Wind power blade variable pitch system multi-working-condition loading simulation system and blade

Abstract

The invention discloses a wind power blade variable pitch system multi-working-condition loading simulation system and a blade, and the system comprises a blade simulation device, a multi-dimensional precise loading device, a variable pitch driving device, a multi-modal monitoring device, a data analysis device, a holographic environment simulation device, a digital twin platform, a transmission device and a control device. The blade simulation device, the multi-dimensional precise loading device, the variable pitch driving device, the multi-modal monitoring device, the data analysis device, the holographic environment simulation device, the digital twin platform and the transmission device are electrically connected with the control device; the system can comprehensively simulate the operation states of the wind power blade under different working conditions, provides all-around support for research, development and testing of a variable pitch system, accurately controls blade shape simulation through the multi-dimensional precise loading device, and monitors the blade state in real time through the multi-modal monitoring device, so that the test efficiency is improved. The system can obtain accurate test data and improve the test accuracy and reliability.

Description

Technical Field

[0001] The invention belongs to the technical field of wind power generation, and particularly relates to a multi-condition loading simulation system for a pitch system of a wind turbine blade and a blade. Background Art

[0002] As an important part of clean energy, wind power plays a crucial role in the global energy structure transformation. Wind turbine blades are the core components of wind turbines. The aerodynamic characteristics, structural strength, fatigue life, and control strategies of wind turbine blades directly determine the power generation efficiency and operation reliability of wind turbines. The pitch system, as an important control mechanism for wind turbine blades, adjusts the blade angle to adapt to different wind conditions, achieving power optimization and wind turbine protection. To improve the safety and adaptability of wind turbines, it is necessary to simulate and test the pitch system under various operating conditions. However, the current testing methods still have many limitations and are difficult to achieve a comprehensive evaluation of the pitch system of wind turbine blades. The main reason is that the current testing of the pitch system of wind turbine blades mainly relies on field tests, that is, in actual wind farms or specific outdoor test bases, the performance of wind turbine blades in the natural wind environment is measured. Although field tests can provide real operating data, their limitations are mainly reflected in the following aspects: uncontrollable natural conditions: environmental factors such as wind speed, wind direction, and airflow turbulence cannot be artificially set, and the test results are greatly affected by environmental changes, making it difficult to reproduce the same test conditions; limited test conditions: only some naturally occurring wind conditions such as normal operating conditions and gust conditions can be covered, but for special conditions such as extreme typhoon conditions, thunderstorm impact conditions, extreme temperature and humidity conditions, and sandstorm environment conditions, it is difficult to conduct effective tests in a short time; high test costs: wind turbine blades and pitch systems are large in size, and field tests require the construction of high-cost test platforms and are greatly affected by the weather, resulting in a long test cycle and high costs; complex data acquisition: field tests often involve multiple variables such as meteorological data, blade forces, structural vibrations, and pitch drive responses, and it is difficult to accurately measure them simultaneously. Secondly, laboratory simulation is a testing method for the pitch system of blades carried out in a controlled environment. Its core lies in using means such as wind tunnel tests, static loading tests, and simplified wind turbine model tests to simulate the operating characteristics of wind turbine blades under different conditions. However, the existing laboratory simulation methods have the following problems: limited operating condition range: traditional laboratory simulation equipment mainly focuses on single or limited operating conditions, and it is difficult for traditional laboratory equipment to accurately reproduce non-uniform and dynamic environment conditions such as high-turbulence wind conditions, extreme temperature and humidity changes, sand erosion, and lightning strikes.Environmental and structural separation test: Current laboratory tests usually conduct tests on environmental factors (temperature, humidity, wind field), blade structural dynamics (stress, deformation), and pitch control strategies separately, lacking an integrated test platform that can comprehensively simulate the interaction of environment-structure-control. For example, wind tunnel tests usually only focus on aerodynamic performance and cannot measure structural deformation and the response of the pitch drive system simultaneously. Static loading tests mainly test the stress distribution of blades under different loads and cannot reflect the dynamic changes in the real wind field. Insufficient dynamic response testing: Existing laboratory test equipment is difficult to accurately simulate the dynamic pitch process, such as the response delay of the pitch control system under gusts, the impact of high-frequency vibrations on blade life, and the impact of extreme temperature changes on the pitch drive mechanism. These dynamic factors are crucial for the long-term stability of wind turbines, but current laboratory methods are difficult to comprehensively evaluate their impacts. Additionally, the limitations of existing field tests and laboratory test methods are mainly caused by the following factors: Complexity of natural wind fields: The randomness of wind speed, wind direction, and turbulence characteristics is strong, making it difficult to fully reproduce in the laboratory. Physical limitations of laboratory equipment: Traditional experimental equipment mostly uses static or one-dimensional loading methods and lacks multi-axial dynamic loading capabilities. Limitations of environmental control systems: Existing laboratory environments are usually mainly maintained at constant temperature and humidity and cannot dynamically simulate the impacts of environmental factors such as temperature mutations, precipitation, and lightning on blades. Limitations of data acquisition technology: There is a lack of high-precision, real-time, and multi-modal monitoring means, and it is impossible to measure the coupling effects of multiple variables such as wind speed, load, temperature, humidity, material aging, and pitch drive response simultaneously. Summary of the Invention

[0003] The object of the present invention is to provide a multi-condition loading simulation system and blade for a pitch system of a wind turbine blade, so as to solve the technical defect in the prior art that it is impossible to comprehensively and accurately load and simulate the blade under various complex conditions.

