the consistency of the test results under different environmental conditions.

[0074] S4: Based on real-time monitoring data, the control algorithm is used to dynamically adjust the raindrop speed, and when the external environment changes, the raindrop speed control strategy is adjusted to perform multiple iterations of speed adjustment;

[0075] Specifically, through real-time monitoring data, the control algorithm is used to dynamically adjust the raindrop speed to ensure that the raindrop speed always remains within the target range. Since the external environment (such as wind speed, air pressure, etc.) may change at any time, this step can adjust the raindrop speed control strategy in time when these changes are detected to ensure the accuracy and stability of the raindrop speed. Through multiple iterative adjustments, the control algorithm is gradually optimized to adapt to the changing external conditions, and finally the raindrop speed is kept consistent with the target speed.

[0076] S5: Introduce a feedback mechanism to adjust the raindrop speed in real time and perform periodic optimization based on the feedback of historical data. According to the needs of different stages of the experiment, rough regulation is carried out in the early stage and fine adjustment is implemented in the critical stage.

[0077] Specifically, the purpose of introducing the feedback mechanism is to dynamically adjust the raindrop speed through instant feedback of real-time data, and to perform periodic optimization in combination with historical data to ensure the accuracy and efficiency of control. In the early stage of the test, the raindrop speed is roughly adjusted to roughly fall within the target range to meet the basic test requirements. As the test progresses, especially in the critical stage, fine adjustment is gradually introduced. Based on historical data feedback, the control algorithm is optimized and adjusted to improve the precise control of the raindrop speed. Through this dual feedback mechanism, adjustments during the test are more flexible and efficient, ensuring that the test needs at different stages are met.

[0078] The present invention effectively solves the problems of low raindrop velocity control accuracy, insufficient dynamic adjustment capability and lack of real-time feedback mechanism in the prior art, and significantly improves the accuracy and stability of the test.

[0079] As a preferred embodiment of the above, Figure 2 As shown, step S1, based on the operating environment of the wind turbine blade, determines the target range of raindrop velocity and establishes a target parameter model for controlling the raindrop velocity, including:

[0080] S11: collecting external meteorological data in the wind turbine blade operating environment and operating parameters of the wind turbine blade;

[0081] S12: Calculate the initial velocity range of raindrops under different external conditions based on the collected external meteorological data;

[0082] S13: Based on external meteorological data, analyze the impact of external environmental factors on raindrop velocity, calculate the change of raindrop velocity under different conditions, and evaluate the relative velocity change between leaves and raindrops;

[0083] S14: Based on the environmental data, initial raindrop velocity and blade motion characteristics, a multi-dimensional target parameter model for controlling raindrop velocity is established, and the model is verified and optimized.

[0084] Specifically, first, it is necessary to collect external meteorological data and operating parameters of wind turbine blades in the operating environment. External meteorological data include wind speed, air pressure, temperature, humidity and other parameters, while wind turbine blade operating parameters may include blade rotation speed, angle, position and other information. These data can comprehensively reflect the working status of wind turbine blades in the actual environment and the external influences they are subject to. Next, based on the collected meteorological data, calculate the initial speed range of raindrops under different external conditions. For example, under different wind speed and air pressure conditions, the generation and acceleration process of raindrops will be different. Therefore, it is necessary to estimate the possible initial speed range of raindrops when they fall based on these external conditions. Analyze the influence of external environmental factors on the speed of raindrops, and further calculate the speed of raindrops under different external conditions. Changes in the situation, through comprehensive meteorological data, analyze how factors such as wind speed and air pressure affect the acceleration or deceleration process of raindrops. In addition, it is necessary to evaluate the changes in the relative speed between the blades and raindrops, and understand the interaction between the blade surface and raindrops when the wind turbine blades move, so as to ensure that the model can reflect the complexity of the actual experiment; finally, based on the external environmental data, the initial speed of raindrops and the movement characteristics of wind turbine blades, a multi-dimensional target parameter model is established to control the speed of raindrops. This model can take into account the complex relationship between multiple variables and accurately predict the speed changes of raindrops under specific conditions. In order to ensure the reliability of the model, the model needs to be verified and optimized. By comparing the actual data with the simulation data, the effectiveness of the model under different environmental conditions is ensured, and its accuracy is gradually improved. The preferred model of this scheme recommends the use of a dynamic system model, especially a state-space model based on Kalman filtering. This model can handle changes in multivariable dynamic systems in real time and has strong adaptability. It is particularly suitable for the frequent fluctuations in the external environment during the corrosion resistance test of wind turbine blades. Kalman filtering is a recursive algorithm that can estimate the system state in real time in a dynamic environment and gradually correct the prediction results of raindrop velocity by minimizing errors. Its advantage is that it can combine current observation data with historical data to achieve precise control of raindrop velocity. Even when external conditions (such as wind speed, air pressure, etc.) are constantly changing, the raindrop velocity control strategy can still be dynamically adjusted.

