Unmanned aerial vehicle inspection and power transmission operation control method and system based on path planning

Abstract

The invention discloses an unmanned aerial vehicle inspection and power transmission operation control method and system based on path planning. The method comprises the following steps: constructing a three-dimensional environment model of a target area; constructing a total cost function at the cost of distance, weather risk, energy consumption and electromagnetic interference; taking the minimum total cost function as a target, and obtaining an inspection path of the unmanned aerial vehicle in the target area, so that the unmanned aerial vehicle flies based on the inspection path; in the flight process of the unmanned aerial vehicle, the inspection path is corrected in combination with the dynamic obstacle influence factors; the dynamic obstacle influence factor is determined by the distance between the unmanned aerial vehicle and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle; in the flight process of the unmanned aerial vehicle, the airborne electricity testing device is controlled to measure the line voltage, and the airborne ground wire hanging and dismounting device is controlled to carry out ground wire hanging and dismounting operation according to the measured line voltage. According to the embodiment of the invention, dynamic obstacles encountered by the unmanned aerial vehicle in the flight process can be avoided, and collision is avoided.

Description

Technical Field

[0001] The present application relates to the field of UAV technology, and in particular to a UAV power transmission operation control method and system based on path planning. Background Art

[0002] In recent years, the rapid development of drone technology has provided a new efficient and safe way for power transmission line inspection. With its flexible flight capabilities and powerful data collection capabilities, drones can conduct all-round inspections of power transmission lines. However, although drone technology has achieved certain application results in power transmission inspections, the existing drone inspection system still has some limitations: it does not take into account the unknown dynamic obstacles encountered during the inspection process, resulting in the inability to avoid dynamic obstacles, which makes the drone at risk of collision during flight. Summary of the invention

[0003] The present application provides a method and system for controlling power transmission operations of unmanned aerial vehicles based on path planning, so as to solve the problem that dynamic obstacles cannot be avoided in the prior art.

[0004] To achieve the above objectives, the present application provides a method for controlling a UAV inspection and power transmission operation based on path planning, including: Construct a three-dimensional environmental model of the target area; For the three-dimensional environment model, construct a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs; Taking the minimum total cost function as the goal, obtaining the inspection path of the UAV in the target area, so that the UAV flies based on the inspection path; During the flight of the UAV, the inspection path is corrected in combination with the dynamic obstacle influence factor; the dynamic obstacle influence factor is determined by the distance between the UAV and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle; During the flight of the UAV, the onboard electrical testing device is controlled to measure the line voltage, and the onboard grounding wire hanging and removing device is controlled to perform the grounding wire hanging and removing operation according to the measured line voltage.

[0005] As an improvement of the above solution, during the flight of the UAV, the inspection path is corrected in combination with the dynamic obstacle influence factor, including: When the dynamic obstacle impact factor is greater than the preset impact factor threshold, the path correction is calculated: in, is the current path correction, is the preset correction factor, is the current dynamic obstacle impact factor, To preset the impact factor threshold, is the preset constant, is the time constant; According to the path correction amount, the total cost function is updated to correct the inspection path.

[0006] As an improvement of the above solution, the dynamic obstacle impact factor is calculated according to the following formula: in, is the current risk factor of dynamic obstacle j, is the preset basic risk factor of dynamic obstacle j, is the current speed of the dynamic obstacle j, is the maximum speed of dynamic obstacles in the target area, is the current acceleration of the dynamic obstacle j, is the maximum acceleration of the dynamic obstacle in the target area, is the time constant; in, is the current dynamic obstacle impact factor, is the current risk factor of dynamic obstacle j, is the current distance between the UAV and the dynamic obstacle j, is the preset influence range parameter of dynamic obstacle j, N is the total number of dynamic obstacles in the target area, is the time constant, is an exponential function.

[0007] As an improvement of the above solution, for the three-dimensional environment model, a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs is constructed, including: Build distance cost for: in, , , is the i+1th position that the drone flies over, , , is the i-th position that the drone flies over, and n is the total number of positions that the drone flies over; Constructing the cost of weather risk for: in, Indicates the type of weather factor. represents the preset weight of the jth weather factor, represents the risk index of the jth weather factor; Building energy cost for: in, Indicates the speed at which the drone is flying and tilt angle The power consumption under the condition, M is the flight type of the UAV; Constructing electromagnetic interference costs for: in, Indicates the electromagnetic interference intensity of the drone at its current location. Indicates the maximum electromagnetic interference intensity that the drone can withstand; Constructing the total cost function for: in, The cost of distance The preset weights of The price of weather risk The preset weights of Energy cost The preset weights of The cost of electromagnetic interference The preset weights.