[0004] To achieve the above object, the present invention adopts the following technical solutions: In the first aspect, a multi-condition loading simulation system for a pitch system of a wind turbine blade is provided, including: a blade simulation device, a multi-dimensional precision loading device, a pitch drive device, a multi-modal monitoring device, a data analysis device, a holographic environment simulation device, a digital twin platform, a transmission device, and a control device. The blade simulation device, the multi-dimensional precision loading device, the pitch drive device, the multi-modal monitoring device, the data analysis device, the holographic environment simulation device, the digital twin platform, and the transmission device are electrically connected to the control device; The blade simulation device is used for simulating the blade shape; the multi-dimensional precision loading device is used for controlling the blade shape simulation; the pitch drive device is used for controlling the pitch process; the multi-modal monitoring device is used for monitoring the blade state; the data analysis device is used for analyzing and processing data; the holographic environment simulation device is used for simulating different working states; the digital twin platform is used for constructing a blade model; the transmission device is used for data transmission.

[0005] Further, the blade simulation device includes a modular blade structure, a smart material component, an active deformation control component, and a nano-coating. The modular blade structure is made of carbon fiber reinforced composite material, glass fiber, and aramid fiber. The nano-coating covers the surface of the modular blade structure. The active deformation control component is electrically connected to the smart material component, and the smart material component is connected to the modular blade structure.

[0006] Further, the multi-dimensional precision loading device includes a main actuation system, an auxiliary actuation system, a force / torque sensor, and an intelligent control unit. The main actuation system is arranged on the loading base and is used for providing large-load simulation for the blade; the auxiliary actuation system is arranged on the blade support structure and is used for simulating high-frequency small-amplitude dynamic loads; the force / torque sensor is arranged at the blade root and is used for measuring the applied force and torque in real time; the braking control unit is used for performing closed-loop optimization on the loading process.

[0007] Further, the pitch drive device includes a drive unit, a transmission system, a cooling system, and a control system. The drive unit, the transmission system, and the cooling system are electrically connected to the control system.

[0008] Further, the multi-modal monitoring device includes a fiber Bragg grating sensing system, an acoustic emission detection system, a three-dimensional digital image system, an infrared thermal imaging system, and a wireless sensor network. Among them, the fiber Bragg grating sensor system is used for monitoring the blade strain and temperature distribution; the acoustic emission detection system is used for detecting internal cracks and micro-damage of the blade; the three-dimensional digital image system is used for tracking the blade deformation in real time; the infrared thermal imaging system is used for monitoring the temperature anomaly on the blade surface; the wireless sensor network is used for remote transmission of detected data.

[0009] Further, the data analysis device includes a hardware platform, a software architecture, an AI module, and a visualization platform. The hardware platform, the software architecture, the AI module, and the visualization platform are signal-connected. The AI module includes a deep reinforcement learning module, a convolutional neural network module, a long short-term memory network module, and a graph neural network module.

[0010] Furthermore, the holographic environment simulation device includes a temperature and humidity control system, a barometric pressure simulation system, a wind field simulation system, a precipitation simulation system, a solar radiation simulation system, and a lightning simulation system, and the humidity control system, the barometric pressure simulation system, the wind field simulation system, the precipitation simulation system, the solar radiation simulation system, and the lightning simulation system are signal-connected to each other.

[0011] Furthermore, the digital twin platform includes a model system, a data processing system, a virtual sensor network, and a visualization interaction system, and the model system, the data processing system, the virtual sensor network, and the visualization interaction system are signal-connected to each other.

[0012] Furthermore, the transmission device includes a data bus, a time synchronization system, an energy management system, and a safety emergency system, and the time synchronization system, the energy management system, and the safety emergency system are connected through the data bus.

[0013] In a second aspect, a blade is provided, which includes a blade body, on which a pitch system is installed. The blade is made of carbon fiber reinforced composite material, glass fiber, and aramid fiber, and a nano-coating is applied to the surface of the blade. The blade is simulated by the multi-condition loading simulation system for the pitch system of the wind turbine blade as described above.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The system integrates multiple functions such as blade simulation, multi-dimensional loading, pitch drive, multi-modal monitoring, data analysis, holographic environment simulation, and digital twin, and can comprehensively simulate the operating states of wind turbine blades under different conditions, providing comprehensive support for the research and development and testing of the pitch system. Through the multi-dimensional precision loading device to precisely control the blade shape simulation, and the multi-modal monitoring device to monitor the blade state in real time, the system can obtain accurate test data, improving the accuracy and reliability of the test.

[0015] 2. The modular blade structure enables the blade to be easily disassembled and replaced as needed, reducing the maintenance cost and time, and can quickly adjust the size, shape, and material of the blade according to different test requirements or wind field conditions, improving the flexibility and adaptability of the test; the use of carbon fiber reinforced composite material, glass fiber, and aramid fiber makes the blade have both high strength and rigidity while maintaining light weight, which helps to improve the overall efficiency and stability of the wind turbine unit.