[0085] As a preferred embodiment of the above embodiment, the calculation formula of the terminal velocity of the raindrop is:

[0086]

[0087] Where v is the terminal velocity of the raindrop, that is, the maximum velocity reached by the raindrop when falling in the air, m is the mass of the raindrop, g is the acceleration of gravity, ρ is the air density, A is the windward cross-sectional area of ​​the raindrop, and C is the windward cross-sectional area of ​​the raindrop. d is the air resistance coefficient.

[0088] Specifically, this formula is based on the state when gravity and air resistance are balanced during the falling process of raindrops. Gravity accelerates the falling of raindrops, but at the same time, the air resistance to raindrops increases with the speed. Eventually, raindrops reach a force balance at a certain speed, which is the terminal speed. In the process of controlling the speed of raindrops, this formula can help predict the maximum speed range of raindrops and be used to control various parameters in the experiment, such as raindrop mass, wind speed, airflow, etc., to accurately simulate the corrosion resistance test conditions of wind turbine blades in real environments.

[0089] As a preferred embodiment of the above, Figure 3 As shown, step S2, based on the target parameters, by regulating the raindrop generation method and the initial power, adjusts the raindrop speed to a close target range, including:

[0090] S21: According to the target parameter model, adjusting the nozzle diameter, the spray pressure or the droplet generating device to generate raindrops with a predetermined size and mass, and controlling the generation frequency of the raindrops;

[0091] S22: According to the target speed range, the air pressure or the dynamic parameters of the injection device are adjusted to give the raindrops an initial speed to reach the target speed range;

[0092] S23: Accelerating raindrops by using gravity by adjusting the falling height of raindrops;

[0093] S24: During the falling process of raindrops, airflow is applied, and the speed of raindrops is adjusted by adjusting the wind speed and the direction of airflow;

[0094] S25: Monitor the speed of raindrops in real time, and adjust raindrop generation parameters, initial power and airflow adjustment parameters according to the monitoring results.

[0095] Specifically, at this stage, the size and mass of raindrops have a direct impact on their speed. By adjusting the diameter of the nozzle, the size of the generated raindrops can be controlled; by adjusting the injection pressure, the kinetic energy of the raindrops when they are formed can be adjusted. At the same time, by adjusting the droplet generation device, the quality of the raindrops can be ensured to meet the predetermined requirements. The size and mass of the generated raindrops must match the target parameter model to ensure that the falling behavior of the raindrops in the air meets the target speed range. In addition, the generation frequency of raindrops must be controlled to ensure continuous and stable raindrop output to meet the time and experimental intensity required for the test; next, by adjusting the air pressure or the dynamic parameters of the injection device, the initial speed of the raindrops can be changed. The greater the injection pressure, the higher the initial speed of the raindrops, and vice versa. Different air pressure or kinetic energy settings can affect the initial acceleration of the raindrops. The purpose of this stage is to make the speed of the raindrops as close to the predetermined target speed range as possible through appropriate initial power settings, laying the foundation for subsequent acceleration and adjustment; increasing the falling height of the raindrops can use gravity to further accelerate the raindrops. When the raindrops fall from a higher place, the effect of gravity will gradually increase their speed. Therefore, adjusting The falling height can effectively control the acceleration process of raindrops, especially when the injection pressure is not enough to fully reach the target speed, the use of gravity acceleration helps to make the raindrops move within a range closer to the target speed. In order to more accurately control the speed of raindrops, airflow can be applied during the falling process of raindrops. By adjusting the wind speed and direction of the airflow, the movement speed of raindrops can be further affected. If the raindrop speed deviates from the target value, it can be adjusted again by accelerating or decelerating the airflow. For example, increasing the wind speed can accelerate the raindrops, while reducing the wind speed or changing the wind direction can slow down the raindrops. This airflow adjustment can finely control the speed of raindrops during their falling process, so that they always remain within the target range. In the final step, sensors and monitoring equipment are used to detect the actual speed of raindrops in real time to obtain accurate dynamic data. By comparing the actual raindrop speed with the target speed, raindrop generation parameters (such as nozzle diameter, injection pressure, etc.), initial power (such as air pressure or power setting of the injection device) and airflow adjustment parameters can be quickly adjusted. Real-time monitoring can ensure that the raindrop speed is always within the target speed range when external conditions change or equipment is unstable.

