A wind power blade static multi-point cooperative loading control system and method

Abstract

This invention relates to the field of static multi-point coordinated loading of wind turbine blades, and discloses a static multi-point coordinated loading control system for wind turbine blades, including a sensing module, an execution module, and a central control unit. The sensing module is used to collect real-time loading data of the loading nodes on the blade. The central control unit includes a real-time calculation module and a feedforward control module. The real-time calculation module calculates the real-time stiffness based on the real-time tension value and the real-time displacement value. Preset data is input, and the feedforward control module calculates the feedforward control quantity based on the preset data, including the target tension curve and the structural coupling relationship. The execution module initially adjusts the loading speed on the loading nodes based on the feedforward control quantity. This establishes a representation model of "force-displacement-stiffness" coordination, constructs an intelligent control architecture that integrates multi-dimensional sensing data and performs feedforward compensation based on the structural coupling relationship, and forms an adaptive closed-loop control based on the real-time state of the blade.

Description

Technical Field

[0001] This invention relates to the field of static multi-point coordinated loading of wind turbine blades, and specifically to a static multi-point coordinated loading control system and method for wind turbine blades. Background Technology

[0002] Structural performance testing of large wind turbine blades is a crucial step in ensuring the safety and power generation efficiency of megawatt-class wind turbines. With the increasing capacity of individual wind turbine units, blade lengths have exceeded 100 meters, exhibiting complex mechanical characteristics such as high flexibility and nonlinear deformation. Static loading tests on these ultra-long blades place extremely high demands on the accuracy, response speed, and coordinated control capabilities of the loading system.

[0003] Currently, the multi-point crane vertical loading method is the main approach used in China for static loading tests of wind turbine blades. However, this technical solution has the following problems in practical applications: 1. Data collection is limited to a single dimension, failing to detect changes in structural state: Existing systems primarily focus on a single dimension of load (tension) for data acquisition, generally using ordinary meters. This results in low sampling frequencies (typically below 1Hz) and large measurement errors (typically ±1.0%). Due to the lack of synchronous acquisition of displacement at the loading point, the system cannot obtain information on the positional changes of the blades during the loading process, causing the control system to operate in a "blind" state and making it difficult to perceive the real-time response of the blade structure.

[0004] 2. Multi-point loading causes severe coupling interference, and there is a lack of active suppression methods: Due to their high flexibility, wind turbine blades exceeding 100 meters in length exhibit strong cross-linking coupling effects among the loading nodes distributed along the span when subjected to synchronous multi-point loading. For example, load adjustments at one loading point can be transmitted to other loading points through blade structural deformation, causing load fluctuations. Existing control systems mostly employ decoupled control methods based on fixed mathematical models, which belong to a passive, lag-based "sensing-response" mode. When coupling disturbances occur, the system can only correct after the deviation has occurred, and cannot actively suppress the disturbance before it affects loading accuracy.

[0005] 3. Fixed control parameters make it difficult to adapt to dynamic loading processes: Traditional control algorithms (such as PID control) rely heavily on offline debugging and manual experience for parameter tuning, and once set, they remain fixed. However, the stiffness of blades changes nonlinearly with increasing load during loading. This time-varying characteristic makes it difficult for fixed-parameter control strategies to maintain optimal control performance throughout the entire loading cycle, easily leading to response lag or overshoot oscillations.

[0006] 4. Low loading accuracy poses a risk of structural damage: Due to issues such as incomplete data perception, insufficient suppression of coupling interference, and poor adaptability of control parameters, the loading accuracy of existing systems is insufficient to meet the testing requirements of megawatt-class blades. Severe coupling interference can directly trigger sudden load changes, leading to localized stress concentration on the blades and even causing structural damage, thus affecting test safety and blade lifespan. Summary of the Invention

[0007] The present invention aims to provide a static multi-point collaborative loading control system for wind turbine blades, in order to establish a representation model of "force-displacement-stiffness" collaboration, construct an intelligent control architecture that integrates multi-dimensional sensing data and performs feedforward compensation based on structural coupling relationship, and form an adaptive closed-loop control based on the real-time state of the blade.