[0016] 3. The main actuation system is installed on the loading base and can provide large-load simulation for the blade, which is crucial for testing the structural strength and stability of the blade under extreme wind conditions or heavy load conditions. Secondly, the auxiliary actuation system is installed on the blade support structure and can simulate high-frequency small-amplitude dynamic loads, which helps to evaluate the fatigue life and dynamic response characteristics of the blade under continuously changing wind conditions. In addition, the force / torque sensor is installed at the blade root and can measure the applied force and torque in real time, providing accurate and reliable input data for data analysis. This real-time measurement ability makes the test process more precise, capable of capturing the subtle changes in the blade during the force application process, and providing strong support for blade design and optimization.

[0017] 4. Integrating the drive unit, transmission system, cooling system, and control system together and enabling them to work collaboratively through electrical connection greatly simplifies the structure of the pitch drive device, improves the overall performance and reliability of the system, enables faster and more accurate information transmission between components, and has a faster response speed, which helps to improve the accuracy and timeliness of the pitch operation. Secondly, as the core of the entire pitch drive device, the control system can accurately control the output power and speed of the drive unit according to external conditions such as wind speed and wind direction and the operating state of the wind turbine. By precisely controlling the pitch process, rapid and accurate adjustment of the blade angle can be achieved, optimizing the power output of the wind turbine and improving the power generation efficiency.

[0018] 5. Monitoring the strain and temperature distribution of the blade through the fiber Bragg grating sensing system can provide important data for evaluating the structural safety and durability of the blade by understanding the deformation and temperature changes of the blade during the force application process in real time. The acoustic emission detection system can detect cracks and micro-damages inside the blade, and can timely detect potential damages even when there are no obvious signs on the blade surface, which helps to prevent sudden failure of the blade. The three-dimensional digital image system tracks the blade deformation in real time, providing intuitive information on the blade shape change, which helps to analyze the dynamic response characteristics of the blade. The infrared thermal imaging system monitors the temperature anomalies on the blade surface and can timely detect local temperature rises caused by friction, overload, or internal damages, providing clues for fault troubleshooting.

[0019] 6. The application of the data analysis device provides strong support for the intelligent development in the wind power field. Through intelligent data analysis, a deeper understanding of the operating state and performance of the blade can be achieved, providing a scientific basis for blade design, manufacturing, and operation and maintenance.

[0020] 7. The holographic environment simulation device can comprehensively simulate various natural environmental factors such as temperature, humidity, air pressure, wind speed, precipitation, solar radiation, and lightning, providing a near-real test environment for outdoor equipment such as wind turbine blades. This comprehensive environmental simulation ability enables researchers to accurately evaluate the performance of wind turbine blades under various extreme weather conditions in the laboratory without waiting for natural conditions to occur.

[0021] 8. The digital twin platform can build a highly realistic virtual model that accurately reflects the structure, function, and behavior of the physical entity, allowing in-depth understanding of its internal mechanism and working state without directly contacting the physical entity. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0023] Figure 1 Schematic structural diagram of the multi-condition loading simulation system for the pitch system of a wind turbine blade provided by the present invention; Figure 2 Schematic diagram of the blade simulation device in the multi-condition loading simulation system for the pitch system of a wind turbine blade provided by the present invention; Figure 3 Schematic diagram of the multi-dimensional precision loading device in the multi-condition loading simulation system for the pitch system of a wind turbine blade provided by the present invention; Figure 4 Schematic diagram of the pitch drive device in the multi-condition loading simulation system for the pitch system of a wind turbine blade provided by the present invention; Figure 5 Schematic diagram of the multi-modal monitoring device in the multi-condition loading simulation system for the pitch system of a wind turbine blade provided by the present invention; Figure 6 Schematic diagram of the data analysis device in the multi-condition loading simulation system for the pitch system of a wind turbine blade provided by the present invention; Figure 7 Schematic diagram of the holographic environment simulation device in the multi-condition loading simulation system for the pitch system of a wind turbine blade provided by the present invention; Figure 8 Schematic diagram of the digital twin platform in the multi-condition loading simulation system for the pitch system of a wind turbine blade provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. Components of the embodiments of the present invention generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations.

[0025] Therefore, the detailed description of the embodiments of the present invention provided in the drawings below is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of the present invention.

[0026] It should be noted that like reference numerals and letters denote like items in the following drawings. Therefore, once an item is defined in one drawing, it does not require further definition and explanation in subsequent drawings.

[0027] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper", "lower", "horizontal", "inner", etc. are used to indicate the orientation or positional relationship, it is based on the orientation or positional relationship shown in the drawings or the orientation or positional relationship in which the product of the invention is usually placed during use. This is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation of the present invention. In addition, terms such as "first", "second", etc. are only used for descriptive distinction and cannot be construed as indicating or implying relative importance.

[0028] In addition, if the term "horizontal" appears, it does not mean that the component is required to be absolutely horizontal, but it can be slightly inclined. For example, "horizontal" only means that its direction is more horizontal relative to "vertical", and does not mean that the structure must be completely horizontal, but it can be slightly inclined.

