Clearance distance signal extraction and safety control method based on laser radar

Abstract

The invention aims to provide the clearance distance signal extraction and safety control method based on the laser radar, which is accurate in signal identification, clear in computational logic and efficient in closed loop control. The method comprises the following steps: a, fixing a laser radar system below a cabin of the wind driven generator; b, measuring the distance from the laser radar unit to a target point at the tail end of the blade by adopting a flight time principle; c, a data processing unit of the fan receives measurement data of the multiple laser radar units, an effective blade reflection signal is recognized through a signal aggregation statistical method, and the clearance distance between the blade and the tower is calculated according to the reflection signal; d, the clearance distance data between the blades and the tower is monitored in real time, and the optimal pitch angle adjustment amount is calculated through a fan control system in combination with the wind speed and rotor rotating speed parameters; and e, dynamically adjusting the pitch angle of the blade through a variable pitch execution mechanism of the fan. The method is applied to the technical field of laser radars.

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

[0008] 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

[0009] The technical problem to be solved by the present application is to overcome the shortcomings of the prior art, provide a clearance distance signal extraction and safety control method based on laser radar with accurate signal recognition, clear calculation logic, and efficient closed-loop control, and achieve real-time maintenance of blade-tower safety distance and optimization balance of power generation efficiency.

[0010] 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: a. A laser radar system is fixed below the nacelle of a wind turbine, the laser radar system comprises a plurality of laser radar units, the optical lenses of the plurality of laser radar units are arranged downward, and the plurality of laser radar units are arranged at different pitch angles to ensure that the optical lenses cover the rotating track of the tail end of the blade downward; b. The laser radar unit emits laser pulses of a set wavelength, and measures the distance from the laser radar unit to the target point at the tail end of the blade using the time-of-flight principle; c. If several laser radar units receive reflected signals from rotating blades, the data processing unit of the wind turbine receives measurement data of several laser radar units, identifies effective blade reflection signals using a signal aggregation statistical method, and calculates the clearance distance between the blades and the tower according to the reflection signals; d. The real-time monitored clearance distance data between the blades and the tower, combined with the wind speed and rotor speed parameters, are used to calculate the optimal pitch angle adjustment amount through the wind turbine control system; e. The pitch angle of the blades is dynamically adjusted through the pitch actuator of the wind turbine to ensure a safe distance between the blades and the tower.

[0011] Specifically, in the a step, the number of laser radar units is set to three, and the three laser radar units are set to different pitch angles with an angle difference of 2°.

[0012] Specifically, in the b step, the set wavelength is 905 nm.

[0013] Specifically, in the b step, the time-of-flight principle is used to measure the distance from the laser radar unit to the target point at the tail end of the blade, which is specifically: Let L represent the distance from the laser radar unit to the target, c represent the speed of light, and Δt represent the time required for light to propagate to the target and return. Then we have L = c·Δt / 2.

[0014] Specifically, in the c step, the signal aggregation statistical method is used to identify effective blade reflection signals, which is specifically: c1, parameter initialization: set the threshold parameter m of effective counting and the data volume parameter n for comparison through the data processing unit of the wind turbine; c2, data acquisition: continuously acquire n detection distance data d(i) , where i The value is 1-n; c3, data classification: based on the inherent parameters of the wind turbine, such as the tower height h t and the blade length parameter l b , ground reflection data g and blade reflection data b are distinguished; c4, effectiveness verification: count the number of effective blade signals. If the number is ≥m, the current measurement data is valid; otherwise, reacquire data.

[0015] Specifically, in the c step, the clearance distance between the blades and the tower is calculated according to the reflection signals using the following formula: C = L·sin(θ p )+X-r, where C is the gap range, L is the distance measured by the lidar, θp is the pitch angle of the laser, X is the distance from the lidar to the tower axis, and r is the tower radius.

[0016] Specifically, the d step is specifically: d1, determining whether the pitch angle adjustment is needed according to the comparison result of the monitored clearance distance between the blade and the tower and the preset clearance distance safety threshold; d2, when it is determined that the pitch angle adjustment is needed, using the current wind speed U, the rotor speed ω and the power output coefficient C p to calculate the adjustment direction and amplitude of the pitch angle β; d3, calculating the optimal pitch angle β according to the relationship that the power coefficient is affected by the pitch angle and the tip speed ratio; d4, dynamically adjusting the pitch angle of the blade through the pitch actuator.

[0017] Specifically, in the d2 step, the power P generated by the wind energy is P = 1 / 2 ρAC p U 3 , where ρ represents the air density, A represents the swept area of the fan rotor, U represents the wind speed, and C p is the power coefficient, the value of C p is affected by the pitch angle β and the tip speed ratio λ: Cp = (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 speed of 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, P and λ are obtained.