[0096] As a preferred embodiment of the above, Figure 4 As shown, step S3 monitors the speed and external environmental conditions of the raindrops in real time during their movement and obtains corresponding dynamic data, including:

[0097] S31: dynamically collect the speed of raindrops and external environmental parameters, and the collected data include but are not limited to the speed of raindrops, wind speed, air pressure and humidity; S32: based on the collected data, continuously monitor the speed of raindrops in motion and its changes affected by external environmental conditions;

[0098] S33: Processing and analyzing the collected data, determining the difference between the raindrop velocity and the target velocity range, adjusting relevant parameters according to the analysis results, and controlling the raindrop velocity to meet the predetermined range.

[0099] Specifically, first, sensors and monitoring equipment are used to collect multiple data related to raindrop movement in real time, including the actual speed of raindrops, wind speed, air pressure, temperature, humidity, etc. of the external environment. These external environmental conditions directly affect the movement of raindrops, so monitoring these data is the basis for ensuring the accuracy of the experiment; next, by real-time monitoring of the collected raindrop speed and external environmental data, the actual movement of raindrops under different environmental conditions can be understood. Since the external environment may change at any time (such as wind speed fluctuations, air pressure changes, etc.), the raindrop speed will be affected. Through continuous monitoring, the dynamic response of the raindrop speed when the external conditions change can be grasped in real time to ensure comprehensive control of the raindrop movement; finally, by processing and analyzing the collected raindrop speed and environmental data, the difference between the actual speed of raindrops and the predetermined target speed can be judged. Based on this analysis, the relevant control parameters can be dynamically adjusted, including nozzle settings, injection pressure, airflow adjustment, etc., to ensure that the raindrop speed can quickly return to the target range. Through such adjustments, the raindrop speed can continue to be maintained within the set standard range during the entire test. Even if the external environmental conditions change, it can respond in time to maintain the accuracy and stability of the test.

[0100] As a preferred embodiment of the above, Figure 5 As shown, step S4, based on the real-time monitoring data, uses the control algorithm to dynamically adjust the raindrop speed, and when the external environment changes, adjusts the raindrop speed control strategy, and performs multiple iterations of speed adjustment, including:

[0101] S41: Analyze the speed of raindrops and external environmental parameters in real time to identify the difference between the current speed and the target speed range;

[0102] S42: Based on the analysis results, dynamically adjust the raindrop speed using a control algorithm and adjust relevant parameters to match the target speed;

[0103] S43: When the external environmental parameters change, the data is updated, the parameters of the control algorithm are adjusted, and the raindrop speed adjustment process is repeated; S44: Through multiple iterative adjustments, the raindrop speed control strategy is continuously optimized under the condition of external environmental fluctuations until the raindrop speed always approaches the target range under different conditions.