[0029] In the description of the embodiments of the present invention, it should also be noted that unless otherwise clearly specified and limited, if terms such as "set", "installed", "connected", "connected" are used, they should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0030] As an important part of clean energy, wind power plays a crucial role in the global energy structure transformation. Wind turbine blades are the core components of wind turbines. The aerodynamic characteristics, structural strength, fatigue life, and control strategies of the blades directly determine the power generation efficiency and operation reliability of wind turbines. As an important control mechanism for wind turbine blades, the pitch system adjusts the blade angle to adapt to different wind conditions, achieving power optimization and wind turbine protection. To improve the safety and adaptability of wind turbines, it is necessary to simulate and test the pitch system under various operating conditions. However, the current testing methods still have many limitations and are difficult to achieve a comprehensive evaluation of the pitch system of wind turbine blades. The main reason is that the current testing of the pitch system of wind turbine blades mainly relies on field tests, that is, in actual wind farms or specific outdoor test bases, the performance of wind turbine blades in the natural wind environment is measured. Although field tests can provide real operating data, their limitations are mainly reflected in the following aspects: uncontrollable natural conditions: environmental factors such as wind speed, wind direction, and airflow turbulence cannot be artificially set, and the test results are greatly affected by environmental changes, making it difficult to reproduce the same test conditions; limited test conditions: only some naturally occurring wind conditions such as normal operating conditions and gust conditions can be covered, but for special conditions such as extreme typhoon conditions, thunderstorm shock conditions, extreme temperature and humidity conditions, and sandstorm environment conditions, it is difficult to conduct effective tests in a short time; high test costs: wind turbine blades and pitch systems are large in size, and field tests require the construction of high-cost test platforms and are greatly affected by the weather, resulting in long test cycles and high costs; complex data acquisition: field tests often involve multiple variables such as meteorological data, blade forces, structural vibrations, and pitch drive responses, and it is difficult to accurately measure them simultaneously. Secondly, laboratory simulation is a testing method for the pitch system of blades carried out in a controlled environment. Its core lies in using means such as wind tunnel tests, static loading tests, and simplified wind turbine model tests to simulate the operating characteristics of wind turbine blades under different conditions. However, the existing laboratory simulation methods have the following problems: limited operating condition range: traditional laboratory simulation equipment mainly focuses on single or limited operating conditions, and it is difficult for traditional laboratory equipment to accurately reproduce non-uniform and dynamic environment conditions such as high-turbulence wind conditions, extreme temperature and humidity changes, sand erosion, and lightning strikes.Environment and structure separation test: Current laboratory tests usually conduct tests on environmental factors (temperature, humidity, wind field), blade structural dynamics (stress, deformation), and pitch control strategies separately, lacking an integrated test platform that can comprehensively simulate the interaction of environment-structure-control. For example, wind tunnel tests usually only focus on aerodynamic performance and cannot measure structural deformation and the response of the pitch drive system simultaneously. Static loading tests mainly test the stress distribution of the blade under different loads and cannot reflect the dynamic changes in the real wind field. Insufficient dynamic response testing: Existing laboratory test equipment is difficult to accurately simulate the dynamic pitch process, such as the response delay of the pitch control system under gusts, the impact of high-frequency vibration on blade life, and the impact of extreme temperature changes on the pitch drive mechanism. These dynamic factors are crucial for the long-term stability of wind turbines, but current laboratory methods are difficult to comprehensively evaluate their impacts. In addition, the limitations of existing field tests and laboratory test methods are mainly caused by the following factors: Complexity of natural wind fields: The randomness of wind speed, wind direction, and turbulence characteristics is strong, making it difficult to fully reproduce in the laboratory. Physical limitations of laboratory equipment: Traditional experimental equipment mostly uses static or one-dimensional loading methods and lacks multi-axial dynamic loading capabilities. Limitations of environmental control systems: Existing laboratory environments usually focus on constant temperature and humidity and cannot dynamically simulate the impacts of environmental factors such as sudden temperature changes, precipitation, and lightning on the blade. Limitations of data acquisition technology: Lack of high-precision, real-time, and multi-modal monitoring means, unable to measure the coupling effects of multiple variables such as wind speed, load, temperature, humidity, material aging, and pitch drive response simultaneously. To address the above technical deficiencies, the inventors provide a multi-parameter coupling test system and method for a wind turbine blade pitch system.