[0008] To achieve the above objectives, the present invention adopts the following technical solution: a static multi-point collaborative loading control system and method for wind turbine blades, comprising a sensing module, an execution module and a central control unit, wherein the sensing module is used to collect real-time loading data of the loading nodes on the blade, and the real-time loading data includes real-time tension value and real-time displacement value. The central control unit is connected to the sensing module and the execution module respectively. The central control unit includes a real-time calculation module and a feedforward control module. The real-time calculation module calculates the real-time stiffness based on the real-time tension value and the real-time displacement value. The feedforward control module calculates the feedforward control quantity based on the preset data, which includes the target tension curve and the structural coupling relationship. The execution module initially adjusts the loading speed on the loading node based on the feedforward control quantity.

[0009] The beneficial effects of this plan are: 1. Achieve multi-dimensional force-displacement sensing and real-time characterization of the supporting structure's state: By setting up a sensing module to synchronously collect real-time tension and displacement values ​​at the loading nodes, the limitation of existing technologies that only collect single tension data is overcome. The central control unit calculates the blade stiffness in real time based on the tension and displacement data, enabling the control system to sense changes in the structural state of the blade during loading, thus providing a data foundation for adaptive control.

[0010] 2. Introduce a feedforward control mechanism to actively suppress coupling interference: By setting up a feedforward control module, the feedforward control quantity is calculated in advance based on preset data including structural coupling relationships. The execution module then adjusts the loading speed based on this feedforward control quantity. This mechanism can proactively compensate for coupling disturbances before they actually affect the loading accuracy, transforming the traditional passive "sensing-response" control mode into a proactive "prediction-compensation" control mode, significantly improving the coordination and stability of multi-point loading. Compared to traditional single closed-loop control, the coupling disturbance suppression rate is improved by ≥80%, avoiding blade damage caused by local overload.

[0011] 3. Improve control precision and loading efficiency: The real-time calculation module provides stiffness values ​​that reflect the dynamic characteristics of the blade, while the feedforward control module performs pre-adjustments based on structural coupling relationships. Their collaborative operation enables the control system to adaptively respond to nonlinear changes in blade stiffness and coupling interference between nodes. Compared to existing fixed-parameter control methods, this scheme reduces the number of oscillations and stabilization time during loading, improves load control accuracy, and lowers the risk of blade structural damage due to sudden load changes. The force control error is ≤±0.5% FS, far superior to the traditional ±1%-±2% FS level.

[0012] 4. Enhance system robustness and scenario adaptability: Since feedforward control does not rely on a precise mathematical model, but rather on a pre-defined structural coupling relationship for compensation, and real-time stiffness feedback can correct model deviations during the loading process, this scheme has a strong adaptability to individual blade differences, installation deviations, and different test conditions, overcoming the limitations of traditional methods that rely on human experience and fixed models.

[0013] Furthermore, the preset data also includes loading time, structural coupling relationships including full-load displacement and full-load tension at the loading nodes, target tension curve including target tension value, and feedforward control variables including structural coupling feedforward. The calculation formula is: ; - Full load displacement; - Full load tensile force; - Loading time; -Real-time tension value; - Target tensile force value.

[0014] With this setup, the maximum displacement and maximum tension that the blade can withstand at the corresponding loading node can be obtained through experiments or computer simulations, i.e., full-load displacement and full-load tension. The required tension value can be obtained based on the difference between the real-time tension value and the target tension value. Multiply the ratio of the required change in tension to the full-load tension by the full-load displacement to obtain the displacement required to load the blade. The loading speed is obtained by dividing the displacement required to load the blade by the loading time. The execution module is usually a winch, so the loading speed is usually the motor speed of the winch.

