A dynamic safety range calculation method for fan non-stop inspection

Abstract

The application relates to the technical field of fan inspection, and provides a dynamic safety range calculation method for fan non-stop inspection, which comprises the following steps: S1, calculating the yaw angle of a fan; S2, calculating the speed of fan yaw rotation; S3, calculating the rotating speed of a fan blade; S4, acquiring the current position of a UAV; S5, drawing a safety area; S6, comparing the current position coordinates of the UAV with the coordinate points of the safety area, and judging whether the UAV is in the safety area; and S7, judging whether a warning measure needs to be taken to ensure the safety of the UAV. The application is very suitable for real-time calculation of a dynamic safety area, does not need to stop the fan for inspection, improves the detection efficiency, reduces the maintenance cost, avoids the problems that a large amount of time and manpower are consumed in the traditional stop inspection method, and improves the reliability and production efficiency of the fan.

Description

Technical Field

[0001] This invention relates to the field of wind turbine inspection technology, and in particular to a method for calculating the dynamic safety range of wind turbine inspection without shutting down the turbine. Background Technology

[0002] Wind power generation is an environmentally friendly and clean energy source, and wind turbine blades are a key component of wind turbine generator sets. Operating at high altitudes and in all weather conditions, the blades bear heavy loads and operate in harsh environments, significantly impacting their lifespan. Therefore, it is essential to inspect the wind turbine blades regularly to identify and repair any abnormalities or defects, ensuring the normal operation of the generator set. Currently, both manual and drone inspections require the wind turbine to be shut down and locked, ensuring the blades are immobilized during inspection. However, this method is time-consuming, inefficient, and reduces power generation, resulting in direct economic losses. On-the-fly inspections avoid the economic losses associated with locking the turbine and effectively reduce overall inspection time. However, during on-the-fly inspections, the blades and yaw angle of the wind turbine are constantly changing, making the calculation of the dynamic safety range crucial. Summary of the Invention

[0003] The purpose of this invention is to address the aforementioned technical problems by proposing a dynamic safety range calculation method for wind turbine non-stop inspection. This objective can be achieved through the following technical solutions:

[0004] A method for calculating the dynamic safety range of a wind turbine during non-stop inspection includes the following steps: Step S1, calculating the yaw angle of the wind turbine; Step S2, calculating the yaw rotation speed of the wind turbine; Step S3, calculating the rotational speed of the wind turbine blades; Step S4, obtaining the current position of the drone; Step S5, drawing a safety zone; Step S6, comparing the current position coordinates of the drone with the coordinates of the safety zone to determine whether the drone is within the safety zone; Step S7, determining whether to take early warning measures to ensure the safety of the drone.

[0005] Specifically, in step S1, there are two ways to calculate the yaw angle of the wind turbine: manual mode S11 and automatic mode S12.

[0006] Specifically, the manual mode S11 is as follows:

[0007] S111: Raise the drone, monitor the positions of the drone and the wind turbine, and ensure that the distance between the drone and the wind turbine remains within a safe range;

[0008] S112: After manually aligning the drone with the wind turbine hub, press the "Start Operation" button;

[0009] S123: When the yaw angle of the UAV is greater than 180 degrees, the yaw angle of the wind turbine = the yaw angle of the UAV - 180 degrees; otherwise, the yaw angle of the wind turbine = the yaw angle of the UAV + 180 degrees.

[0010] Specifically, the automatic mode S12 is as follows;

[0011] S121: Perform distortion correction on the FPV image of the UAV;

[0012] S122: Automatically identify and track the wind turbine hub using deep learning algorithms, thereby controlling the drone to face the wind turbine hub;

[0013] S123: The image data is processed by computer vision algorithms to calculate the yaw angle of the current wind turbine.

[0014] Specifically, in step S2, the process of calculating the speed of the yaw rotation of the wind turbine is as follows;

[0015] S21: Set the starting point A of the drone flight at a safe distance from the front of the wind turbine hub;

[0016] S22: After the UAV flies to the work point B and hovers, it begins to calculate the speed of the wind turbine's yaw rotation;

[0017] S23: When the wind turbine yaws, the distance between the wind turbine blades and the UAV is detected by lidar to determine the direction of rotation of the wind turbine blades toward the UAV; when the distance decreases, the wind turbine blades rotate in the opposite direction to the UAV, the wind turbine blades approach the UAV, and the yaw rate is recorded as a negative value; when the distance increases, the wind turbine blades rotate in the direction the UAV is facing, the wind turbine blades move away from the UAV, and the yaw rate is recorded as a positive value.