[0008] As an improvement to the above scheme, the weather risk cost Specifically, it is composed of wind speed factors, precipitation factors, temperature factors and humidity factors; Among them, the weather risk cost of wind speed factor for: In the formula, is the current wind speed, The maximum wind speed for safe drone flight; Weather risk cost of precipitation factor for: In the formula, is the current precipitation, is the maximum amount of precipitation that the drone can withstand; Temperature-related weather risk costs for: In the formula, is the current temperature, The best operating temperature for drones. is the operating temperature tolerance of the drone; Weather risk cost of humidity factor for: In the formula, is the current humidity, Maximum humidity for safe drone flight; Weather risk cost Specifically: in, , , and They are the preset weights of weather wind speed cost, weather precipitation cost, weather temperature cost and weather humidity cost respectively.

[0009] As an improvement of the above scheme, the onboard electric testing device is controlled to measure the line voltage, and the onboard grounding wire hanging and removing device is controlled to perform the grounding wire hanging and removing operation according to the measured line voltage, including: Control the onboard electric test device to measure the line voltage; If a hanging operation is required, when the measured line voltage is less than or equal to the preset voltage, the grounding wire tension is measured, and when the grounding wire tension is greater than or equal to the preset tension, the onboard grounding wire hanging and removing device is controlled to perform the grounding wire hanging operation; If removal operation is required, when the measured line voltage is less than or equal to the preset voltage, the electromagnetic field strength is measured. When the electromagnetic field strength is less than or equal to the preset strength, the onboard grounding wire removal device is controlled to perform the grounding wire removal operation.

[0010] As an improvement of the above solution, the UAV inspection and power transmission operation control method based on path planning also includes: During the flight of the drone, combined with the current learning rate Adjusting control parameters of a PID control algorithm, and controlling the flight of the UAV with the adjusted control parameters; in, , To preset the initial learning rate, is the deviation between the target value and the actual value in the PID control algorithm, is the time constant, is an exponential function.

[0011] As an improvement of the above solution, the step of constructing a three-dimensional environment model of the target area includes: Acquire a first depth map of the target area; Preprocessing and extracting features from the first depth map to obtain a second depth map; generating point cloud data according to the second depth map; A three-dimensional environment model is constructed according to the point cloud data.

[0012] As an improvement of the above solution, the step of obtaining a first depth map of the target area includes: Acquire a third depth map of the target area captured by multiple cameras; A weighted average fusion is performed on the plurality of the third depth maps to obtain a first depth map of the target area.

[0013] To achieve the above objectives, the present application also provides a UAV inspection and power transmission operation control system based on path planning, including: A model building module is used to build a three-dimensional environment model of the target area; A cost construction module, for constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs for the three-dimensional environment model; A path acquisition module, used to acquire the inspection path of the UAV in the target area with the minimum total cost function as the goal, so that the UAV flies based on the inspection path; A path correction module, used to correct the inspection path in combination with a dynamic obstacle influence factor during the flight of the UAV; the dynamic obstacle influence factor is determined by the distance between the UAV and the dynamic obstacle, the speed of the dynamic obstacle, and the acceleration of the dynamic obstacle; The hanging and removing operation module is used to control the airborne electrical testing device to measure the line voltage during the flight of the UAV, and control the airborne hanging and removing grounding wire device to perform the hanging and removing operation of the grounding wire according to the measured line voltage.