[0031] The following further describes the present invention in detail with reference to the accompanying drawings: In a first aspect, an embodiment of the present invention provides a multi-condition loading simulation system for a wind turbine blade pitch system, as Figure 1-8As shown in the figure, it includes a blade simulation device, a multi-dimensional precision loading device, a pitch drive device, a multi-modal monitoring device, a data analysis device, a holographic environment simulation device, a digital twin platform, a transmission device, and a control device. The blade simulation device, the multi-dimensional precision loading device, the pitch drive device, the multi-modal monitoring device, the data analysis device, the holographic environment simulation device, the digital twin platform, and the transmission device are electrically connected to the control device. Among them, the blade simulation device is used to simulate the blade shape; the multi-dimensional precision loading device is used to control the blade shape simulation; the pitch drive device is used to control the pitch process; the multi-modal monitoring device is used to monitor the blade state; the data analysis device is used to analyze and process data; the holographic environment simulation device is used to simulate different working states; the digital twin platform is used to construct a blade model; the transmission device is used for data transmission. By integrating advanced sensing, control, artificial intelligence, and digital twin technologies, this system realizes a comprehensive and accurate simulation of wind turbine blades under various complex working conditions. It can not only perform conventional static and dynamic load tests but also simulate the blade performance under extreme environmental conditions, greatly improving the comprehensiveness and reliability of the tests. Its modular design and intelligent control system make the device highly flexible and scalable, capable of adapting to wind turbine blades of different specifications and diverse test requirements. Moreover, by adopting artificial intelligence and digital twin technologies, this device also has the capabilities of adaptive optimization and predictive analysis, significantly improving the test efficiency and data value. This innovative design provides strong support for the research, development, optimization, and reliability assessment of wind turbine blades, and is expected to promote the rapid development of wind power technology, improve the overall performance and economic benefits of wind power systems.

[0032] Furthermore, as Figure 2 shown, the blade simulation device includes a modular blade structure, intelligent material components, an active deformation control component, and a nano-coating. The modular blade structure is made of carbon fiber-reinforced composite materials, glass fibers, and aramid fibers. The nano-coating covers the surface of the modular blade structure. The active deformation control component is electrically connected to the intelligent material components, and the intelligent material components are connected to the modular blade structure. During application, the total length range of the modular blade structure can be selected between ten meters and twenty-five meters and can be adjusted. The weight of the blade can be controlled between one ton and five tons to improve the authenticity of the simulation. At the same time, in order to cover the working conditions of the blade in actual applications during the simulation, normal operating conditions, gust conditions, turbulent wind conditions, extreme typhoon conditions, ice and snow load conditions, sand and dust environment conditions, high humidity environment conditions, high temperature or low temperature conditions, mechanical fatigue conditions, and fault diagnosis conditions, etc. can be carried out, which can comprehensively cover various situations that the wind turbine blade may encounter in actual applications, helping to ensure that the wind turbine blade can adapt to various complex environments during the design, manufacturing, and use processes, and improving its reliability and durability.

[0033] Finally, under the above working conditions, on the one hand, the aerodynamic response, structural deformation response, vibration response, thermal stress response, material aging characteristics, variable pitch system response characteristics and control strategy adaptability of wind turbine blades can be simulated; on the other hand, static load tests, dynamic load tests, wind speed influence tests, temperature and humidity influence tests, vibration characteristic tests, variable pitch drive characteristic tests, material durability tests and fault prediction and early warning tests can be carried out to comprehensively verify the performance of wind turbine blades. These tests can ensure that the blades can meet the design requirements in actual use, while revealing potential problems and risks.

[0034] In this scheme, if Figure 3 As shown, the multi-dimensional precision loading device includes a main actuation system, an auxiliary actuation system, a force / torque sensor and an intelligent control unit. The main actuation system is arranged on the loading base to provide large load simulation for the blade; the auxiliary actuation system is arranged on the blade support structure to simulate high-frequency small-amplitude dynamic loads; the force / torque sensor is arranged at the root of the blade to measure the applied force and torque in real time; the braking control unit is used to perform closed-loop optimization of the loading process; the intelligent control unit adopts model predictive control (MPC) and adaptive control algorithms to perform closed-loop optimization of the loading process; wherein, the main actuation system is arranged on the loading base, which can provide stable large-load simulation for large blades, and has a good effect on testing the structural strength and stability of the blade when subjected to extreme static loads; the auxiliary actuation system is arranged on the blade support structure, which can simulate high-frequency small-amplitude dynamic loads, which is helpful to evaluate the high-frequency vibration and fatigue damage that the blade may encounter in actual operation, and through the coordinated work of the main and auxiliary actuation systems, the device can accurately simulate the working state of the blade under a complex load environment, and improve the comprehensiveness and accuracy of the test. In addition, the force / torque sensor is set at the root of the blade, which can measure the force and torque applied to the blade in real time and accurately, providing key feedback information for the intelligent control unit, so that it can adjust the loading strategy according to the actual force conditions to ensure the accuracy and safety of the test. The brake control unit is part of the intelligent control unit and is responsible for executing the closed-loop optimization strategy. It works closely with the intelligent control unit and adopts model predictive control (MPC) and adaptive control algorithms. The MPC algorithm can plan the loading path in advance based on the prediction model, optimize the loading process, and reduce unnecessary fluctuations and delays. The adaptive control algorithm can dynamically adjust the control parameters according to the real-time response of the blade to improve the adaptability and stability of the system. The closed-loop optimization strategy ensures the precise control of the loading process, improves the test efficiency, and reduces repeated tests caused by inaccurate loading.