[0018] S24: Calculate the distance difference between the wind turbine blades and the UAV per unit time, and the distance from work point A to work point B, using the distance data detected by the lidar; work point A is the starting point A, and work point B is the hovering point;

[0019] S25: Use inverse trigonometric functions to calculate the angle moved per unit time and convert the angle per second to radians per second;

[0020] Based on the above steps, the angular velocity of the wind turbine's yaw rotation is calculated. The larger the angular velocity, the faster the wind turbine yaws, requiring a larger dynamic safety range to ensure the safe flight of the UAV.

[0021] Specifically, the angular velocity of the wind turbine's yaw rotation is filtered and smoothed using a filtering algorithm to reduce the impact of noise and interference on the data, improve the accuracy and reliability of the data, and thus accurately calculate the dynamic safety range of the wind turbine, providing more reliable technical support for wind turbine monitoring and maintenance.

[0022] Specifically, in step S3, the interval between two consecutive sweeps of the wind turbine blades is captured by the pre-positioned lidar, and the rotational speed of the wind turbine blades is calculated.

[0023] The formula for calculating the rotational speed in one minute is: RPM = 60 / T; where RPM represents the rotational speed in rpm; and T represents the time taken for each revolution in seconds.

[0024] Specifically, in step S4, the current location of the drone is determined by an RTK or GPS positioning system.

[0025] Specifically, in step S5, based on the current design parameters and safety requirements of the wind turbine, a three-dimensional sector in the shape of a double-edged axe, symmetrical about the wind turbine tower, is drawn to represent the dangerous area of ​​the wind turbine, and the area outside the dangerous area is the safe area; the dangerous area is then divided into 8 coordinate points, corresponding to different positions around the wind turbine, as follows:

[0026] A(-w_d*cos@,w_h+w_d,w_d*sin@);

[0027] B(-w_d*cos@,w_h+w_d,-w_d*sin@);

[0028] C(w_d*cos@,w_h+w_d,w_d*sin@);

[0029] D(w_d*cos@,w_h+w_d,-w_d*sin@);

[0030] E(w_d*cos@,w_h-w_d,w_d*sin@);

[0031] F(w_d*cos@,w_h-w_d,-w_d*sin@);

[0032] G(-w_d*cos@,w_h-w_d,w_d*sin@);

[0033] H(-w_d*cos@,w_h-w_d,-w_d*sin@);

[0034] Wherein, w_d is the length of the wind turbine blade; w_h is the height of the wind turbine tower; @ is the yaw angle of the wind turbine; the above eight coordinate points can be used to draw a sector, the side of which is a rectangle with a length of w_d*2 and a height of w_h; the sector corresponds to the dangerous area of ​​the wind turbine.

[0035] Specifically, in step S7, when the location coordinates of the drone are within the safe area, the drone is in a safe state and no warning is required; when the location coordinates of the drone are within the danger area, a warning signal must be issued immediately.

[0036] Compared with the prior art, the present invention has at least one of the following technical advantages:

[0037] (1) This invention provides a method for calculating the dynamic safety range of a wind turbine without shutting it down for inspection. It is very suitable for calculating the dynamic safety zone in real time without shutting down the wind turbine for inspection, which improves the detection efficiency and reduces the maintenance cost. Traditional shutdown inspection methods consume a lot of time and manpower, while this method can avoid these problems, thereby improving the reliability and production efficiency of the wind turbine.

[0038] (2) The present invention can draw a three-dimensional sector based on information such as the rotational speed, height, and blade length of the wind turbine yaw, and use eight coordinate points to describe the safe area of ​​the wind turbine, thereby more accurately determining the safe range of the wind turbine.

[0039] (3) This invention provides a fast and effective method for detecting unmanned aerial vehicles (UAVs), which determines whether the UAV is in a safe area by comparing the UAV's position coordinates with the coordinates of the safe area.

[0040] (4) This invention ensures the safety of the wind turbine while effectively avoiding any impact on its power generation efficiency. It can monitor the wind turbine's status in real time, preventing malfunctions and allowing for timely intervention. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below:

[0042] Figure 1 This is a flowchart illustrating the dynamic safety range calculation method for non-stop wind turbine inspection according to the present invention.

[0043] Figure 2 This is a top view of the UAV inspection movement path of the dynamic safety range calculation method for wind turbine non-stop inspection according to the present invention.

[0044] Figure 3 This is a top view of the UAV inspection movement path of the dynamic safety range calculation method for wind turbine non-stop inspection according to the present invention.