[0015] In existing technologies, the required tension value is usually directly multiplied by a coefficient to obtain the motor speed. However, in this solution, the required speed is calculated by combining the different full-load displacement and full-load tension at each loading node of the blade. That is, the feedforward control quantity is calculated in advance based on preset data that includes structural coupling relationships, thereby making the feedforward control quantity more accurate. Furthermore, the preset data also includes the load proportional feedforward coefficient and the average lag time of the execution module, and the feedforward control quantity includes the load target feedforward. and system dynamic feedforward and system dynamic feedforward The calculation formulas are as follows: ; ; -Load proportional feedforward coefficient; -Real-time tension value; -Target tensile force value; τ - Average delay time of the execution module.

[0016] With this setup, the required change in tension is calculated based on the target tension value and the real-time tension value; thus, the load target feedforward is calculated; in order to compensate for the inherent lag of the motor driver of the execution unit, the average lag time of the execution module is considered, thereby obtaining the system dynamic feedforward.

[0017] Furthermore, the preset data also includes stiffness proportional feedforward coefficients, and the feedforward control quantities include real-time stiffness feedforward. The calculation formula is: ; -Real-time stiffness; - Stiffness proportional feedforward coefficient.

[0018] The change in loading speed can be considered to be linearly related to the change in stiffness. Therefore, the difference between the real-time stiffness and the stiffness under full load is compared with the stiffness under full load, and multiplied by the stiffness proportional feedforward coefficient and the load target feedforward to obtain the real-time stiffness feedforward. This real-time stiffness feedforward is based on the real-time stiffness and is corrected accordingly.

[0019] Furthermore, feedforward control quantity The calculation formula is as follows: ; W1+W2+W3+W4=1; W1, W2, W3, W4 - Weighting coefficients.

[0020] Furthermore, the central control unit also includes a closed-loop feedback adjustment module. After the execution module makes initial adjustments, the closed-loop feedback adjustment module calculates the residual error based on the real-time tension value and the target tension value. The closed-loop feedback adjustment module adjusts the residual error through a PID algorithm. The formula for dynamically adjusting PID parameters is: , , - Initial PID parameters; ; -Real-time stiffness; - Initial stiffness.

[0021] This invention uses an improved PID algorithm for real-time adjustment to ensure that the loading accuracy meets the test requirements; the specific parameters of the above formula are obtained from the test; according to the formula, the adjustment principle of this scheme is: when the stiffness increases (the blade becomes harder), decrease Kp to avoid overshoot; when the stiffness decreases (the blade deformation increases), increase Ki to improve the response speed.

[0022] Real-time calculation of blade stiffness When the stiffness change rate is >10%, dynamically adjust the PID parameters. , , It adapts to the time-varying characteristics of parameters during blade deformation.

[0023] Furthermore, the closed-loop feedback adjustment module adjusts the residual error based on the closed-loop control quantity, and the closed-loop control quantity... The calculation formula is: ; - Residual error; - After anti-integral saturation treatment .

[0024] Anti-integral saturation refers to technical measures in control systems to prevent integral saturation, primarily addressing the problem of excessive accumulation of the integral term due to long-term controller deviation. When the load limit is reached or there is a large deviation, the accumulation of the integral term leads to overshoot during unloading. This is addressed using existing anti-integral saturation logic. This prevents the accumulation of integral items from causing overshoot during unloading.

[0025] Furthermore, the central control unit includes a full-condition smooth transition module. The operating conditions of the central control unit include steady-state operating conditions and dynamic operating conditions. When the operating conditions of the central control unit are switched, the full-condition smooth transition module is used to eliminate abrupt changes in the control quantity. The control quantity includes the weighting coefficient of the feedforward control quantity and the PID parameters. Based on the two control quantities before and after the operating condition switch, the full-condition smooth transition module obtains the intermediate value through linear interpolation or exponential interpolation. The full-condition smooth transition module fits the discrete control quantity and the intermediate value into a smooth curve.

[0026] Furthermore, the full-condition smooth transition module sets the maximum control quantity and the maximum control quantity rate. When the control quantity exceeds the maximum control quantity, the control quantity is set to be equal to the maximum control quantity; when the rate of change of the control quantity exceeds the maximum control quantity rate, the rate of change of the control quantity is set to be equal to the maximum control quantity rate.