[0014] Compared with the prior art, the embodiment of the present application provides a method and system for controlling power transmission operations of unmanned aerial vehicles based on path planning, by constructing a three-dimensional environmental model of the target area; for the three-dimensional environmental model, constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as the cost; taking the minimum total cost function as the goal, obtaining the inspection path of the unmanned aerial vehicle in the target area, so that the unmanned aerial vehicle can fly based on the inspection path; during the flight of the unmanned aerial vehicle, the inspection path is corrected in combination with the dynamic obstacle influence factor; the dynamic obstacle influence factor is determined by the distance between the unmanned aerial vehicle and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle; during the flight of the unmanned aerial vehicle, the airborne electrical test device is controlled to measure the line voltage, and the airborne grounding wire hanging and removing device is controlled according to the measured line voltage to perform the grounding wire hanging and removing operation. It can be seen that the embodiment of the present application can avoid dynamic obstacles encountered by the unmanned aerial vehicle during flight and avoid collision by correcting the inspection path of the unmanned aerial vehicle based on the distance between the unmanned aerial vehicle and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle. In addition, the embodiments of the present application realize fully autonomous operation of drones in power transmission operations, covering the entire process from environmental perception, path planning to specific operations, especially key operations such as electrical testing and grounding wire hanging and removal, which do not require human participation. This not only reduces dependence on manual operation, reduces the need for operators to directly participate in high-altitude operations, significantly reduces operational risks, but also can cope with various complex operating environments, significantly improving the intelligence level, operational efficiency and operational safety of drones in power line inspections and power transmission operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of a method for controlling a UAV inspection and power transmission operation based on path planning provided in an embodiment of the present application; Figure 2 It is a structural block diagram of a UAV inspection and power transmission operation control system based on path planning provided in an embodiment of the present application; Figure 3 It is a structural block diagram of a UAV inspection and power transmission operation control device based on path planning provided in an embodiment of the present application. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0017] See also Figure 1 , Figure 1 : is a flow chart of a method for controlling a UAV inspection and power transmission operation based on path planning provided in an embodiment of the present application, wherein the method for controlling a UAV inspection and power transmission operation based on path planning comprises: S1, construct a three-dimensional environment model of the target area; It should be noted that building a 3D environment model is a key step for drones to perform tasks in complex environments. 3D environment model data is crucial for path planning and obstacle avoidance because they provide detailed information about the environment, allowing drones to deal with complex environments more intelligently and flexibly in actual operations. Static obstacles are included in the 3D environment model.

[0018] S2. Constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs for the three-dimensional environment model; It should be noted that the total cost function comprehensively considers four factors: distance, weather risk, energy consumption and electromagnetic interference. The distance cost is used to minimize the flight distance of the UAV. A shorter flight path can reduce flight time and energy consumption and improve operational efficiency. The weather risk cost assesses flight risks based on weather conditions to ensure that the UAV avoids bad weather and reduces potential safety hazards during flight. The energy consumption cost ensures that the UAV consumes the least energy when completing the mission, so as to extend the flight time and improve the economy of the mission. The electromagnetic interference cost is used to evaluate and avoid areas with high electromagnetic interference, ensure that the UAV is not interfered with, and ensure flight stability and data transmission reliability.

[0019] S3, taking the minimum total cost function as the goal, obtaining the inspection path of the UAV in the target area, so that the UAV flies based on the inspection path; In the embodiment of the present application, four factors, namely, distance, weather risk, energy consumption and electromagnetic interference, are comprehensively considered to ensure that path planning can balance efficiency and safety and find the optimal inspection path. For example, the total cost function can be calculated by the path search algorithm to find an optimal inspection path. During the path search process, different preset weights are combined to adapt to different mission requirements and environmental conditions to ensure the rationality of the drone inspection path.

[0020] S4. During the flight of the UAV, the inspection path is corrected in combination with a dynamic obstacle influence factor; the dynamic obstacle influence factor is determined by the distance between the UAV and the dynamic obstacle, the speed of the dynamic obstacle, and the acceleration of the dynamic obstacle; In the embodiment of the present application, an adaptive path correction algorithm can be used in combination with the dynamic obstacle influence factor to correct the inspection path, so that the drone can avoid dynamic obstacles and avoid collisions during flight.

[0021] S5. During the flight of the UAV, the onboard electrical testing device is controlled to measure the line voltage, and the onboard grounding wire hanging and removing device is controlled to perform grounding wire hanging and removing operations according to the measured line voltage.

[0022] It should be noted that power testing and ground wire installation and removal control are the core operating steps for drones to perform power transmission operations. The onboard power testing device can detect whether the line is energized to ensure the safety of ground wire installation or removal operations. If the line is out of power, the drone can continue to install or remove the ground wire, avoiding the risk of high voltage electricity.

[0023] In an optional embodiment, constructing a three-dimensional environment model of the target area includes: Acquire a first depth map of the target area; Preprocessing and extracting features from the first depth map to obtain a second depth map; generating point cloud data according to the second depth map; A three-dimensional environment model is constructed according to the point cloud data.