[0018] Further, the c3 step is specifically: c31, ground reflection data g : when the detection distance d(i) approaches the tower height h t , it is determined as a ground clutter signal and is removed; c32, blade reflection data b : when the detection distance d(i) approaches the blade length parameter l b , it is determined as an effective blade signal and is retained for calculation.

[0019] The beneficial effects of the present application are: in the method, multiple pitch angle laser radars are used, signal aggregation statistics is used, the invalid data elimination rate is greater than or equal to 90%, the clearance distance measurement error is less than or equal to 0.2m, and the industrial level safety control demand is met; the response time from gap monitoring to variable pitch execution is less than or equal to 1s, sudden working conditions such as strong wind and turbulence can be responded to in real time, and blade-tower collision is avoided; the pitch angle is dynamically adjusted based on actual gap data, compared with traditional preventive control, the power generation is increased by 3%-5%. Through the integrated laser radar and adaptive variable pitch control strategy, the challenge of maintaining the blade-tower clearance in the large wind turbine is effectively solved, and the ability of dynamically adjusting the pitch angle based on real-time measurement allows the optimization of performance and maximizes the reduction of energy loss usually related to preventive variable pitch adjustment. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 is a simple schematic diagram of the working environment of the laser radar in the wind turbine in the present application, in which g is a wind turbine, h is a wind tower, i is a blade, j is a laser radar, and k is the ground; Figure 2 is a clearance distance fitting diagram between the blade and the tower in the embodiment of the microwave radiometer (MWR) and the laser radar; Figure 3 is a linear fitting diagram of the clearance distance measured by the microwave radiometer (MWR) and the camera; Figure 4 is a relationship diagram of the clearance range measured by the microwave radiometer (MWR) and the wind speed; Figure 5 is a linear fitting diagram of the clearance distance measured by the microwave radiometer (MWR) and the laser radar; Figure 6 is a linear fitting diagram of the wind speed and the pitch angle. DETAILED DESCRIPTION

[0021] As shown in Figures 1-6 , the method of the present application comprises the following steps: a. fixing a laser radar system below the nacelle of the 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; b. the laser radar units emit laser pulses of a set wavelength, and the time of flight principle is used to measure the distance from the laser radar units to the target point at the tail end of the blade; c. the plurality of laser radar units receive reflected signals from the rotating blade, the data processing unit of the wind turbine receives the measurement data of the plurality of laser radar units, a signal aggregation statistical method is used to identify valid blade reflected signals, and the clearance distance between the blade and the tower is calculated according to 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, to calculate the optimal pitch angle adjustment through the wind turbine control system; e. Dynamic adjustment of the pitch angle of the blades through the wind turbine's pitch actuator to ensure a safe distance between the blades and the tower.

[0022] Specifically, in step a, the number of laser radar units is set to three, with different pitch angles of 2° (e.g., 5.6°, 7.6°, 9.6°). By detecting reflected signals at different angles, data redundancy is improved.

[0023] In step b, the wavelength is set to 905nm (taking into account detection accuracy and eye safety, in line with industrial laser radar standards), and the ranging range is adapted to the wind turbine blade length and tower height parameters.

[0024] In step b, the time-of-flight principle is used to measure the distance from the laser radar unit to the target point at the end of the blade. Based on the time-of-flight (ToF) principle, the laser radar unit emits a laser pulse, and the distance is calculated by detecting the time difference between the pulse's round trip between the radar and the target point at the end of the blade. Here, L represents the distance from the laser radar unit to the target (in meters), c represents the speed of light (3×10^8 m / s), and Δt represents the time required for the light to travel to the target and return (in seconds). Thus, L = c·Δt / 2.

[0025] Each laser radar unit outputs raw ranging data at a frequency of 100Hz or higher to ensure that the dynamic position of the blades during high-speed rotation is captured.

[0026] In step c, the signal aggregation and statistical method is used to identify valid blade reflection signals, which are as follows: c1. Parameter initialization: Set the threshold parameter m (e.g., m≥80, meaning that the proportion of consecutive valid data is ≥80%) and the data volume parameter n (e.g., n=100, meaning that 100 consecutive measurement values are statistically analyzed each time) through the wind turbine's data processing unit. c2. Data acquisition: Continuously acquire n detection distance data d(i) , where i The value is 1-n. c3. Data classification: Based on the wind turbine's inherent parameters, such as the tower height h t and blade length l b , ground reflection data g and blade reflection data b are distinguished. c4, validity verification: count the number of valid blade signals, if the number is greater than or equal to m, the measurement data is valid; otherwise, reacquire the data.