[0045] Figure 4 A design block diagram of a wind turbine monitoring program written for the ROS2 framework based on the dynamic safety range calculation method for wind turbine non-stop inspection according to the present invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0047] Example

[0048] This invention provides a method for calculating the dynamic safety range of wind turbine inspections without shutting down, such as... Figure 1 As shown, the calculation method includes the following steps: Step S1, calculate the yaw angle of the wind turbine; Step S2, calculate the yaw rotation speed of the wind turbine; Step S3, calculate the rotational speed of the wind turbine blades; Step S4, obtain the current position of the UAV; Step S5, draw the safe zone; Step S6, compare the current position coordinates of the UAV with the coordinates of the safe zone to determine whether the UAV is within the safe zone; Step S7, determine whether to take early warning measures to ensure the safety of the UAV.

[0049] Specifically, in step S1, there are two ways to calculate the yaw angle of the wind turbine: manual method S11 and automatic method S12.

[0050] Specifically, the manual mode S11 process is as follows:

[0051] S111: Raise the drone, monitor the position of the drone and the wind turbine, and ensure that the distance between the drone and the wind turbine remains within a safe range;

[0052] S112: After manually aligning the drone with the wind turbine hub, press the "Start Operation" button;

[0053] S123: When the yaw angle of the drone is greater than 180 degrees, the yaw angle of the wind turbine = the yaw angle of the drone - 180 degrees; otherwise, the yaw angle of the wind turbine = the yaw angle of the drone + 180 degrees.

[0054] Here's an example of a C++ code implementation of the algorithm for determining the wind turbine's yaw angle based on the drone's yaw angle: `wind_yaw = (uav_yaw > 180) ? (uav_yaw - 180): (uav_yaw + 180);` This code uses a ternary operator, which can return different results depending on the condition.

[0055] Specifically, in automatic mode S12, the process is as follows;

[0056] S121: Perform distortion correction on the FPV images of the drone;

[0057] S122: It uses deep learning algorithms to automatically identify and track the wind turbine hub, thereby controlling the drone to face the wind turbine hub;

[0058] S123: The image data is processed using computer vision algorithms to calculate the current yaw angle of the wind turbine.

[0059] Specifically, in step S2, the process of calculating the speed of the wind turbine's yaw rotation is as follows;

[0060] S21: Set the starting point A of the drone flight at a safe distance from the front of the wind turbine hub;

[0061] S22: After the drone flies to work point B and hovers, it begins to calculate the speed of the wind turbine's yaw rotation.

[0062] S23: When the wind turbine yaws, the distance between the wind turbine blades and the drone is detected by lidar to determine the direction of rotation of the wind turbine blades toward the drone. When the distance decreases, the wind turbine blades rotate in the opposite direction to the drone, the wind turbine blades move closer to the drone, and the yaw rate is recorded as a negative value. When the distance increases, the wind turbine blades rotate in the direction the drone is facing, the wind turbine blades move away from the drone, and the yaw rate is recorded as a positive value.

[0063] S24: The distance difference (d) between the wind turbine blades and the drone per unit time (Δt) is calculated using distance data detected by lidar. Δt ), and the distance (d) from work point A to work point B. AB ); Work point A is the starting point A, and work point B is the hovering point;

[0064] S25: Using inverse trigonometric functions ( Calculate the angle moved per unit time and convert the angle per second to radians per second.

[0065] Based on the above steps, the angular velocity of the wind turbine's yaw rotation can be calculated. The greater the angular velocity, the faster the wind turbine yaws, requiring a larger dynamic safety range to ensure the safe flight of the drone.

[0066] Specifically, the angular velocity of the wind turbine's yaw rotation is filtered and smoothed using a filtering algorithm to reduce the impact of noise and interference on the data, improve the accuracy and reliability of the data, and thus accurately calculate the dynamic safety range of the wind turbine, providing more reliable technical support for wind turbine monitoring and maintenance.

[0067] Specifically, in step S3, the interval between two consecutive wind turbine blades is captured by the front-end lidar, and the rotational speed of the wind turbine blades is calculated.

[0068] The formula for calculating the rotational speed in one minute is: RPM = 60 / T; where RPM represents the rotational speed in rpm; and T represents the time taken for each revolution in seconds.

[0069] Specifically, in step S4, the current location of the drone is determined by an RTK or GPS positioning system.

