Lidar-based clearance distance signal extraction and safety control method

Abstract

The present application aims to provide a kind of clearance distance signal extraction and safety control method based on laser radar with accurate signal identification, clear calculation logic and efficient control closed loop.The method of the present application comprises the following steps: a. fixing a laser radar system below the nacelle of a wind turbine;b. measuring the distance from the target point at the tail end of the blade to the laser radar unit using the time-of-flight principle;c. the data processing unit of the wind turbine receives the measurement data of several laser radar units, identifies the effective blade reflection signal using a signal aggregation statistical method, and calculates the clearance distance between the blade and the tower based on the reflection signal;d. real-time monitoring of the clearance distance data between the blade and the tower, combined with wind speed and rotor speed parameters, to calculate the optimal pitch angle adjustment amount through the wind turbine control system;e. dynamically adjusting the pitch angle of the blade through the pitch actuator of the wind turbine.The present application is applied to the field of laser radar technology.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laser radar, and particularly relates to a clearance distance signal extraction and safety control method based on laser radar, which is suitable for real-time monitoring and safety control of the gap between a large wind turbine blade and a tower. BACKGROUND

[0002] As the core equipment of renewable energy utilization, the technical upgrading of wind turbines promotes the development of turbines in the direction of large-scale. The increase in blade size can significantly improve the efficiency of wind energy capture and power generation, but at the same time, it brings two key problems: first, the increase in blade weight leads to an increase in tower structure load, causing fatigue stress and safety hazards; second, the risk of interference between the blade and the tower during rotation is intensified - under complex working conditions such as strong wind and turbulence, the blade is prone to elastic deformation, which may cause the blade to collide with the tower, causing equipment damage.

[0003] In order to reduce this risk, it is crucial to use sensors to monitor the deformation of the blade in real time. These sensors provide key data on the structural integrity of the blade and can detect operational problems early. In addition to regular equipment maintenance, it is also necessary to monitor the clearance range (defined as the distance between the tip of the blade and the tower) in real time during normal operation.

[0004] The detection of the clearance range mainly involves two categories: one is based on visual detection methods, such as using cameras and image processing technology; the other relies on distance measurement methods, such as millimeter wave, laser or other optical technology.

[0005] Visual detection methods rely on optical imaging technology to obtain environmental information. These methods usually use cameras in combination with image processing algorithms. Techniques include camera systems that capture high-resolution images, as well as image processing algorithms such as edge detection, image segmentation, and pattern recognition, which are used to identify obstacles and measure distances. Stereovision uses two or more cameras to simulate human binocular vision, and can also calculate depth by comparing left and right images. The advantages of visual methods include the ability to provide rich environmental details, effective detection of static and dynamic targets, and the potential to improve accuracy through sensor fusion. However, they may not perform well in low light or adverse weather conditions, and require a large amount of computing resources.

[0006] Distance measurement methods utilize millimeter waves, lasers, or other optical technologies. For example, radar, which emits microwave signals and measures the time of the reflected wave to calculate distance and speed; LiDAR (Light Detection and Ranging), which uses a laser beam to scan and generate a high-precision 3D map of the environment by measuring the reflection time; and laser sensors that measure the distance to obstacles using infrared lasers. These methods can be unaffected by lighting conditions, allowing effective operation in darkness or complex environments, and generally provide more accurate distance measurements. However, they can be affected by the material properties of objects (such as absorption or scattering), and can be more expensive, especially for high-precision laser sensors.

[0007] In view of the above, the prior art has the following shortcomings:

[0008] Disconnection between monitoring and control: Most detection methods can only achieve distance data acquisition, lack of closed-loop linkage with the fan control system, and cannot respond to blade deformation risk in real time;

[0009] Energy loss of preventive control: Traditional variable pitch control is mostly based on preset wind speed threshold for preventive adjustment, without combining actual gap data, resulting in reduced wind energy utilization efficiency;

[0010] Insufficient signal effectiveness: Under complex working conditions (such as ground clutter and blade vibration), sensors are prone to collect invalid data, affecting the accuracy of distance calculation.