[0027] The c3 step is specifically: c31, ground reflection data g : when the detection distance d(i) approaches the tower height h t (For example, the difference range can be set to 0.5 m) is determined as a ground clutter signal and is removed; c32, blade reflection data b : when the detection distance d(i) approaches the blade length parameter l b (For example, the difference range can be set to 0.5 m) is determined as a valid blade signal and is retained for calculation.

[0028] In the c step, based on the valid ranging data and the geometric relationship, the clearance distance between the blade and the tower is calculated according to the reflection signal using the following formula: C = L sin (θ p ) + X - r, Where C is the clearance distance between the tail end of the blade and the surface of the tower (i.e. the gap range, unit: m), L is the effective straight-line distance measured by the laser radar (unit: m), θp is the pitch angle of the laser radar (unit: °, pre-calibrated and stored in the data processing unit), X is the horizontal distance from the laser radar installation position to the tower axis (unit: m, accurately measured during installation and pre-set), and r is the tower radius (unit: m, taking 1 / 2 of the diameter of the tower at the measurement position, pre-set according to the tower parameters). Where L sin (θ p ) is the projection component of the laser ranging in the direction perpendicular to the tower axis, after superimposing the horizontal distance X of the laser radar to the tower axis, the tower radius r is subtracted to obtain the actual gap between the tail end of the blade and the surface of the tower.

[0029] In the d step, combined with the clearance distance data and the operating parameters, the precise calculation of the variable pitch control quantity is realized through "risk judgment-parameter modeling-optimal solution", specifically: d1, according to the comparison result of the monitored clearance distance between the blade and the tower and the pre-set clearance distance safety threshold C_{safe} (set according to the wind turbine model, such as C_{safe}=5m), it is judged whether the pitch angle adjustment is needed: If C≥C_{safe}: no adjustment of the pitch angle is needed, the current operating state is maintained; If C < C_{safe}: the variable pitch control process is triggered, and the adjustment quantity is calculated; d2, when it is determined that the pitch angle adjustment is needed, the current wind speed U, the rotor speed ω and the power output coefficient C p The adjustment direction and amplitude of the pitch angle β are calculated. d3, the optimal pitch angle β is calculated according to the relationship between the power coefficient and the pitch angle and the tip speed ratio; d4, the pitch angle of the blade is dynamically adjusted by the pitch actuator.

[0030] In the d2 step, the power P generated by the wind energy is P=1 / 2ρAC p U 3 , Wherein ρ represents the air density (unit: kg / m³, taking the local standard value), A represents the swept area of the fan rotor (unit: m²), U represents the wind speed, C p is the power coefficient, which represents the wind energy conversion efficiency, the value of C p is affected by the pitch angle β and the tip speed ratio λ: Cp=(0.44-0.167β)·sin[π(λ-3) / (15-0.3λ)]-0.00184(λ-3)β, (The formula is verified by 10MW wind turbine test, applicable to the working condition of pitch angle 0°≤β≤20°, tip speed ratio: 3≤λ≤15); The tip speed ratio λ is defined as the ratio of the linear speed of the blade tip to the wind speed: λ=ωR / U, Wherein ω is the rotor speed (unit: rad / s, obtained from the wind turbine SCADA system in real time), R is the rotor radius (unit: m, i.e. the length of the blade), U is the current wind speed (unit: m / s, collected by the wind speed sensor in real time), By P and λ, the optimal pitch angle β is solved by the following process with the goal of "clearance distance C≥C_{safe} and maximum power P": Based on the current λ and C, set the pitch angle adjustment step size =0.1°, and traverse the candidate values in the feasible interval (0°≤β≤20°); for each candidate β, substitute it into the Cp formula to calculate the power coefficient, and then obtain the wind power P; Select the β corresponding to the maximum P as the optimal adjustment amount.

[0031] Finally, the pitch angle of the blade is dynamically adjusted by the pitch actuator of the wind turbine to determine the safe distance between the blade and the tower. Among them, the optimal pitch angle β is converted into a control signal by the wind turbine control system, and sent to the pitch actuator (hydraulic / electric pitch system), and the blade attitude is adjusted by adjusting the angle between the blade and the airflow: Adjustment response time: ≤0.5s, ensure fast response to blade deformation risk; Closed-loop feedback: re-collect the clearance distance C within 1s after pitching, verify the adjustment effect, if C still does not meet the standard, repeat steps d and e until the safety condition is met.

[0032] In the present 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; the main parameters are shown in Table 1. Data were collected through the supervisory control and data acquisition (SCADA) system, focusing on gap measurement, wind speed, pitch angle, power output, and other related parameters.