[0035] like Figure 4As shown in the figure, the pitch drive device includes a drive unit, a transmission system, a cooling system, and a control system. The drive unit, the transmission system, and the cooling system are electrically connected to the control system. Specifically, the drive unit includes a main drive and an auxiliary drive. The main drive combines a permanent magnet synchronous motor and a harmonic reducer, and the auxiliary drive uses a high-temperature superconducting motor. The transmission system uses a high-strength alloy steel spindle and ceramic rolling bearings to ensure high stability. The cooling system combines liquid nitrogen cooling and closed-loop water cooling to maintain the stable operation of the drive unit. The control system is based on a field-programmable gate array (FPGA) and uses an adaptive fuzzy PID and a feedforward compensation control algorithm for real-time pitch optimization. In the above process, the drive unit includes a main drive and an auxiliary drive. This redundant design improves the reliability and stability of the system. The main drive combines a permanent magnet synchronous motor and a harmonic reducer, which has the advantages of high efficiency, energy saving, and low noise, and can ensure the accuracy and rapidity of the pitch action. The auxiliary drive uses a high-temperature superconducting motor, which has extremely high efficiency and power density under specific conditions, providing additional driving ability and emergency backup for the system.

[0036] The transmission system uses a high-strength alloy steel spindle and ceramic rolling bearings. These materials have excellent wear resistance and fatigue resistance, which can ensure the high stability and long life of the transmission system. The high-strength alloy steel spindle can withstand large torques and bending moments, while the ceramic rolling bearings have the characteristics of low friction, high speed, and high precision, further improving the performance of the transmission system. The cooling system combines liquid nitrogen cooling and closed-loop water cooling methods to provide comprehensive cooling protection for the drive unit. Liquid nitrogen cooling can quickly reduce the temperature of the drive unit and effectively prevent overheating. Closed-loop water cooling can continuously and stably take away the heat generated by the drive unit to ensure its stability during long-term operation.

[0037] The control system is based on a field-programmable gate array (FPGA). This hardware platform has the ability of high-speed and parallel processing and can respond to pitch demands in real time. It uses an adaptive fuzzy PID and a feedforward compensation control algorithm. These algorithms can automatically adjust control parameters according to the system state and environmental changes to achieve precise control and optimization of the pitch action. The adaptive fuzzy PID algorithm can handle uncertainties and nonlinear problems in the system and improve the robustness of the control.

[0038] The feedforward compensation control algorithm can predict the future behavior of the system and make adjustments in advance to reduce control lag and error.

[0039] Such as Figure 5As shown in the figure, the multimodal monitoring device includes a fiber Bragg grating sensing system, an acoustic emission detection system, a three-dimensional digital image system, an infrared thermal imaging system, and a wireless sensor network. Among them, the fiber Bragg grating sensor system is used to monitor the strain and temperature distribution of the blade; the acoustic emission detection system is used to detect internal cracks and micro-damage of the blade; the three-dimensional digital image system is used to track the deformation of the blade in real time; the infrared thermal imaging system is used to monitor the temperature anomaly on the surface of the blade; the wireless sensor network is used for remote transmission of detection data. The fiber Bragg grating sensor system can monitor the strain and temperature distribution of the blade, providing detailed deformation information and temperature change conditions of the blade under the stressed state, which helps to evaluate the structural integrity and thermal performance of the blade. The acoustic emission detection system can detect internal cracks and micro-damage of the blade, timely discover potential structural problems, and prevent blade failure caused by crack propagation. The three-dimensional digital image system can track the deformation of the blade in real time, providing intuitive blade deformation images, which helps to analyze the dynamic response of the blade under wind load. The infrared thermal imaging system can monitor the temperature anomaly on the surface of the blade, timely discover temperature increases caused by reasons such as friction and overheating, and prevent safety accidents such as fires. Through the combination of these multiple monitoring technologies, the device can comprehensively and accurately monitor the state of the blade, providing strong data support for the maintenance and management of the blade.

[0040] The high-precision strain and temperature data provided by the fiber Bragg grating sensor system can be combined with the crack information detected by the acoustic emission detection system to more accurately evaluate the structural state of the blade. The wireless sensor network is used for remote transmission of detection data, enabling the monitoring data to be transmitted to the monitoring center or cloud platform in real time and wirelessly, facilitating remote monitoring and management. This not only improves the convenience of monitoring but also reduces the cost and risk of manual inspection. Through the real-time monitoring data provided by the multimodal monitoring device, the operation and maintenance personnel can timely understand the state of the blade, discover potential problems and take measures to repair or replace them, which helps to reduce the downtime caused by blade failures and improve the availability and power generation efficiency of the wind turbine.

[0041] As Figure 6As shown in the figure, the data analysis device includes a hardware platform, a software architecture, an AI module, and a visualization platform. The hardware platform, software architecture, AI module, and visualization platform are signal-connected. The AI module includes a deep reinforcement learning module, a convolutional neural network module, a long short-term memory network module, and a graph neural network module. The integration of the hardware platform, software architecture, AI module, and visualization platform enables each part to cooperate closely and jointly complete complex data analysis tasks. The hardware platform provides powerful computing capabilities, the software architecture ensures the stability and scalability of the system, the AI module provides intelligent algorithm support, and the visualization platform provides intuitive data display. The deep reinforcement learning module can learn optimal strategies by interacting with the environment and is suitable for scenarios that require decision-making and optimization, such as recommendation systems and autonomous driving. The convolutional neural network module is good at processing image and video data, can automatically extract features and perform tasks such as classification and recognition, and is widely used in fields such as image recognition and video analysis. The long short-term memory network module is particularly suitable for processing time series data, can capture long-term dependencies in the data, and is widely used in fields such as speech recognition and natural language processing. The graph neural network module can process graph-structured data, such as social networks and transportation networks, and mine potential patterns and relationships in the data.