[0070] Specifically, such as Figure 2 , 3 As shown, in step S5, based on the current wind turbine design parameters (wind turbine yaw rotation speed, height, blade length, etc.) and safety requirements, a three-dimensional sector shaped like a double-edged axe, symmetrical about the wind turbine tower, is drawn to represent the wind turbine's hazardous area. The area outside this sector is the safe area. The hazardous area is divided into eight coordinate points, corresponding to different locations around the wind turbine. The eight coordinate points are as follows:

[0071] A(-w_d*cos@,w_h+w_d,w_d*sin@);

[0072] B(-w_d*cos@,w_h+w_d,-w_d*sin@);

[0073] C(w_d*cos@,w_h+w_d,w_d*sin@);

[0074] D(w_d*cos@,w_h+w_d,-w_d*sin@);

[0075] E(w_d*cos@,w_h-w_d,w_d*sin@);

[0076] F(w_d*cos@,w_h-w_d,-w_d*sin@);

[0077] G(-w_d*cos@,w_h-w_d,w_d*sin@);

[0078] H(-w_d*cos@,w_h-w_d,-w_d*sin@);

[0079] Where w_d is the length of the wind turbine blade; w_h is the height of the wind turbine tower; @ is the yaw angle of the wind turbine; the above eight coordinate points can be used to draw a sector with a side of a rectangle, the length of which is w_d*2 and the height of which is w_h; this sector corresponds to the dangerous area of ​​the wind turbine.

[0080] Specifically, in step S7, when the drone's location coordinates are within the safe area, the drone is in a safe state and no warning is required; when the drone's location coordinates are within the danger area, a warning signal must be issued immediately to prompt staff to take appropriate measures. The warning signal depends on the specific situation and may be an audible alarm, text prompt, flashing light, etc.

[0081] To help those skilled in the art understand the present invention, such as Figure 3 As shown below, the wind turbine monitoring program based on the calculation method of this invention, written using the ROS2 framework, can calculate the dynamic safety range and monitor the operating status of the wind turbine without shutting it down:

[0082] This program is a wind turbine monitoring program based on the ROS2 framework, which is mainly divided into three parts: message subscription, safe range calculation, and abnormal alarm.

[0083] Message Subscription: The program obtains the drone's location information and LiDAR data by subscribing to ROS2 messages. The message type is std_msgs::msg::Float64, which is floating-point data.

[0084] Safety range calculation: such as Figure 4 As shown, the safe range of the wind turbine is calculated using data from the lidar sensor, UAV flight control information, and camera information. The program first calculates the rotational speed range of the wind turbine blades and the rotational speed range of the wind turbine yaw angle, and then calculates the range of blade angle and amplitude. Finally, based on the range of blade angle and amplitude, the dangerous range of the wind turbine is calculated, and the area outside this range is considered the safe range.

[0085] Anomaly Alarm: The program monitors the drone's operating status in real time based on the calculated danger zone of the wind turbine and compares it with the danger zone. If the drone's operating status enters the danger zone, the program will publish an anomaly alarm message to a specified topic. The message type is std_msgs::msg::Float64, i.e., floating-point data.

[0086] Overall, this program adopts the ROS2 framework and makes full use of the ROS2 messaging mechanism to realize the dynamic safety range calculation and operational status monitoring of wind turbines. It features real-time performance and scalability, and can meet the wind turbine monitoring needs in different scenarios.

[0087] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.

Claims

1. A method for calculating the dynamic safety range of a wind turbine during non-stop inspection, characterized in that, Includes the following steps: Step S1: Calculate the safe range of the wind turbine and the yaw angle of the wind turbine using data from the lidar sensor, UAV flight control information, and camera information. Step S2: Calculate the speed of the wind turbine's yaw rotation; Step S3: Calculate the rotational speed, blade angle, and amplitude range of the wind turbine blades; Step S4: Obtain the current location of the drone; Step S5: Calculate the danger zone of the fan based on the range of the blade angle and the amplitude, and draw the safe zone. Based on the current design parameters and safety requirements of the wind turbine, a three-dimensional sector in the shape of a double-edged axe, symmetrical about the wind turbine tower, is drawn to represent the hazardous area of ​​the wind turbine. The area outside the hazardous area is the safe area. The hazardous area is divided into 8 coordinate points, corresponding to different locations around the wind turbine. The 8 coordinate points are as follows: A(-w_d * cos@, w_h + w_d, w_d * sin@); B(-w_d * cos@, w_h + w_d, -w_d * sin@); C(w_d * cos@, w_h + w_d, w_d * sin@); D(w_d * cos@, w_h + w_d, -w_d * sin@); E(w_d * cos@, w_h - w_d, w_d * sin@); F(w_d * cos@, w_h - w_d, -w_d * sin@); G(-w_d * cos@, w_h - w_d, w_d * sin@); H(-w_d * cos@, w_h - w_d, -w_d * sin@); Wherein, w_d is the length of the wind turbine blade; w_h is the height of the wind turbine tower; @ is the yaw angle of the wind turbine; the above eight coordinate points can be used to draw a sector, the side of which is a rectangle with a length of w_d*2 and a height of w_h; the sector corresponds to the dangerous area of ​​the wind turbine; Step S6: Compare the current position coordinates of the drone with the coordinates of the safe area to determine whether the drone is within the safe area; Step S7: Determine whether to take early warning measures to ensure the safety of the drone.