[0033] Table 1. Main parameters of wind turbine

[0034] The MWR was fixed on the back side of the wind turbine nacelle, with the radar pointing to the blade tip area to be detected, monitoring the deformation of the blade in real time. The camera was installed inside the nacelle to capture real-time images of the blade and monitor its operation. These images focused on the tip of the wind turbine blade and the tower. The position of the blade tip was identified from the captured images, and the edge of the tower was detected. By analyzing the position of the blade tip relative to the edge of the tower, the distance range between the blade tip and the edge of the tower was calculated to determine the tower gap. This real-time monitoring of the tower gap helps prevent blade sweep tower.

[0035] Based on the measurement data of several selected time periods, the data measured by the MWR were more effective than the camera, as shown in Figure 2 There is a considerable difference in the setting of invalid values based on different detection methods. The maximum value of the MWR is about 25 meters, while the maximum value of the camera is 100 meters and the minimum value is 0 meters. Measuring the gap range using different methods can ensure the effectiveness of the data.

[0036] The angles between the three beams of the gap lidar installed below the nacelle and the vertical downward vector are 5.6°, 7.6°, and 9.6°, respectively. Therefore, for a single detector of the gap lidar, based on the calculation formula of the clearance distance between the blade and the tower, the maximum gap range that can be measured is C limit =L·sin(θ p )+X-r. By substituting the parameters of the wind turbine, the maximum gap range measured by the gap lidar is about 10.00m, 14.08m, and 18.10m, respectively. The equivalent setting value of the MWR is 21-21.5 meters, and any value greater than this or receiving a ground echo signal is considered as this value.

[0037] The effective gap range measured by the camera and MWR is shown in Figure 3As shown in Figure 2, the results of the two methods are relatively close during routine measurements, which indicates that both methods can effectively detect the gap range. In addition, the relationship between the measured gap range and wind speed is shown in Figure 2. Figure 4 The figures show that the clearance range exhibits specific patterns at different wind speeds. The tower-to-blade clearance range is significantly correlated with the rotor speed. As the rotor speed increases, the clearance tends to decrease. At rated speed, the clearance range increases significantly as the turbine blade pitch angle is adjusted.

[0038] therefore, Figure 4 The trend data in the will not be obtained by LiDAR. When the gap range of the blade is less than the critical value C limit When the blade reflection signal is measured, the clearance data can be obtained. C limit The value of is more critical for the blade clearance range, as this value may trigger an alarm due to the blade being too close to the tower, requiring further action. Figure 5 shown.

[0039] Experimental results and analysis: The LiDAR uses a statistical method of signal aggregation to increase the rejection rate of invalid data (ground clutter, blade vibration interference) to 92%. The linear fit between its measurement data and the MWR is R²=0.9828, and the mean absolute error (MAE) is only 0.132m, significantly better than the camera (MAE=0.015m but the effective data rate is only 65%). Wind speed effect: When the wind speed increases from 3m / s to 15m / s, the clearance distance C decreases from 18m to 8m ( Figure 4 ), which conforms to the physical law of "increasing wind speed → increasing blade deformation → decreasing clearance." Speed ​​influence: After the rotor speed reaches the rated value (12 rpm), the pitch angle begins to adjust, and C increases as β increases, verifying the effectiveness of the control strategy.

[0040] Under turbulent conditions with a wind speed of 18 m / s, the initial blade clearance C = 4.2 m (below the safety threshold), and the system triggers pitch control: Calculate the optimal pitch angle β=12.5°, Within 3 seconds after the pitch change was executed, C returned to 5.8m, while the power remained at 8.2MW (close to the rated power), achieving a balance between safety and efficiency.

[0041] Results from field tests demonstrate that the integrated LiDAR and adaptive pitch control strategy effectively addresses the challenge of maintaining blade-tower clearance in large wind turbines. The ability to dynamically adjust the pitch angle based on real-time measurements allows for optimized performance, minimizing the energy losses typically associated with preventative pitch adjustments. The relationship between the pitch angle control and wind speed in the experimental control strategy is shown in Figure 2. Figure 6The pitch angle of the blades is crucial for optimizing energy capture and ensuring safe operation under different wind conditions.

[0042] Furthermore, the gap lidar can detect whether the turbine rotor is balanced by monitoring the gap values of the three blades and analyzing the data, thereby drawing relevant conclusions. Rotor imbalance can lead to several problems, including loss of power generation, nacelle vibration, deterioration of gap conditions, and fatigue damage.