[0027] To eliminate abrupt changes in control quantities during operating condition switching, this invention sets up a smooth transition module for all operating conditions. Through strategies such as state recognition, parameter interpolation, curve smoothing, and limiting maximum values, it achieves a shock-free transition during loading and unloading, avoiding local overload of blades or system oscillation.

[0028] The present invention aims to provide a static multi-point collaborative loading control method for wind turbine blades. Based on a static multi-point collaborative loading control system for wind turbine blades, an intelligent control architecture is constructed that integrates multi-dimensional sensing data and performs feedforward compensation based on structural coupling relationship, forming an adaptive closed-loop control based on the real-time state of the blade.

[0029] A method for static multi-point coordinated loading control of wind turbine blades includes the following steps: Step 1: Prepare the blades and a static multi-point coordinated loading control system for wind turbine blades. The central control unit maintains a steady-state operating condition. =0, =0; Step 2: Send a load or unload command to the central control unit. The feedforward control module calculates the feedforward control quantity, and the execution module performs the load according to the feedforward control quantity. Step 3: The central control unit enters dynamic operating mode. >0, >0; The feedforward control module calculates the feedforward control quantity, and the execution module performs loading based on the feedforward control quantity.

[0030] The feedforward weights are dynamically optimized according to the operating conditions, maintaining optimal control performance in both steady-state and dynamic conditions.

[0031] This invention has a certain degree of fault tolerance and adaptability, good robustness, and effectively avoids the tedious process of traditional algorithms that require precise debugging of PID parameters for different blade types one by one, greatly reducing debugging costs and time, and improving the system's adaptability to diverse test scenarios. Attached Figure Description

[0032] Figure 1 Here is the algorithm flow chart for Example 1; Figure 2 This is a schematic diagram of the execution module in Example 1; Figure 3 This is a schematic diagram of blade loading in Example 1. Detailed Implementation

[0033] The following detailed description illustrates the specific implementation method: Example 1 Example 1 is basically as follows Figures 1-3 As shown: A static multi-point collaborative loading control system for wind turbine blades includes a central control unit, several sensing modules, and several execution modules. The application is for wind turbine blades, such as... Figure 3 As shown, the blade is equipped with several loading nodes, and each loading node corresponds to a sensing module and an execution module.

[0034] The execution module includes a loading device, such as Figure 2 As shown, in this embodiment, the loading device is a winch, with a fixed pulley bolted to it. A steel wire rope is wound around the winch, and after being turned by the fixed pulley, the steel wire rope connects to the corresponding loading node. The winch includes servo motors, each driven one-to-one by an independent CU310-2PN servo driver. Protocol conversion between EtherCAT and PROFINET buses is achieved through a Beckhoff EL6631 gateway module, completing the network integration of the entire servo system. In this embodiment, the control variables are all speed control parameters for the servo motors.

[0035] The sensing module includes a force sensor with a range of 0-400kN and an accuracy of ±0.1%FS, and a wire displacement sensor with a resolution of 0.01mm. The force sensor is positioned between the wire rope and the blade, while the wire displacement sensor is positioned within the loading node range on the blade. All sensors have the same sampling frequency of ≥100Hz. The installation method of the force and displacement sensors is existing technology and will not be described further. The sensing module is used to collect real-time loading data from the loading nodes on the blade, including real-time tension and displacement values. The central control unit is connected to both the sensing module and the execution module. The central control unit is a PLC controller, which serves as the core control unit. It establishes real-time periodic communication with each CU310-2PN servo drive via the PROFINET bus with a 4ms cycle. The PLC controller receives control commands such as start, stop, and target angle from the host computer via the ADS protocol and sends them to each servo motor simultaneously. At the same time, it collects feedback data on the actual speed, actual position, and actual output torque of the servo motor in real time to achieve closed-loop precise control of the servo system.