[0011] Therefore, it is necessary to design a method for measuring the distance between the fan blade and the tower to avoid the above-mentioned risk situations. SUMMARY

[0012] The technical problem to be solved by the present application is to overcome the shortcomings of the prior art and provide a clearance distance signal extraction and safety control method based on laser radar, which is accurate in signal recognition, clear in calculation logic, and efficient in closed-loop control, to realize real-time maintenance of blade-tower safety distance and optimization balance of power generation efficiency.

[0013] The technical solution adopted by the present application is that the clearance distance signal extraction and safety control method based on laser radar comprises the following steps:

[0014] a. A laser radar system is fixed below the nacelle of a wind turbine, the laser radar system comprising a plurality of laser radar units, the optical lenses of the plurality of laser radar units being arranged downward, and the plurality of laser radar units being arranged at different pitch angles to ensure that the optical lenses cover the rotating track of the tail end of the blade downward;

[0015] b. The lidar unit emits a laser pulse of a set wavelength and uses the time-of-flight principle to measure the distance from the lidar unit to the target point at the tail end of the blade;

[0016] c. Several lidar units receive reflected signals from rotating blades, and the wind turbine's data processing unit receives measurement data from several lidar units, uses a signal aggregation and statistical method to identify valid blade reflected signals, and calculates the clearance distance between the blades and the tower based on the reflected signals.

[0017] d. Real-time monitoring of the clearance distance between the blades and the tower, combined with wind speed and rotor speed parameters, allows the wind turbine control system to calculate the optimal blade pitch angle adjustment.

[0018] e. The blade pitch angle is dynamically adjusted by the pitch actuator of the wind turbine to ensure a safe distance between the blade and the tower.

[0019] Specifically, in step a, the number of lidar units is set to three, and the three lidar units are set with different pitch angles, with an angle difference of 2°.

[0020] Specifically, in step b, the wavelength is set to 905nm.

[0021] Specifically, in step b, the method of measuring the distance from the lidar unit to the target point at the tail end of the blade using the time-of-flight principle is as follows:

[0022] Let L represent the distance from the lidar unit to the target, c represent the speed of light, and Δt represent the time required for light to travel to the target and return. Then we have:

[0023] L = c·Δt / 2.

[0024] Specifically, in step c, the identification of valid blade reflection signals using a signal aggregation statistical method involves:

[0025] c1. Parameter initialization: Set the threshold parameter m for effective counting and the data volume parameter n for comparison through the data processing unit of the wind turbine;

[0026] c2. Data Acquisition: Continuously acquire n detection distance data points. d(i) ,in i Values ​​range from 1 to n;

[0027] c3. Data Classification: Based on inherent wind turbine parameters, tower height h t and blade length parameters l b Distinguishing ground reflection data g and blade reflection data b ;

[0028] c4. Validity verification: Count the number of valid blade signals. If the number is ≥ m, the measurement data is valid; otherwise, re-collect the data.

[0029] Specifically, in step c, the clearance distance between the blade and the tower is calculated based on the reflected signal using the following formula:

[0030] C=L·sin(θ p )+Xr,

[0031] Where C is the gap range, L is the distance measured by the lidar, θp is the elevation angle of the laser, X is the distance from the lidar to the tower axis, and r is the tower radius.

[0032] Specifically, step d is as follows:

[0033] d1. Determine whether pitch angle adjustment is needed based on the comparison between the monitored clearance distance between the blade and the tower and the preset clearance distance safety threshold.

[0034] d2. When it is determined that pitch angle adjustment is required, the current wind speed U, rotor speed ω, and power output coefficient C are used. p Calculate the adjustment direction and magnitude of the pitch angle β;

[0035] d3. Calculate the optimal pitch angle β based on the relationship between the power coefficient and the pitch angle and tip speed ratio;

[0036] d4. The blade pitch angle is dynamically adjusted by the pitch actuator.