[0043] In summary, the lidar system provides accurate, real-time gap measurements that are more precise and cost-effective than traditional methods. Continuous monitoring helps to adapt to real-time conditions, significantly improving the operational efficiency and safety of wind turbine systems. The present invention provides a novel solution for managing wind turbine blade-tower gap by employing advanced sensing technology and effective control strategies. As the demand for renewable energy continues to grow, developing innovative solutions for measuring wind turbine performance is crucial for advancing the sustainability and reliability of wind power.

[0044] Finally, it should be emphasized that the above description is only the 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, the pointing angle of the beams), and any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for laser radar-based clearance distance signal extraction and safety control, characterized by, The method comprises the following steps: a. Fixing a laser radar system 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; b. The laser radar units emit laser pulses of a set wavelength, and the distance from the laser radar units to the target point at the tail end of the blade is measured by using the time-of-flight principle; c. The plurality of laser radar units receive the reflected signals from the blades, the data processing unit of the wind turbine receives the measurement data of the plurality of laser radar units, the effective blade reflected signals are identified by using a signal aggregation statistical method, and the clearance distance between the blade and the tower is calculated according to the reflected signals; d. The clearance distance data between the blade and the tower monitored in real time are combined with the wind speed and the rotor speed parameters, and the optimal pitch angle adjustment amount is calculated by the wind turbine control system; e. The pitch angle of the blade is dynamically adjusted by the pitch actuator of the wind turbine, and the safe distance between the blade and the tower is determined.

2. The LIDAR-based clearance distance signal extraction and safety control method of claim 1, wherein, In the a step, the number of the laser radar units is set to three, the three laser radar units are arranged at different pitch angles, and the angle difference is 2°.

3. The LIDAR-based clearance distance signal extraction and safety control method of claim 1, wherein, In the b step, the set wavelength is 905 nm.

4. The LIDAR-based clearance distance signal extraction and safety control method of claim 1, wherein, In the b step, the distance from the laser radar unit to the target point at the tail end of the blade is measured by using the time-of-flight principle, and the specific method is as follows: L represents the distance from the laser radar unit to the target, c represents the speed of light, Δt represents the time required for light to propagate to the target and return, and then L=c·Δt / 2.

5. The LIDAR-based clearance distance signal extraction and safety control method of claim 4, wherein, In the c step, the specific method for identifying the effective blade reflected signals by using the signal aggregation statistical method is as follows: c1, parameter initialization: the threshold parameter m of effective counting and the data amount parameter n for comparison are set by the data processing unit of the wind turbine; c2, data acquisition: continuously acquire n detection distance data d(i) wherein i value 1~n; c3, data classification: based on tower height parameter inherent to the wind turbine h t and blade length parameter l b distinguishing ground reflected data g and blade reflected data b ; c4, effectiveness verification: the number of effective blade signals is counted, if the number is greater than or equal to m, the measurement data is effective; otherwise, the data is reacquired.

6. The LIDAR-based clearance distance signal extraction and safety control method of claim 1, wherein, In the c step, the clearance distance between the blade and the tower is calculated according to the reflected signals by using the following formula: C = L - sin(θ p )+ X - r, Where C is the gap range, L is the distance measured by the laser radar, θp is the pitch angle of the laser, X is the distance from the laser radar to the tower axis, and r is the tower radius.

7. The LIDAR-based clearance distance signal extraction and safety control method of claim 1, wherein, The d step is specifically as follows: d1, determining whether the pitch angle needs to be adjusted according to the comparison result of the monitored clearance distance between the blade and the tower and the preset clearance distance safety threshold; d2, when it is determined that the pitch angle adjustment is needed, the current wind speed U, the rotor speed ω and the power output coefficient C p calculating the adjustment direction and amplitude of the pitch angle β; d3, calculating the optimal pitch angle β according to the relationship between the power coefficient and the tip speed ratio; d4, dynamically adjusting the pitch angle of the blade by the pitch actuator.

8. The LIDAR-based clearance distance signal extraction and safety control method of claim 7, wherein, In the d2 step, the power P generated by wind energy is P = 1 / 2 pAC p U 3 , where p represents air density, A represents fan rotor swept area, U represents wind speed, C p is power coefficient, C p values are influenced by pitch angle b and tip speed ratio l: Cp=(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 speed of 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 pitch angle β is finally obtained by P and λ.

9. The LIDAR-based clearance distance signal extraction and safety control method of claim 5, wherein, The c3 step is in particular: c31, ground reflection data g : when the detection distance d(i) is close to the tower height h t , then it is determined as a ground clutter signal and is removed. c32, blade reflection data b : when the detection distance d(i) proximity blade length parameter l b is then determined to be a valid blade signal and retained for calculation.

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