[0104] Specifically, first, the actual speed of the current raindrops is compared with the predetermined target speed range through the real-time collection of raindrop speed and external environmental parameters, so as to identify the difference between the two. This difference analysis helps to understand whether the raindrop speed meets the target requirements and provides a basis for subsequent adjustments. External environmental parameters such as wind speed and air pressure will also affect the raindrop speed. Real-time analysis of these changes is an important part of ensuring accurate control. When a deviation is found between the raindrop speed and the target range, the control algorithm will adjust the relevant parameters according to this deviation and make dynamic adjustments. These parameters may include the pressure of the injection device, the air flow speed or the raindrop generation method. By flexibly adjusting these parameters, the raindrop speed can be brought closer to the target range. The application of the control algorithm ensures rapid response and flexible adjustment to ensure that the raindrops are within the target range. The speed can be precisely controlled under different conditions; if the external environmental parameters such as wind speed or air pressure change, the data will be updated in time, and the deviation between the raindrop speed and the target range will be recalculated. The control algorithm will readjust the relevant parameters according to the updated data, and re-execute the adjustment of the raindrop speed. This continuous dynamic adjustment can cope with changes in the external environment and ensure that the raindrop speed is always within the target speed range; through multiple iterations, the control algorithm gradually optimizes the control strategy of the raindrop speed. Each iteration will correct the relevant parameters according to actual feedback to narrow the gap between the raindrop speed and the target speed. After multiple adjustments, even if the external environment fluctuates greatly, the raindrop speed can always be close to the target range. Finally, the control strategy will achieve the best speed control effect in a changing environment. As a preferred embodiment of the above, Figure 6 As shown in the figure, a feedback mechanism is introduced to adjust the raindrop speed in real time and perform periodic optimization based on the feedback of historical data, including:

[0105] A10: Based on the real-time monitored raindrop speed and environmental conditions, analyze the deviation between the current raindrop speed and the predetermined target speed and make immediate adjustments; A20: Store the real-time monitoring data, adjustment parameters and environmental condition data to generate a historical data set;

[0106] A30: By periodically analyzing historical data sets, applying optimization algorithms, evaluating the effectiveness of each parameter, extracting regulation patterns related to environmental changes, and optimizing control algorithms;

[0107] A40: A dual feedback mechanism combining instant feedback and historical data optimization is used to dynamically iterate and update the control strategy.

[0108] Specifically, first, by monitoring the raindrop velocity and external environmental conditions (such as wind speed, air pressure, etc.) in real time, the difference between the actual raindrop velocity and the predetermined target velocity is compared. When a deviation is found, the relevant parameters, such as the power of the injection device, the nozzle diameter or the air flow velocity, are immediately adjusted to quickly correct the raindrop velocity to bring it close to the target range. This step ensures that the raindrop velocity can respond quickly to external changes and remain within a reasonable range; then, while adjusting the raindrop velocity, the real-time monitored raindrop velocity, external environmental conditions and adjusted parameters are all recorded and stored to form a historical data set, which will provide a basis for subsequent analysis and optimization; then, the stored historical data sets are regularly analyzed, and by applying optimization algorithms, the effects of different adjustment parameters can be evaluated to identify specific external Which parameter adjustments are most effective under certain conditions? Based on these analysis results, the adjustment patterns related to changes in the external environment can be extracted to provide a scientific basis for further optimizing the control algorithm. The purpose of periodic analysis is to continuously improve the control accuracy and adapt the control algorithm to complex and changing environments. Finally, through the dual feedback mechanism of instant feedback and historical data analysis, the control strategy can be continuously iterated and updated. Instant feedback allows rapid adjustment of the raindrop velocity, while historical data optimization provides in-depth analysis support for long-term adjustment. The dual feedback mechanisms complement each other to ensure that the control strategy can be optimized when external conditions change and maintain precise control of the raindrop velocity under different environmental conditions. Through this dynamic iterative update method, the control strategy can be continuously improved to ensure the accuracy and stability of the test process.

[0109] As a preferred embodiment of the above, Figure 7 As shown in the figure, according to the needs of different stages of the experiment, rough regulation is carried out in the early stage and fine adjustment is implemented in the key stage, including:

[0110] B10: In the initial stage of the test, a rough adjustment is made by adjusting the raindrop generation method, injection power and airflow parameters to make the raindrop speed fall within the allowable interval of the target speed range. The adjustment does not make fine processing for individual variables;

[0111] B20: monitors the speed of raindrops and external environmental parameters in real time, determines whether the speed of raindrops is within the target speed range, and makes necessary rough adjustments to relevant parameters when there is a large deviation;

[0112] B30: When the test enters the critical stage, the adjustment range is gradually reduced according to the monitoring data, and the air flow speed, direction and injection pressure are finely adjusted. The critical stages include the precise testing stage, the extreme environment simulation stage and the key parameter measurement stage.