[0024] It should be noted that the depth map can be used to perceive and quantify the three-dimensional structure of the surrounding environment, providing a basis for the subsequent generation of point cloud data. By converting point cloud data into a network model using a three-dimensional modeling algorithm, an accurate three-dimensional scene can be generated. These scene data are crucial for path planning and obstacle avoidance because they provide detailed information about the environment, allowing drones to respond to complex environments more intelligently and flexibly in actual operations.

[0025] Specifically, preprocessing and feature extraction include: Image preprocessing: Gaussian filtering of the first depth map input Perform preprocessing to improve image quality and reduce noise: in, represents the convolution operation, is the standard deviation of the Gaussian kernel, x represents the column coordinate of the pixel, and y represents the row coordinate of the pixel; In the embodiment of the present application, the input first depth map is preprocessed by Gaussian filtering to remove noise and enhance the clarity and quality of the image. This step ensures that subsequent convolution operations can be based on higher quality input images, thereby improving the accuracy of target detection.

[0026] Convolutional layer operation: Use convolutional neural network to extract features from the preprocessed image. Assume that the convolution kernel used is , the output of the convolutional layer is expressed as : in, is the bias term, and represents the size of the convolution kernel, x represents the column coordinate of the pixel, y represents the row coordinate of the pixel, and the output after the ReLU activation function is ; In the embodiment of the present application, the convolutional neural network (CNN) extracts key features in the image through convolution operations. The function of the convolution layer is to automatically learn and extract feature maps in the image, which can capture the edges and textures of the transmission line and surrounding obstacles, providing important information for subsequent target classification.

[0027] Pooling layer operation: Pooling operation is performed on the feature map output by the convolution layer to reduce the amount of data and retain key features. The maximum pooling operation is: Among them, x represents the column coordinate of the pixel, y represents the row coordinate of the pixel, and represents the size of the convolution kernel and the pooling window size is ; In the embodiment of the present application, the pooling operation can reduce the size of the feature map, thereby reducing the computational complexity, while retaining important information in the image. Through the maximum pooling operation, the most significant features in the image can be concentrated and retained, making target detection more accurate.

[0028] The fully connected layer classifies the pooled features. Assuming there are m categories, the output of the fully connected layer is: in, is the linear combination output of category i, is the linear combination output of category j; Finally, the non-maximum suppression algorithm is used to generate the target detection box : In the embodiment of the present application, the non-maximum suppression algorithm suppresses the frames with high overlap and retains the most likely target frame. The fully connected layer classifies the pooled features and identifies the targets belonging to different categories in the image. The non-maximum suppression (NMS) algorithm is used to eliminate the detection frames with high overlap and finally output the unique and most likely target detection result to ensure the accuracy of target recognition.

[0029] In the embodiments of the present application, image preprocessing and feature extraction are the basic steps for the drone to identify and locate the power transmission lines and surrounding obstacles. By preprocessing the depth map, noise can be reduced, image quality can be improved, and subsequent feature extraction can be more accurate. The convolutional neural network (CNN) is used to extract important features in the image, which can efficiently identify the target area. The pooling operation reduces the amount of data, making the model more robust while retaining key features. The target detection results are further streamlined through the non-maximum suppression algorithm to ensure the accuracy of target detection, and ultimately achieve accurate identification and positioning of the power transmission lines and the surrounding environment.

[0030] The embodiment of the present application calculates the three-dimensional coordinates of each pixel point in the second depth map to form point cloud data, which represents the spatial distribution of the entire target area. This step converts the second depth map into a data format that can be used for three-dimensional modeling, making the subsequent three-dimensional environment model construction more intuitive and accurate.

[0031] The Marching Cubes algorithm is used to convert point cloud data into a 3D environment model, further improving the accuracy of the 3D environment model. This model is the basic data for subsequent path planning and obstacle avoidance; In addition, the drone can detect the electromagnetic field strength in the surrounding environment through the electromagnetic field camera installed. The calculation formula is: in, is the permittivity in vacuum, is the charge, In order to determine the distance between the UAV and the electromagnetic source, the high electromagnetic interference area in the three-dimensional environment model is marked through electromagnetic field perception, and an electric field strength distribution map is generated to avoid the UAV passing through the high electromagnetic interference area during path planning.

[0032] The embodiments of the present application utilize image processing calculations and three-dimensional modeling technology to accurately detect and model the transmission lines and their surrounding environment, so as to ensure that the drone can efficiently complete the inspection task along the optimal path, thereby greatly improving the inspection efficiency and data accuracy.