[0037] Specifically, in step d2, let the power P generated by the wind energy be...

[0038] P=1 / 2ρAC p U 3 ,

[0039] Where ρ represents air density, A represents the swept area of ​​the fan rotor, U represents wind speed, and C... p It is the power coefficient, C p The value is affected by the blade pitch angle β and the tip speed ratio λ:

[0040] Cp=(0.44-0.167β)·sin[π(λ-3) / (15-0.3λ)]-0.00184(λ-3)β,

[0041] The tip speed ratio λ is defined as the ratio of the linear velocity at the blade tip to the wind speed:

[0042] λ=ωR / U,

[0043] Where ω is the rotor speed, R is the rotor radius, and U is the wind speed.

[0044] The propeller pitch angle β is finally obtained by using P and λ.

[0045] Furthermore, step c3 specifically includes:

[0046] c31, Ground Reflection Data g When the detection distance d(i) Approximately tower height h t If so, it is determined to be a ground clutter signal and is removed;

[0047] c32, blade reflection data b When the detection distance d(i) Approximate blade length parameters l b If the signal is valid, it is considered a valid blade signal and is retained for calculation.

[0048] The beneficial effects of this invention are as follows: The method employs multi-pitch angle lidar and signal aggregation statistics, achieving an invalid data rejection rate of ≥90% and a clearance distance measurement error of ≤0.2m, meeting industrial-grade safety control requirements. The response time from clearance monitoring to pitch control execution is ≤1s, enabling real-time response to sudden conditions such as strong winds and turbulence, avoiding blade-tower collisions. Dynamically adjusting the pitch angle based on actual clearance data increases power generation by 3%-5% compared to traditional preventative control. The integrated lidar and adaptive pitch control strategy effectively solves the challenge of maintaining blade-tower clearance in large wind turbines. The ability to dynamically adjust the pitch angle based on real-time measurement allows for performance optimization, minimizing energy losses typically associated with preventative pitch adjustments. Attached Figure Description

[0049] Figure 1 This is a simplified schematic diagram of the working environment of the lidar in the wind turbine in this invention. In the diagram, g is the wind turbine, h is the wind tower, i is the blade, j is the lidar, and k is the ground.

[0050] Figure 2 This is a fitted diagram of the clearance distance between the microwave radiometer (MWR) and the lidar blade-to-tower in the embodiment;

[0051] Figure 3 This is a linear fit graph of the clearance distance measured by the microwave radiometer (MWR) and the camera in the embodiment;

[0052] Figure 4 This is a diagram showing the relationship between the clearance range measured by the microwave radiometer (MWR) and the wind speed in the embodiment.

[0053] Figure 5It is a linear fit graph of the clearance distance measured by microwave radiometer (MWR) and lidar;

[0054] Figure 6 It is a linear fit graph of wind speed and blade pitch angle. Detailed Implementation

[0055] like Figures 1-6 As shown, the method of the present invention includes the following steps:

[0056] a. A lidar system is fixed below the nacelle of a wind turbine. The lidar system includes several lidar units, the optical lenses of the lidar units are set downwards, and the lidar units are set with different pitch angles to ensure that the downward-facing optical lenses cover the rotation trajectory of the blade tail.

[0057] b. The lidar unit emits a laser pulse of a set wavelength and uses the time-of-flight principle to measure the distance from the lidar unit to the target point at the tail end of the blade;

[0058] c. Several lidar units receive reflected signals from rotating blades, and the wind turbine's data processing unit receives measurement data from several lidar units, uses a signal aggregation and statistical method to identify valid blade reflected signals, and calculates the clearance distance between the blades and the tower based on the reflected signals.

[0059] d. Real-time monitoring of the clearance distance between the blades and the tower, combined with wind speed and rotor speed parameters, allows the wind turbine control system to calculate the optimal blade pitch angle adjustment.