[0113] Specifically, at the beginning of the test, the main goal is to make the raindrop speed roughly fall within the target range. At this time, rough adjustments are made by adjusting the raindrop generation method, the power of the spray device, and the basic parameters of the airflow (such as wind speed and direction). The focus of this stage is to quickly achieve preliminary control of the raindrop speed without overly fine processing. Through the rough adjustment of these basic parameters, it can be ensured that the raindrop speed falls within a relatively wide allowable range, laying the foundation for subsequent fine adjustments. Next, the movement speed of the raindrops and external environmental conditions (such as wind speed, air pressure, humidity, etc.) are monitored in real time to ensure that the raindrop speed remains within the predetermined target range. If the speed is detected to deviate from the set range and the deviation is large, necessary rough adjustments need to be made. These adjustments are still based on a large range of parameter adjustments, such as increasing the spray power or adjusting the airflow direction to quickly return the raindrop speed to the target range. The adjustments at this stage do not need to be too fine, as long as the raindrop speed remains within the allowable error range.When the test enters a critical stage, such as precise testing, extreme environment simulation or key parameter measurement, higher control accuracy is required, and fine adjustment is required at this time. The precise testing stage is a stage in which a specific parameter or behavior is measured and controlled with high precision during the test. At this stage, the test requires extremely high precision, and all environmental variables, parameter adjustments and measurements must be strictly controlled to ensure the accuracy of the measurement results. This usually involves fine adjustment and recording of key parameters such as raindrop velocity and blade surface wear. Any slight error may affect the final test results. The extreme environment simulation stage is to evaluate the performance of wind turbine blades under extreme conditions by artificially creating extreme external conditions (such as extremely high or extremely low temperatures, high humidity, strong winds or heavy rains, etc.). At this stage, the test simulates the operating state of the blades under extreme climatic conditions. The purpose is to test the corrosion resistance, fatigue resistance and other extreme environmental tolerance of the blades. The key to this stage is to reproduce the real extreme conditions and ensure that the test environment is consistent with the actual operation of the wind turbine blades. The key parameter measurement phase is the core of the test, which aims to measure and record the key parameters of wind turbine blades and related systems under various test conditions. The key parameters may include raindrop velocity, erosion degree of blade surface, material wear rate, dynamic changes of wind speed on blades, etc. This phase is usually carried out on the basis of precise testing phase and extreme environment simulation phase. The accuracy and consistency of data are the key points. By measuring these key parameters, we can deeply understand the performance of wind turbine blades and provide necessary data support for subsequent analysis and optimization. According to the real-time monitored data, the adjustment range is gradually reduced to accurately control the speed and direction of the airflow and the pressure of the injection device. Different from the rough adjustment in the early stage, the fine adjustment will strictly control the small changes of each parameter to ensure that the raindrop velocity can fully meet the strict test requirements in the key test stage. Through fine adjustment, the test environment with high precision requirements can be met to ensure accurate test results in the key stage. ;

[0114] Embodiment 2

[0115] Based on the same inventive concept as the raindrop velocity control method for a wind turbine blade corrosion resistance test in the aforementioned embodiment, the present invention further provides a raindrop velocity control system for a wind turbine blade corrosion resistance test, the system comprising:

[0116] The parameter model building module determines the target range of raindrop velocity based on the operating environment of wind turbine blades and establishes a target parameter model for controlling raindrop velocity. The raindrop velocity initial adjustment module adjusts the raindrop velocity to a range close to the target range by regulating the raindrop generation method and initial power based on the target parameters.

[0117] The dynamic data acquisition module monitors the speed and external environmental conditions of raindrops in real time and acquires the corresponding dynamic data;

[0118] The data iteration adjustment module dynamically adjusts the raindrop speed using the control algorithm based on the real-time monitoring data, and adjusts the raindrop speed control strategy when the external environment changes, and performs multiple iterations of speed adjustment;

[0119] The feedback mechanism optimization module introduces a feedback mechanism to adjust the raindrop speed in real time and perform periodic optimization based on the feedback of historical data. According to the needs of different stages of the experiment, rough regulation is performed in the early stage and fine adjustment is implemented in the critical stage.

[0120] The control system in the present invention can effectively implement the raindrop velocity control method for wind turbine blade corrosion resistance test, and the technical effects that can be achieved are as described in the above embodiments, which will not be repeated here.