[0033] In an optional embodiment, acquiring a first depth map of the target area includes: Acquire a third depth map of the target area captured by multiple cameras; A weighted average fusion is performed on the plurality of the third depth maps to obtain a first depth map of the target area.

[0034] In the embodiment of the present application, the drone generates a depth map through a camera device to capture the three-dimensional structure information of the environment. The depth map is obtained by parallax calculation, which can directly reflect the distance between the camera and the object, providing basic data for three-dimensional modeling.

[0035] In the embodiment of the present application, the 3D modeling accuracy is further improved by fusing the depth maps taken by different cameras. Assume that the data taken by multiple cameras are , and , fused by weighted averaging: in, , and The preset weight of each camera can be adjusted dynamically according to the accuracy and confidence of the camera. In addition, the Kalman filter algorithm is used to perform real-time error correction on the depth map taken by the camera to reduce the impact of noise and improve the modeling accuracy. By fusing data from multiple cameras, the accuracy of 3D modeling is further improved. The weighted average method is used to integrate the measurement data of different cameras, and the Kalman filter algorithm is used to perform real-time error correction to reduce measurement noise and ensure the accuracy of the modeling results.

[0036] In an optional embodiment, constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs for the three-dimensional environment model includes: Build distance cost for: in, , , is the i+1th position that the drone flies over, , , is the i-th position that the drone flies over, and n is the total number of positions that the drone flies over; Constructing the cost of weather risk for: in, Indicates the type of weather factor; represents the preset weight of the jth weather factor, which refers to the risk contribution of the jth weather factor to the UAV; represents the risk index of the jth weather factor, which can be obtained based on real-time weather data; Building energy cost for: in, Indicates the speed at which the drone is flying and tilt angle The power consumption under the condition, M is the flight type of the UAV; Constructing electromagnetic interference costs for: in, Indicates the electromagnetic interference intensity of the drone at its current location. Indicates the maximum electromagnetic interference intensity that the drone can withstand; Constructing the total cost function for: in, The cost of distance The preset weights of The price of weather risk The preset weights of Energy cost The preset weights of The cost of electromagnetic interference The preset weights.

[0037] In an optional embodiment, the weather risk cost Specifically, it is composed of wind speed factors, precipitation factors, temperature factors and humidity factors; Among them, the weather risk cost of wind speed factor for: In the formula, is the current wind speed, The maximum wind speed for safe drone flight; Weather risk cost of precipitation factor for: In the formula, is the current precipitation, is the maximum amount of precipitation that the drone can withstand; Temperature-related weather risk costs for: In the formula, is the current temperature, The best operating temperature for drones. is the operating temperature tolerance of the drone; Weather risk cost of humidity factor for: In the formula, is the current humidity, Maximum humidity for safe drone flight; Weather risk cost Specifically: in, , , and The preset weights are respectively the weather wind speed cost, the weather precipitation cost, the weather temperature cost and the weather humidity cost, which can be determined according to the working environment and mission requirements of the UAV.

[0038] In the embodiment of the present application, the weather risk cost is subdivided into four main factors, each of which has a different impact on the flight safety of the UAV. The wind speed directly affects the flight stability of the UAV. High wind speed may make the UAV difficult to control, increasing the risk of flight loss of control. Therefore, the higher the wind speed, the greater the weather risk cost. Precipitation (such as rain and snow) will affect the electronic equipment and flight performance of the UAV. Heavy precipitation may cause sensor failure or structural damage, reducing flight safety. Therefore, the greater the precipitation, the higher the weather risk cost. Extreme temperature (too high or too low) will affect the battery performance and the working efficiency of the mechanical components of the UAV. The further the temperature deviates from the optimal working range, the greater the weather risk cost, which may cause flight interruption or equipment damage. A high humidity environment may cause the electronic components of the UAV to become damp, increasing the risk of short circuit or corrosion. In addition, excessive humidity may also affect the aerodynamic performance of the UAV. Therefore, the higher the current humidity, the greater the weather risk cost.

[0039] In an optional embodiment, during the flight of the UAV, the inspection path is corrected in combination with the dynamic obstacle influence factor, including: When the dynamic obstacle impact factor is greater than the preset impact factor threshold, the path correction is calculated: in, is the current path correction; is a preset correction factor used to control the magnitude of the correction; is the current dynamic obstacle impact factor; is the preset impact factor threshold; is a preset constant used to prevent the denominator from being zero. is the time constant; In an embodiment of the present application, the preset impact factor threshold can be set manually, or the average dangerous impact range and frequency of obstacles in the UAV operating environment can be estimated by statistical analysis of the distribution, danger level and historical flight data, and a relatively stable threshold can be obtained after a large number of flight tests.