[0060] e. The blade pitch angle is dynamically adjusted by the pitch actuator of the wind turbine to ensure a safe distance between the blade and the tower.

[0061] Specifically, in step a, the number of lidar units is set to three, and the three lidar units are set with different elevation angles, with an angle difference of 2° (e.g., 5.6°, 7.6°, 9.6°). By detecting reflected signals covering different blade positions from multiple angles, data redundancy is improved.

[0062] In step b, the wavelength is set to 905nm (balancing detection accuracy and eye safety, in line with industrial-grade lidar standards), and the ranging range is adapted to the wind turbine blade length and tower height parameters.

[0063] In step b, the specific method for measuring the distance from the lidar unit to the target point at the blade tip using the time-of-flight principle is as follows:

[0064] Based on the Time-of-Flight (ToF) principle, the lidar unit emits a laser pulse. The distance is calculated by detecting the time difference between the pulse's round trip to the target point at the tail of the blade. Here, L represents the distance from the lidar unit to the target (in meters), c represents the speed of light (3 × 10⁸ m / s), and Δt represents the time required for light to travel to the target and return (in seconds). Therefore,

[0065] L = c·Δt / 2.

[0066] Each lidar unit outputs raw ranging data at a frequency of over 100Hz to ensure the capture of the dynamic position of the blade during its high-speed rotation.

[0067] In step c, the specific method for identifying valid blade reflection signals using signal aggregation and statistical analysis is as follows:

[0068] c1. Parameter initialization: Set the threshold parameter m for effective count (e.g., m≥80, i.e., the proportion of continuous effective data ≥80%) and the data volume parameter n for comparison (e.g., n=100, i.e., 100 consecutive measurement values ​​are counted each time) through the data processing unit of the wind turbine.

[0069] c2. Data Acquisition: Continuously acquire n detection distance data points. d(i) ,in i Values ​​range from 1 to n;

[0070] c3. Data Classification: Based on inherent wind turbine parameters, tower height h t and blade length parameters l b Distinguishing ground reflection data g and blade reflection data b ;

[0071] c4. Validity verification: Count the number of valid blade signals. If the number is ≥ m, the measurement data is valid; otherwise, re-collect the data.

[0072] Specifically, step c3 is as follows:

[0073] c31, Ground Reflection Data g When the detection distance d(i) Approximately tower height h t If the difference range can be set to 0.5m, it is determined to be a ground clutter signal and is removed.

[0074] c32, blade reflection data b When the detection distance d(i) Approximate blade length parameters l bWhen the difference range can be set (for example, the difference range is set to 0.5 m), it is determined as a valid blade signal and retained for calculation.

[0075] In step c, based on the valid ranging data and geometric relationship, the clearance distance between the blade and the tower is calculated according to the reflection signal using the following formula:

[0076] C = L·sin(θ p ) + X - r,

[0077] where C is the clearance distance between the blade tip and the tower surface (i.e., the clearance range, unit: m), L is the effective straight-line distance measured by the lidar (unit: m), θp is the pitch angle of the lidar (unit: °, pre-calibrated and stored in the data processing unit), X is the horizontal distance from the lidar installation position to the tower axis (unit: m, accurately measured and preset during installation), and r is the tower radius (unit: m, taking half of the tower diameter at the measurement position, preset according to the tower parameters). Among them, L·sin(θ p ) is the projection component of the laser ranging in the direction perpendicular to the tower axis. After adding the horizontal distance X from the lidar to the tower axis and subtracting the tower radius r, the actual clearance between the blade tip and the tower surface is obtained.