[0042] As Figure 7 As shown in the figure, the holographic environment simulation device includes a temperature and humidity control system, a pressure simulation system, a wind field simulation system, a precipitation simulation system, a solar radiation simulation system, and a lightning simulation system. The humidity control system, pressure simulation system, wind field simulation system, precipitation simulation system, solar radiation simulation system, and lightning simulation system are signal-connected. By integrating the above systems, it is possible to simultaneously simulate various natural environmental factors such as temperature, humidity, pressure, wind field, precipitation, solar radiation, and lightning, providing a highly realistic simulation environment for fields such as scientific research, testing, and training. This comprehensive environmental simulation ability enables the reproduction of complex natural environmental conditions in a laboratory or specific location, greatly reducing the costs and risks of field testing or experiments. By precisely controlling the parameters of each environmental factor, the device can ensure the stability and consistency of experimental conditions, thereby improving the accuracy and reliability of experiments. For example, in scenarios such as material testing, equipment performance verification, or personnel training, stable environmental conditions can ensure the comparability and effectiveness of test results. In addition, by simulating different natural environmental conditions, researchers can deeply study the impact of environmental factors on organisms, materials, equipment, or systems, promoting interdisciplinary cooperation and innovation.

[0043] Compared with field tests or experiments, the device can simulate the environment in a laboratory or a specific location, which can greatly save labor, material and time costs. At the same time, by precisely controlling environmental factors, it can also reduce waste and pollution during the experiment, in line with the concept of green and sustainable development. Secondly, the device can provide a controllable environmental platform for the development and testing of new technologies and products, accelerating the process of technological innovation and product R & D.

[0044] As Figure 8 shown, the digital twin platform includes a model system, a data processing system, a virtual sensor network and a visualization interaction system. The model system, the data processing system, the virtual sensor network and the visualization interaction system are signal-connected. The application of the digital twin platform in the multi-condition loading simulation experiment of the wind turbine blade pitch system can accurately simulate the multi-condition environment, efficiently process and analyze data, enhance the safety and controllability of the experiment, and promote the verification and optimization of the experimental results. These beneficial effects will provide strong support for the R & D, testing and application of the wind turbine blade pitch system, and promote the continuous progress and development of wind power technology.

[0045] The transmission device includes a data bus, a time synchronization system, an energy management system and a safety emergency system. The time synchronization system, the energy management system and the safety emergency system are connected through the data bus. As the core of the transmission device, the data bus is responsible for data exchange between systems. In the multi-condition loading simulation experiment of the wind turbine blade pitch system, the data bus can efficiently and accurately transmit various data generated during the experiment, such as blade angle, rotational speed, torque, stress, etc., ensuring the real-time and accuracy of experimental data, providing comprehensive data support for experimental personnel, and facilitating in-depth analysis of experimental results. The time synchronization system is used to ensure the time consistency between systems during the experiment. In the multi-condition loading simulation experiment, precise time management can improve the accuracy and reliability of experimental results, avoiding errors caused by time asynchronization. At the same time, precise time synchronization helps experimental personnel to control and monitor the experimental process more finely. The energy management system is responsible for monitoring and managing the energy consumption during the experiment. In the multi-condition loading simulation experiment of the wind turbine blade pitch system, the energy management system can reasonably allocate energy according to experimental requirements, ensure the normal operation of experimental equipment, improve energy utilization efficiency, and reduce experimental costs. At the same time, the energy management system can timely detect and solve energy waste problems, providing guarantee for the sustainable progress of the experiment. The safety emergency system is used to monitor potential safety risks during the experiment and take emergency measures in case of emergency. In the multi-condition loading simulation experiment of the wind turbine blade pitch system, the safety emergency system can ensure the safety of experimental personnel and equipment, enhance the safety of the experiment, and reduce the occurrence of safety accidents. At the same time, the safety emergency system can quickly respond in case of emergency, reduce experimental losses, and ensure the smooth progress of the experiment.

[0046] In a second aspect, a blade is provided, including a blade body, on which a pitch system is installed. The blade is made of carbon fiber reinforced composite material, glass fiber and aramid fiber, and a nano-coating is applied on the surface of the blade. The blade is simulated by using the multi-condition loading simulation system for the pitch system of the wind turbine blade as described above. The blade made of carbon fiber reinforced composite material, glass fiber and aramid fiber, with a nano-coating on the surface, and equipped with a pitch system, and simulated by using the multi-condition loading simulation system for the pitch system of the wind turbine blade is of great significance for improving the performance of the wind turbine blade, reducing the R & D cost, enhancing the market competitiveness and promoting the development of wind power technology.