[0036] The algorithm of the central control unit is as follows Figure 1 As shown, it includes a real-time calculation module, a feedforward control module, a closed-loop feedback adjustment module, and a full-condition smooth transition module; The real-time calculation module calculates the real-time stiffness based on the real-time tension and displacement values; the formula is as follows: ; - The difference between the two most recent real-time tensile force values; - The difference between the two most recent real-time displacement values; 1) Input preset data. The feedforward control module calculates the feedforward control quantity based on the preset data. The preset data includes loading time, load proportional feedforward coefficient, stiffness proportional feedforward coefficient, average lag time of the execution module, weighting coefficient, target tension curve, and structural coupling relationship. The structural coupling relationship includes the full-load displacement and full-load tension at the loading node. The full-load displacement and full-load tension are obtained through experiments or computer simulations, showing the maximum displacement and maximum tension that the blade can withstand at the corresponding loading node. The target tension curve includes the target tension value. Feedforward control parameters include real-time stiffness feedforward. ;Structural coupling feedforward Target feedforward of payload and system dynamic feedforward Feedforward control quantity The calculation formula is: ; ; -Load proportional feedforward coefficient; -Real-time tension value; -Target tensile force value; τ - Average latency of the execution module; ; - Full load displacement; - Full load tensile force; - Loading time; -Real-time tension value; -Target tensile force value; ; -Real-time stiffness; -Stiffness proportional feedforward coefficient; ; W1+W2+W3+W4=1; W1, W2, W3, W4 - Weighting coefficients; The central control unit's operating conditions include steady-state and dynamic conditions. Under steady-state conditions, the execution module is not loaded. =0.5, =0.5, =0, =0; Under dynamic operating conditions, the module is loaded. =0.2, =0.1, =0.5, =0.2; The execution module initially adjusts the motor speed of the winch based on the feedforward control input.

[0037] 2) After the initial adjustment of the execution module, the closed-loop feedback adjustment module calculates the residual error based on the real-time tension value and the target tension value, and adjusts the residual error through the PID algorithm; The formula for calculating residual error is: : -Target tensile force value; -Real-time tension value; The formula for dynamically adjusting PID parameters is: , , - Initial PID parameters; ; -Real-time stiffness; - Initial stiffness; The calculation formula is: ; - Residual error; -After anti-integral saturation treatment The anti-integral saturation treatment is a current technology and will not be elaborated further.

[0038] The final closed-loop control quantity after fusing the closed-loop control quantity and the feedforward control quantity The calculation formula is: .

[0039] The execution module readjusts the winch motor speed based on the final closed-loop control value.

[0040] 3) When the operating conditions of the central control unit are switched, the full-condition smooth transition module is used to eliminate the sudden change of the control quantity so that the control quantity does not jump directly. The control quantity includes the weighting coefficient of the feedforward control quantity and the PID parameters. The full-condition smooth transition module obtains 100-200 intermediate values ​​based on the two control quantities before and after the operating condition switch through linear interpolation or exponential interpolation. In this embodiment, smooth interpolation is performed using the following formula: ; P(t) - Real-time parameter value; - Control variables before switching operating conditions; - Control quantities after switching operating conditions; - Smooth the time constant (e.g., 50-100ms); avoid system oscillations caused by sudden parameter changes.

[0041] The full-condition smooth transition module smooths and filters the curve of control quantity change to eliminate sharp peaks and abrupt changes, and uses cubic spline interpolation to fit discrete target points into a continuous and smooth curve.

[0042] The full-condition smooth transition module sets the maximum control quantity and the maximum control quantity rate. When the control quantity exceeds the maximum control quantity, the control quantity is set to be equal to the maximum control quantity; when the rate of change of the control quantity exceeds the maximum control quantity rate, the rate of change of the control quantity is set to be equal to the maximum control quantity rate, so as to avoid oscillations caused by sudden changes in the control quantity.

[0043] Similarly, the full-condition smooth transition module is also set with minimum control quantity and maximum control quantity rate. When the control quantity exceeds the maximum control quantity, the control quantity is set to be equal to the maximum control quantity; when the rate of change of the control quantity exceeds the maximum control quantity rate, the rate of change of the control quantity is set to be equal to the maximum control quantity rate.