[0121] As a preferred embodiment of the above, the parameter model building module includes:

[0122] An operating parameter collection unit collects external meteorological data in the operating environment of the wind turbine blades and operating parameters of the wind turbine blades;

[0123] An initial velocity calculation unit calculates the initial velocity range of raindrops under different external conditions based on the collected external meteorological data;

[0124] The speed change evaluation unit analyzes the influence of external environmental factors on the raindrop speed based on external meteorological data, calculates the change of raindrop speed under different conditions, and evaluates the relative speed change between the blade and the raindrop;

[0125] The model verification and optimization unit integrates environmental data, initial raindrop velocity and blade motion characteristics to establish a multi-dimensional target parameter model for controlling raindrop velocity, and verifies and optimizes the model.

[0126] Similarly, the above-mentioned optimization schemes for the system can also respectively achieve the optimization effects corresponding to the method in Example 1, which will not be repeated here.

[0127] Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present application as defined therein, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A raindrop velocity control method for wind turbine blade corrosion resistance test, characterized in that: include: Based on the operating environment of wind turbine blades, the target range of raindrop velocity is determined, and a target parameter model for controlling raindrop velocity is established; Based on the target parameters, the raindrop speed is adjusted to a range close to the target by regulating the raindrop generation method and initial power; Monitor the speed and external environmental conditions of raindrops in real time and obtain corresponding dynamic data; Based on real-time monitoring data, the control algorithm is used to dynamically adjust the raindrop speed. When the external environment changes, the raindrop speed control strategy is adjusted to perform multiple iterations of speed adjustment. A feedback mechanism is introduced to adjust the raindrop speed in real time and perform periodic optimization based on feedback from historical data. According to the needs of different stages of the experiment, rough regulation is carried out in the early stage and fine adjustment is implemented in the critical stage.

2. The raindrop velocity control method for wind turbine blade corrosion resistance test according to claim 1 is characterized in that: Based on the operating environment of wind turbine blades, the target range of raindrop velocity is determined, and a target parameter model for controlling raindrop velocity is established, including: Collect external meteorological data and wind turbine blade operating parameters in the wind turbine blade operating environment; Calculating the initial velocity range of raindrops under different external conditions based on the collected external meteorological data; Based on the external meteorological data, analyzing the influence of external environmental factors on the raindrop velocity, calculating the change of the raindrop velocity under different conditions, and evaluating the relative velocity change between the blade and the raindrop; Based on the environmental data, initial raindrop velocity and blade motion characteristics, a multi-dimensional target parameter model for controlling raindrop velocity is established, and the model is verified and optimized.

3. The raindrop velocity control method for wind turbine blade corrosion resistance test according to claim 2 is characterized in that: The calculation formula of the terminal velocity of the raindrop is: Where v is the terminal velocity of the raindrop, that is, the maximum velocity reached by the raindrop when falling in the air, m is the mass of the raindrop, g is the acceleration of gravity, ρ is the air density, A is the windward cross-sectional area of ​​the raindrop, and C is the windward cross-sectional area of ​​the raindrop. d is the air resistance coefficient.

4. The raindrop velocity control method for wind turbine blade corrosion resistance test according to claim 1, characterized in that: Based on the target parameters, the raindrop speed is adjusted to a range close to the target by regulating the raindrop generation method and initial power, including: According to the target parameter model, the nozzle diameter, the spray pressure or the droplet generating device is adjusted to generate raindrops with a predetermined size and mass, and the generation frequency of the raindrops is controlled; According to the target speed range, the air pressure or the dynamic parameters of the injection device are adjusted to give the raindrops an initial speed to reach the target speed range; By adjusting the falling height of raindrops, gravity is used to accelerate raindrops; During the falling process of raindrops, airflow is applied, and the speed of raindrops is adjusted by adjusting the wind speed and airflow direction. The speed of raindrops is monitored in real time, and the raindrop generation parameters, initial dynamics and airflow regulation parameters are adjusted according to the monitoring results.

5. The raindrop velocity control method for wind turbine blade corrosion resistance test according to claim 1, characterized in that: Monitor the speed and external environmental conditions of raindrops in real time and obtain corresponding dynamic data, including: Dynamically collect the speed of raindrops and external environmental parameters, including but not limited to the speed of raindrops, wind speed, air pressure and humidity; Based on the collected data, the speed of raindrops in motion and its changes affected by external environmental conditions are continuously monitored; The collected data is processed and analyzed to determine the difference between the raindrop velocity and the target velocity range. The relevant parameters are adjusted according to the analysis results to control the raindrop velocity to be within the predetermined range.