[0047] Generally speaking, the multi-condition loading simulation system for the pitch system of the wind turbine blade provided by the present invention realizes the comprehensive and accurate simulation of the wind turbine blade under various complex conditions by integrating a number of advanced technologies. This system can not only conduct conventional static and dynamic load tests, but also simulate the blade performance under extreme environmental conditions, providing a comprehensive and reliable experimental platform for the R & D, testing and optimization of the wind power system. By adopting artificial intelligence technology and digital twin technology, this system also has the ability of adaptive optimization and predictive analysis, greatly improving the test efficiency and data value. This innovative design is expected to significantly promote the development of wind power technology and make an important contribution to improving the reliability and efficiency of the wind power system.

[0048] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the scope of its protection. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that after reading the present invention, various changes, modifications or equivalent replacements can still be made to the specific implementation manners of the invention, but these changes, modifications or equivalent replacements are all within the scope of the protection of the pending claims of the invention.

Claims

1. A wind turbine blade pitch control system multi-condition loading simulation system, characterized in that: include: A blade simulation device, a multi-dimensional precision loading device, a pitch drive device, a multi-modal monitoring device, a data analysis device, a holographic environment simulation device, a digital twin platform, a transmission device, and a control device, wherein the blade simulation device, the multi-dimensional precision loading device, the pitch drive device, the multi-modal monitoring device, the data analysis device, the holographic environment simulation device, the digital twin platform, and the transmission device are electrically connected to the control device; The blade simulation device is used to simulate the blade shape; the multi-dimensional precision loading device is used to control the blade shape simulation; the pitch drive device is used to control the pitch process; the multi-modal monitoring device is used to monitor the blade state; the data analysis device is used to analyze and process the data; the holographic environment simulation device is used to simulate different working states; The digital twin platform is used to construct a blade model; the transmission device is used for data transmission.

2. The wind turbine blade pitch control system multi-operating condition loading simulation system according to claim 1 is characterized in that: The blade simulation device includes a modular blade structure, an intelligent material component, an active deformation control component and a nano-coating. The modular blade structure is made of carbon fiber reinforced composite material, glass fiber and aramid fiber. The nano-coating covers the surface of the modular blade structure. The active deformation control component is electrically connected to the intelligent material component, and the intelligent material component is connected to the modular blade structure.

3. The wind turbine blade pitch control system multi-operating condition loading simulation system according to claim 1 is characterized in that: The multi-dimensional precision loading device includes a main actuation system, an auxiliary actuation system, a force / torque sensor and an intelligent control unit. The main actuation system is arranged on a loading base to provide a large load simulation for the blade; the auxiliary actuation system is arranged on a blade support structure to simulate a high-frequency small-amplitude dynamic load; The force / torque sensor is arranged at the root of the blade and is used for measuring the applied force and torque in real time; the brake control unit is used for performing closed-loop optimization on the loading process.

4. The wind turbine blade pitch control system multi-operating condition loading simulation system according to claim 1, characterized in that: The variable pitch drive device comprises a drive unit, a transmission system, a cooling system and a control system, and the drive unit, the transmission system and the cooling system are electrically connected to the control system.

5. The wind turbine blade pitch control system multi-operating condition loading simulation system according to claim 1, characterized in that: The multimodal monitoring device includes a fiber grating sensor system, an acoustic emission detection system, a three-dimensional digital imaging system, an infrared thermal imaging system and a wireless sensor network; wherein the fiber grating sensor system is used to monitor blade strain and temperature distribution; the acoustic emission detection system is used to detect internal cracks and micro-damages of the blade; the three-dimensional digital imaging system is used to track blade deformation in real time; the infrared thermal imaging system is used to monitor temperature anomalies on the blade surface; and the wireless sensor network is used to detect remote transmission of data.

6. The wind turbine blade pitch control system multi-operating condition loading simulation system according to claim 1, characterized in that: The data analysis device includes a hardware platform, a software architecture, an AI module and a visualization platform. The hardware platform, software architecture, AI module and visualization platform are signal-connected. The AI ​​module includes a deep reinforcement learning module, a convolutional neural network module, a long short-term memory network module and a graph neural network module.

7. The wind turbine blade pitch control system multi-operating condition loading simulation system according to claim 1, characterized in that: The holographic environment simulation device includes a temperature and humidity control system, an air pressure simulation system, a wind field simulation system, a precipitation simulation system, a solar radiation simulation system and a lightning simulation system, and signals are connected among the humidity control system, the air pressure simulation system, the wind field simulation system, the precipitation simulation system, the solar radiation simulation system and the lightning simulation system.

8. The wind turbine blade pitch control system multi-operating condition loading simulation system according to claim 1, characterized in that: The digital twin platform includes a model system, a data processing system, a virtual sensor network and a visualization interaction system, and the model system, the data processing system, the virtual sensor network and the visualization interaction system are signal-connected.

9. The wind turbine blade pitch control system multi-operating condition loading simulation system according to claim 1, characterized in that: The transmission device includes a data bus, a time synchronization system, an energy management system and a safety emergency system, and the time synchronization system, the energy management system and the safety emergency system are connected via the data bus.

10. A blade, comprising a blade body, a pitch system installed on the blade body, the blade being made of carbon fiber reinforced composite material, glass fiber and aramid fiber, the surface of the blade being coated with a nano coating, characterized in that: The blade is simulated using the wind turbine blade pitch system multi-condition loading simulation system according to any one of claims 1 to 9.

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