[0078] In step d, by combining the clearance distance data and operating parameters, precise calculation of the pitch control amount is achieved through "risk judgment - parameter modeling - optimal solution calculation", specifically:

[0079] d1. According to the comparison result between the monitored clearance distance between the blade and the tower and the preset clearance distance safety threshold C_{safe} (set according to the wind turbine model, such as C_{safe} = 5 m), it is judged whether pitch angle adjustment is required:

[0080] If C ≥ C_{safe}: There is no need to adjust the pitch angle, and the current operating state is maintained;

[0081] If C < C_{safe}: Trigger the pitch control process and calculate the adjustment amount;

[0082] d2. When it is determined that pitch angle adjustment is required, the current wind speed U, rotor speed ω, and power output coefficient C p are used to calculate the adjustment direction and amplitude of the pitch angle β;

[0083] d3. Calculate the optimal pitch angle β according to the relationship between the power coefficient affected by the pitch angle and tip speed ratio;

[0084] d4. Dynamically adjust the pitch angle of the blade through the pitch actuator.

[0085] In step d2, let the power P generated by the wind energy be

[0086] P=1 / 2ρAC p U 3 ,

[0087] Where ρ represents air density (unit: kg / m³, local standard value), A represents the swept area of ​​the fan rotor (unit: m²), U represents wind speed, and C... p It is the power coefficient, which characterizes the wind energy conversion efficiency, C p The value is affected by the blade pitch angle β and the tip speed ratio λ:

[0088] Cp=(0.44-0.167β)·sin[π(λ-3) / (15-0.3λ)]-0.00184(λ-3)β,

[0089] (This formula has been verified by actual tests on a 10MW wind turbine and is applicable to operating conditions where the blade pitch angle is 0°≤β≤20° and the tip speed ratio is 3≤λ≤15).

[0090] The tip speed ratio λ is defined as the ratio of the linear velocity at the blade tip to the wind speed:

[0091] λ=ωR / U,

[0092] Where ω is the rotor speed (unit: rad / s, obtained in real time by the wind turbine SCADA system), R is the rotor radius (unit: m, i.e., blade length), and U is the current wind speed (unit: m / s, collected in real time by the wind speed sensor).

[0093] Using P and λ, with the objective of "net distance C ≥ C_{safe} and power P maximized", the optimal pitch angle β is solved through the following process:

[0094] Based on the current λ and C, the pitch angle adjustment step size is set to 0.1°, and the candidate values ​​are traversed within the feasible interval (0°≤β≤20°). For each candidate β, the power coefficient is calculated by substituting it into the Cp formula, and then the wind power P is obtained.

[0095] Filter out candidate βs that satisfy C≥C_{safe}, and select the β with the largest corresponding P as the optimal adjustment amount.

[0096] Ultimately, the pitch angle of the blades is dynamically adjusted by the pitch actuator of the wind turbine to ensure a safe distance between the blades and the tower. Specifically, the wind turbine control system converts the optimal pitch angle β into a control signal and sends it to the pitch actuator (hydraulic / electric pitch system), which adjusts the blade attitude by regulating the angle between the blades and the airflow.

[0097] Adjust the response time to ≤0.5s to ensure rapid response to blade deformation risks;

[0098] Closed-loop feedback: Within 1 second after pitch adjustment, the clearance distance C is re-acquired to verify the adjustment effect. If C still does not meet the standard, steps d and e are repeated until the safety conditions are met.

[0099] In this invention, field tests were conducted at a wind farm to evaluate the performance of the lidar. The lidar, camera, and millimeter-wave radar (MWR) monitoring system were installed on the turbine; key parameters are shown in Table 1. Data was collected using a Supervisory Control and Data Acquisition (SCADA) system, focusing on clearance measurement, wind speed, pitch angle, power output, and other relevant parameters.

[0100] Table 1. Main parameters of wind turbine generators

[0101]

[0102] The MWR (Medium-Range Detector) is fixed to the rear of the wind turbine nacelle, with the radar pointing towards the blade tip area to be inspected, monitoring blade deformation in real time. Cameras are installed inside the nacelle to capture real-time images of the blades and monitor their operation. These images focus on the tips of the wind turbine blades and the tower. The location of the blade tips is identified from the captured images, and the tower edge is detected. By analyzing the position of the blade tips relative to the tower edge, the distance range between the blade tips and the tower edge is calculated to determine the tower clearance. This real-time monitoring of tower clearance helps prevent blade sweeping.