6. The raindrop velocity control method for wind turbine blade corrosion resistance test according to claim 1, characterized in that: Based on real-time monitoring data, the control algorithm is used to dynamically adjust the raindrop speed. When the external environment changes, the raindrop speed control strategy is adjusted to perform multiple iterations of speed adjustment, including: Analyze the speed of raindrops and external environmental parameters in real time to identify the difference between the current speed and the target speed range; Based on the analysis results, the control algorithm is used to dynamically adjust the raindrop speed and adjust the relevant parameters to match the target speed; When the external environmental parameters change, the data is updated, the parameters of the control algorithm are adjusted, and the adjustment process of the raindrop speed is repeated; Through multiple iterative adjustments, the raindrop velocity control strategy is continuously optimized under the condition of external environmental fluctuations until the raindrop velocity always approaches the target range under different conditions.

7. The raindrop velocity control method for wind turbine blade corrosion resistance test according to claim 1, characterized in that: Introduce a feedback mechanism to adjust the raindrop speed in real time and perform periodic optimization based on feedback from historical data, including: Based on the real-time monitoring of raindrop velocity and environmental conditions, the deviation between the current raindrop velocity and the predetermined target velocity is analyzed and immediate adjustments are made; Store real-time monitoring data, adjustment parameters and environmental condition data to generate historical data sets; By periodically analyzing the historical data set, applying the optimization algorithm, evaluating the effectiveness of each parameter, extracting the regulation mode related to environmental changes, and optimizing the control algorithm; The control strategy is dynamically updated by combining the dual feedback mechanism of instant feedback and historical data optimization.

8. The raindrop velocity control method for wind turbine blade corrosion resistance test according to claim 1, characterized in that: According to the needs of different stages of the experiment, rough regulation is carried out in the early stage and fine adjustment is implemented in the key stage, including: In the initial stage of the test, a rough adjustment is made by adjusting the raindrop generation method, the jet power and the airflow parameters so that the raindrop velocity falls within the allowable interval of the target velocity range. The adjustment does not perform fine processing on individual variables. Monitor the speed of raindrops and external environmental parameters in real time to determine whether the speed of raindrops is within the target speed range, and make necessary rough adjustments to relevant parameters when there is a large deviation; When the test enters the critical stage, the adjustment range is gradually reduced according to the monitoring data, and the air flow speed, direction and injection pressure are finely adjusted. The critical stage includes the precise testing stage, the extreme environment simulation stage and the key parameter measurement stage.

9. A raindrop velocity control system for wind turbine blade corrosion resistance test, characterized in that: The system comprises: The parameter model building module determines the target range of raindrop velocity based on the operating environment of the wind turbine blades and establishes a target parameter model for controlling the raindrop velocity; The raindrop velocity initial adjustment module adjusts the raindrop velocity to a close target range by regulating the raindrop generation method and initial power based on the target parameters; The dynamic data acquisition module monitors the speed and external environmental conditions of raindrops in real time and acquires the corresponding dynamic data; The data iteration adjustment module dynamically adjusts the raindrop speed using the control algorithm based on real-time monitoring data, and adjusts the raindrop speed control strategy when the external environment changes, and performs multiple iterations of speed adjustment; The feedback mechanism optimization module introduces a feedback mechanism to adjust the raindrop speed in real time and perform periodic optimization based on the feedback of historical data. According to the needs of different stages of the experiment, rough regulation is performed in the early stage and fine adjustment is implemented in the critical stage.

10. The raindrop velocity control system for wind turbine blade corrosion resistance test according to claim 9, characterized in that: The parameter model building module includes: An operating parameter collection unit collects external meteorological data in the operating environment of the wind turbine blades and operating parameters of the wind turbine blades; An initial velocity calculation unit, which calculates the initial velocity range of raindrops under different external conditions according to the collected external meteorological data; a speed change evaluation unit, which analyzes the influence of external environmental factors on the raindrop speed based on the external meteorological data, calculates the change of the raindrop speed under different conditions, and evaluates the relative speed change between the blade and the raindrop; The model verification and optimization unit integrates environmental data, initial raindrop velocity and blade motion characteristics to establish a multi-dimensional target parameter model for controlling raindrop velocity, and verifies and optimizes the model.

Images