[0044] By employing anti-integral saturation logic and smooth transition across all operating conditions, overshoot and oscillations during operating condition switching are eliminated, resulting in steady-state fluctuations ≤0.2%FS.

[0045] Example 2 Step 1: Prepare the blades and a static multi-point collaborative loading control system for wind turbine blades, and test the startup process; Step 1.1: The PLC controller sends control words to the frequency converters controlling all motors, causing them to perform error clearing and motor emergency stop (thus ensuring that all devices are in an initial, non-operating state).

[0046] Step 1.2: The PLC controller opens the brake switch of the motor at the corresponding loading point according to the loading point identifier set by the host computer, and sends a control word to the frequency converter controlling the motor to enable it and prepare to start motion control.

[0047] Step 1.3: The PLC controller sends a control word to the enabled motor control frequency converter to set the motor torque output limit, enable torque protection, and simultaneously put the motor into speed control mode, setting its speed to 0 to avoid starting shock.

[0048] Step 1.4: Initialize the multi-point collaborative loading control parameters, start the loading control module corresponding to the enabled motor, and record the current motor position and loading tension parameters (if an abnormal situation occurs, return to the initial state).

[0049] Step 1.5: Complete the test start-up process, the system is ready, start the closed-loop initial loading tension, and wait for the multi-point coordinated loading control command.

[0050] The central control unit maintains steady-state operation at this time. =0, =0; Step 2: When the host computer sends a load or unload command to the PLC controller through the ADS interface, the parameters of the feedforward control module are initialized, the feedforward control quantity of each loading node is calculated, the execution sequence of the entire loading or unloading process is generated, and the target closed-loop value is continuously modified according to the generated loading / unloading process execution sequence, and the loading closed-loop thread is put into the loading state. The execution module performs loading according to the feedforward control quantity. Step 3: The central control unit enters the dynamic operating condition, initiates structural coupling feedforward and real-time stiffness feedforward calculations, and obtains the results. Step 4: To ensure stable speed and avoid shocks, the calculated speed value is filtered and protected. The filtering and protection include setting a speed buffer queue, direction limitation, mean filtering, speed limiting protection, and finally outputting the final closed-loop control quantity.

[0051] Step 5: In the last 5 seconds before the loading state is about to end, interpolation calculations are used to slowly bring the speed to zero, achieving a smooth transition from the loading state to the steady state and avoiding system oscillations and overshoot caused by sudden parameter changes.

[0052] Safety protection: After step one is completed, the test flag is set to TRUE, and motor position limit protection, motor status monitoring, and load force deviation protection are started. Four shutdown strategies are built-in to deal with different emergency situations.

[0053] 1. Emergency Stop: Immediately stops the movement of all executing equipment and maintains the current state. After the emergency stop, all equipment control commands from Beckhoff's main controller and host computer are rejected until the reset operation is completed.

[0054] 2. Rapid Stop: In non-test mode, all movement of the actuators ceases; in test mode, the force closed-loop control of the motor stops, switching to motor position control commands to drive the equipment quickly back to the initial test position. After rapid stop, all device control commands from the Beckhoff main controller and the host computer are rejected until the reset operation is completed.

[0055] 3. Slow Stop: In non-test mode, all movement of the executing equipment stops; in test mode, the current test process is terminated, and a force closed-loop control method is adopted to drive the equipment to move towards the force closed-loop state at the start of the test. When the force value or position at the start is reached, the executing equipment stops moving. After slow stop, all equipment control commands from Beckhoff's main controller and host computer are rejected until the reset operation is completed.

[0056] 4. Pause Loading: Only effective in test mode. Pauses the test loading process until the reset operation is completed.

[0057] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific technical solutions and / or characteristics are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solutions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A static multi-point collaborative loading control system for wind turbine blades, characterized in that: It includes a sensing module, an execution module, and a central control unit. The sensing module is used to collect real-time loading data of the loading nodes on the blade. The real-time loading data includes real-time tension value and real-time displacement value. The central control unit is connected to the sensing module and the execution module respectively. The central control unit includes a real-time computing module and a feedforward control module. The real-time calculation module calculates the real-time stiffness based on the real-time tensile force and displacement values; the preset data is input, and the feedforward control module calculates the feedforward control quantity based on the preset data, which includes the target tensile force curve and the structural coupling relationship. The execution module initially adjusts the loading speed on the loading node based on the feedforward control quantity.