[0103] Based on measurement data from several selected time periods, the data utilization rate of MWR measurements is higher than that of cameras, such as... Figure 2 As shown, different detection methods have significantly different settings based on invalid values. The maximum value for MWR is approximately 25 meters, while the maximum value for the camera is 100 meters, and the minimum value is 0 meters. Using different methods to measure the gap range ensures the validity of the data.

[0104] The three beams of the gap lidar installed below the nacelle make angles of 5.6°, 7.6°, and 9.6° with the vertically downward vector, respectively. Therefore, for a single detector of the gap lidar, based on the calculation formula for the clearance distance between the blade and the tower, the maximum measurable gap range is... C limit =L·sin(θ p Substituting the parameters of the wind turbine generator, the maximum gap ranges measured by the gap lidar are approximately 10.00m, 14.08m, and 18.10m, respectively. The equivalent MWR setting is 21-21.5 meters; any value greater than this or a ground echo signal received is considered to be within this range.

[0105] The effective gap range of the camera and MWR measurement is as follows Figure 3As shown, the results of the two methods are relatively close during routine measurements, indicating that both methods can effectively detect the gap range. Furthermore, the relationship between the measured gap range and wind speed is as follows: Figure 4 As shown, the clearance range exhibits a specific pattern under different wind speeds. The tower-blade clearance range is significantly correlated with rotor speed. As rotor speed increases, the clearance tends to decrease. When the rated speed is reached, the clearance range increases significantly with adjustments to the turbine blade pitch angle.

[0106] therefore, Figure 4 The trend data in this data cannot be obtained using lidar. This occurs when the blade clearance range is less than a critical value. C limit At this time, the blade reflection signal can be measured to obtain gap data. Less than C limit The value is more critical for the blade clearance range because it may trigger an alarm if the blade is too close to the tower, requiring further action. Measurement results are as follows... Figure 5 As shown.

[0107] Experimental Results and Analysis: The lidar, through signal aggregation and statistical methods, improved the rejection rate of invalid data (ground clutter, blade vibration interference) to 92%. Its measurement data showed a linear fit of R² = 0.9828 with the mean absolute error (MAE) of only 0.132m, significantly better than the camera (MAE = 0.015m, but with an effective data rate of only 65%). Wind Speed ​​Influence: When the wind speed increased from 3m / s to 15m / s, the clearance distance C decreased from 18m to 8m. Figure 4 This conforms to the physical law that "increased wind speed → increased blade deformation → decreased clearance". Rotational speed effect: After the rotor speed reaches the rated value (12 rpm), the blade pitch angle begins to adjust, and C increases with increasing β, verifying the effectiveness of the control strategy.

[0108] Under turbulent conditions with a wind speed of 18 m / s and an initial blade clearance C = 4.2 m (below the safety threshold), the system triggers pitch control:

[0109] The optimal pitch angle β is calculated to be 12.5°.

[0110] Within 3 seconds of the pitch change being executed, C rises to 5.8m while the power remains at 8.2MW (close to the rated power), achieving a balance between safety and efficiency.

[0111] Field test results demonstrate that the integrated lidar and adaptive pitch control strategy effectively addresses the challenge of maintaining blade-to-tower clearance in large wind turbines. The ability to dynamically adjust the pitch angle based on real-time measurements allows for performance optimization, minimizing energy losses typically associated with preventative pitch adjustments. The relationship between pitch angle control and wind speed in the experimental control strategy is shown below.Figure 6 As shown, the blade pitch angle is crucial for optimizing energy capture and ensuring safe operation under different wind conditions.

[0112] Furthermore, gap lidar can detect turbine rotor imbalance by monitoring the gap values ​​of the three blades and analyzing the data, thus drawing relevant conclusions. Rotor imbalance can lead to several problems, including power generation loss, nacelle vibration, deterioration of gap conditions, and fatigue damage.