2. The method for calculating the dynamic safety range of wind turbine inspection without shutting down, as described in claim 1, is characterized in that... In step S1, there are two ways to calculate the yaw angle of the wind turbine: manual method S11 and automatic method S12.

3. The method for calculating the dynamic safety range of wind turbine inspection without shutting down, as described in claim 2, is characterized in that... The manual mode S11 process is as follows: S111: Raise the drone, monitor the positions of the drone and the wind turbine, and ensure that the distance between the drone and the wind turbine remains within a safe range; S112: After manually aligning the drone with the wind turbine hub, press the "Start Operation" button; S123: When the yaw angle of the UAV is greater than 180 degrees, the yaw angle of the wind turbine = the yaw angle of the UAV - 180 degrees; Otherwise, the yaw angle of the wind turbine is equal to the yaw angle of the UAV plus 180 degrees.

4. The method for calculating the dynamic safety range of wind turbine inspection without shutting down, as described in claim 3, is characterized in that... The automatic mode S12 process is as follows; S121: Perform distortion correction on the FPV image of the UAV; S122: Automatically identify and track the wind turbine hub using deep learning algorithms, thereby controlling the drone to face the wind turbine hub; S123: The image data is processed by computer vision algorithms to calculate the yaw angle of the current wind turbine.

5. The method for calculating the dynamic safety range of wind turbine inspection without shutting down, as described in claim 4, is characterized in that... In step S2, the process of calculating the speed of the yaw rotation of the wind turbine is as follows; S21: Set the starting point A of the drone flight at a safe distance from the front of the wind turbine hub; S22: After the UAV flies to the work point B and hovers, it begins to calculate the speed of the wind turbine's yaw rotation; S23: When the wind turbine yaws, the distance between the wind turbine blades and the UAV is detected by lidar to determine the direction of rotation of the wind turbine blades toward the UAV; when the distance decreases, the wind turbine blades rotate in the opposite direction to the UAV, the wind turbine blades approach the UAV, and the yaw rate is recorded as a negative value; when the distance increases, the wind turbine blades rotate in the direction the UAV is facing, the wind turbine blades move away from the UAV, and the yaw rate is recorded as a positive value. S24: Calculate the distance difference between the wind turbine blades and the UAV per unit time, and the distance from work point A to work point B, using the distance data detected by the lidar; work point A is the starting point A, and work point B is the hovering point; S25: Use inverse trigonometric functions to calculate the angle moved per unit time and convert the angle per second to radians per second; Based on the above steps, the angular velocity of the wind turbine's yaw rotation is calculated. The larger the angular velocity, the faster the wind turbine yaws, requiring a larger dynamic safety range to ensure the safe flight of the UAV.

6. The method for calculating the dynamic safety range of wind turbine inspection without shutting down, as described in claim 5, is characterized in that... The angular velocity of the wind turbine's yaw rotation is filtered and smoothed using a filtering algorithm to reduce the impact of noise and interference on the data, improve the accuracy and reliability of the data, and thus accurately calculate the dynamic safety range of the wind turbine, providing more reliable technical support for wind turbine monitoring and maintenance.

7. The method for calculating the dynamic safety range of wind turbine inspection without shutting down, as described in claim 5, is characterized in that... In step S3, the interval between two consecutive sweeps of the wind turbine blades is captured by the pre-positioned lidar, and the rotational speed of the wind turbine blades is calculated. The formula for calculating the rotational speed in one minute is: RPM = 60 / T; where RPM represents the rotational speed in rpm; and T represents the time taken for each revolution in seconds.

8. The method for calculating the dynamic safety range of wind turbine inspection without shutting down, as described in claim 5, is characterized in that... In step S4, the current location of the drone is determined by an RTK or GPS positioning system.

9. The method for calculating the dynamic safety range of wind turbine inspection without shutting down, as described in claim 1, is characterized in that... In step S7, if the location coordinates of the drone are within the safe area, then the drone is in a safe state and no warning is required; if the location coordinates of the drone are within the danger area, a warning signal must be issued immediately.

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