2. The wind turbine blade static multi-point cooperative loading control system according to claim 1, characterized in that: The preset data also includes loading time, structural coupling relationship including full-load displacement and full-load tension at the loading nodes, target tension curve including target tension value, and feedforward control variables including structural coupling feedforward. The calculation formula is: ； - Full load displacement; - Full load tensile force; - Loading time; -Real-time tension value; - Target tensile force value.

3. The wind turbine blade static multi-point cooperative loading control system according to claim 2, characterized in that: The preset data also includes the load proportional feedforward coefficient and the average lag time of the execution module. The feedforward control quantity includes the load target feedforward. and system dynamic feedforward and system dynamic feedforward The calculation formulas are as follows: ； ； -Load proportional feedforward coefficient; -Real-time tension value; -Target tensile force value; τ - Average delay time of the execution module.

4. The wind turbine blade static multi-point cooperative loading control system according to claim 3, characterized in that: The preset data also includes stiffness proportional feedforward coefficients, and the feedforward control quantities include real-time stiffness feedforward. The calculation formula is: ； -Real-time stiffness; - Stiffness proportional feedforward coefficient.

5. A static multi-point cooperative loading control system for wind turbine blades according to claim 4, characterized in that: Feedforward control quantity The calculation formula is as follows: ； W1+W2+W3+W4=1; W1, W2, W3, W4 - Weighting coefficients.

6. The wind turbine blade static multi-point cooperative loading control system according to claim 1, characterized in that: The central control unit also includes a closed-loop feedback adjustment module. After the execution module makes initial adjustments, the closed-loop feedback adjustment module calculates the residual error based on the real-time tension value and the target tension value. The closed-loop feedback adjustment module adjusts the residual error through a PID algorithm. The formula for dynamically adjusting PID parameters is: , , - Initial PID parameters; ； -Real-time stiffness; - Initial stiffness.

7. A static multi-point cooperative loading control system for wind turbine blades according to claim 6, characterized in that: The closed-loop feedback control module adjusts the residual error based on the closed-loop control quantity. The calculation formula is: ； - Residual error; -After anti-integral saturation treatment .

8. The static multi-point coordinated loading control method for wind turbine blades according to claim 1, characterized in that: The central control unit includes a full-condition smooth transition module. The operating conditions of the central control unit include steady-state operating conditions and dynamic operating conditions. When the operating conditions of the central control unit are switched, the full-condition smooth transition module is used to eliminate abrupt changes in the control quantity. The control quantity includes the weighting coefficient of the feedforward control quantity and the PID parameters. Based on the two control quantities before and after the operating condition switch, the full-condition smooth transition module obtains the intermediate value through linear interpolation or exponential interpolation. The full-condition smooth transition module fits the discrete control quantity and the intermediate value into a smooth curve.

9. The static multi-point coordinated loading control method for wind turbine blades according to claim 8, characterized in that: The full-condition smooth transition module sets the maximum control quantity and the maximum control quantity rate. When the control quantity exceeds the maximum control quantity, the control quantity is set to be equal to the maximum control quantity; when the rate of change of the control quantity exceeds the maximum control quantity rate, the rate of change of the control quantity is set to be equal to the maximum control quantity rate.

10. A static multi-point collaborative loading control method for wind turbine blades, characterized in that, Includes the following steps: Step 1: Prepare the blades and a static multi-point coordinated loading control system for wind turbine blades. The central control unit maintains a steady-state operating condition. =0, =0; Step 2: Send a load or unload command to the central control unit. The feedforward control module calculates the feedforward control quantity, and the execution module performs the load according to the feedforward control quantity. Step 3: The central control unit enters dynamic operating mode. >0, >0; The feedforward control module calculates the feedforward control quantity, and the execution module performs loading based on the feedforward control quantity.

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