[0113] In summary, lidar systems offer more accurate and cost-effective real-time clearance measurements than traditional methods. Continuous monitoring helps adapt to real-time conditions, significantly improving the operational efficiency and safety of wind turbine systems. This invention provides a novel solution for managing wind turbine blade-tower clearance by employing advanced sensing technology and effective control strategies. With the continued growth in demand for renewable energy, developing innovative solutions for measuring wind turbine performance is crucial for advancing the sustainability and reliability of wind power generation.

[0114] Finally, it should be emphasized that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications (such as the number of lidar beams and the beam pointing angle). Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for extracting and controlling airspace distance signals based on lidar, characterized in that, The method includes the following steps: a. A lidar system is fixed below the nacelle of a wind turbine. The lidar system includes several lidar units, the optical lenses of the lidar units are set downwards, and the lidar units are set with different pitch angles to ensure that the downward-facing optical lenses cover the rotation trajectory of the blade tail. b. The lidar unit emits a laser pulse of a set wavelength and uses the time-of-flight principle to measure the distance from the lidar unit to the target point at the tail end of the blade; c. Several lidar units receive reflected signals from wind turbine blades, and the wind turbine's data processing unit receives measurement data from several lidar units, uses a signal aggregation and statistical method to identify valid blade reflected signals, and calculates the clearance distance between the blades and the tower based on the reflected signals. d. Real-time monitoring of the clearance distance between the blades and the tower, combined with wind speed and rotor speed parameters, allows the wind turbine control system to calculate the optimal blade pitch angle adjustment. e. The blade pitch angle is dynamically adjusted by the pitch actuator of the wind turbine to ensure a safe distance between the blade and the tower; In step c, the clearance distance between the blade and the tower is calculated based on the reflected signal using the following formula: C=L sin(θ p )+Xr, Where C is the gap range, L is the distance measured by the lidar, and θ p X is the elevation angle of the laser, X is the distance from the laser to the tower axis, and r is the tower radius. Step d specifically refers to: d1. Determine whether pitch angle adjustment is needed based on the comparison between the monitored clearance distance between the blade and the tower and the preset clearance distance safety threshold. d2. When it is determined that pitch angle adjustment is required, the current wind speed U, rotor speed ω, and power output coefficient C are used. p Calculate the adjustment direction and magnitude of the pitch angle β; d3. Calculate the optimal pitch angle β based on the relationship between the power coefficient and the pitch angle and tip speed ratio; d4. The blade pitch angle is dynamically adjusted by the pitch actuator; In step d2, let the power generated by wind energy be P. P=1 / 2ρAC p U 3 , Where ρ represents air density, A represents the swept area of ​​the fan rotor, U represents wind speed, and C... p It is the power coefficient, C p The value is affected by the blade pitch angle β and the tip speed ratio λ: C p =(0.44-0.167β)·sin[π(λ-3) / (15-0.3λ)]-0.00184(λ-3)β, The tip speed ratio λ is defined as the ratio of the linear velocity at the blade tip to the wind speed: λ=ωR / U, Where ω is the rotor speed, R is the rotor radius, and U is the wind speed. The propeller pitch angle β is finally obtained by using P and λ.

2. The method for extracting and controlling airspace distance signals based on lidar according to claim 1, characterized in that, In step a, the number of lidar units is set to three, and the three lidar units are set with different pitch angles, with an angle difference of 2°.

3. The method for extracting and controlling airspace distance signals based on lidar according to claim 1, characterized in that, In step b, the wavelength is set to 905nm.

4. The method for extracting and controlling airspace distance signals based on lidar according to claim 1, characterized in that, In step b, the distance from the lidar unit to the target point at the tail of the blade is measured using the time-of-flight principle as follows: Let L represent the distance from the lidar unit to the target, c represent the speed of light, and Δt represent the time required for light to travel to the target and return. Then we have: L = c·Δt / 2.

Images