[0040] According to the path correction amount, the total cost function is updated to correct the inspection path.

[0041] Exemplarily, the total cost function is updated according to the following formula: in, is the dynamic obstacle impact factor, is the total cost function before updating, is the updated total cost function. By solving the updated total cost function, the updated inspection path is obtained, and the UAV flies according to the updated inspection path.

[0042] In an optional embodiment, the dynamic obstacle impact factor is calculated according to the following formula: in, is the current risk factor of dynamic obstacle j, is the preset basic risk factor of dynamic obstacle j, is the current speed of the dynamic obstacle j, is the maximum speed of dynamic obstacles in the target area, is the current acceleration of the dynamic obstacle j, is the maximum acceleration of the dynamic obstacle in the target area, is the time constant; in, is the current dynamic obstacle impact factor, is the current risk factor of dynamic obstacle j, is the current distance between the UAV and the dynamic obstacle j, is the preset influence range parameter of dynamic obstacle j, N is the total number of dynamic obstacles in the target area, is the time constant, is an exponential function.

[0043] In the embodiment of the present application, the drone adjusts its inspection path in real time in combination with dynamic obstacle factors to ensure that the drone can still complete its mission safely in a complex and dynamic environment.

[0044] In an optional embodiment, the controlling the onboard electric testing device to measure the line voltage, and controlling the onboard grounding wire hanging and removing device to perform the grounding wire hanging and removing operation according to the measured line voltage, comprises: Control the onboard electric test device to measure the line voltage; If a hanging operation is required, when the measured line voltage is less than or equal to the preset voltage, the grounding wire tension is measured, and when the grounding wire tension is greater than or equal to the preset tension, the onboard grounding wire hanging and removing device is controlled to perform the grounding wire hanging operation; If removal operation is required, when the measured line voltage is less than or equal to the preset voltage, the electromagnetic field strength is measured. When the electromagnetic field strength is less than or equal to the preset strength, the onboard grounding wire removal device is controlled to perform the grounding wire removal operation.

[0045] In the embodiment of the present application, during the installation and removal of the grounding wire, the tension of the grounding wire is monitored to ensure the stability and firmness of the operation, to ensure that the grounding wire will not loosen or fall off during the installation and removal process, and to improve the safety of the overall operation. Electricity testing operation: The drone approaches the power transmission line and measures the line voltage through the onboard electricity testing device , if the voltage is detected to meet the conditions: , If the voltage is the preset voltage, it is confirmed that the line has been powered off and it is allowed to continue the operation. The voltage of the transmission line is measured by the onboard voltage test device to ensure the safety of the operating environment. If the line has been powered off, it is allowed to continue the grounding wire hanging or removal operation to avoid the risk of electric shock.

[0046] Grounding wire installation: The drone moves the onboard grounding wire installation device to the installation point. After positioning, the ground wire is installed and the tension is monitored during the operation. ,make sure: , To preset the tension to ensure that the grounding wire is firmly hung, avoid hanging the grounding wire in areas with high electromagnetic field strength, and choose areas with low or stable electromagnetic field strength to hang the grounding wire to reduce the impact of electromagnetic interference on the hanging process. The drone hangs the grounding wire at the specified position through precise positioning and monitors the tension of the grounding wire in real time to ensure its firmness. This step ensures that the grounding wire can be stably connected to the transmission line to avoid safety problems caused by loosening or falling off.

[0047] Ground wire removal: When the measured line voltage is less than or equal to the preset voltage, the electromagnetic field strength is measured. When the electromagnetic field strength is less than or equal to the preset strength, the onboard ground wire removal device is controlled to remove the ground wire. The onboard ground wire removal device removes the ground wire in the reverse order of the ground wire installation operation to ensure the safety of the drone and the working environment during the removal process. The removal process is accurately controlled to avoid safety accidents caused by misoperation.

[0048] In an optional embodiment, the UAV inspection and power transmission operation control method based on path planning further includes: During the flight of the drone, combined with the current learning rate Adjusting control parameters of a PID control algorithm, and controlling the flight of the UAV with the adjusted control parameters; in, , To preset the initial learning rate, is the deviation between the target value and the actual value, is the time constant, is an exponential function.

[0049] It is understandable that the flight of the UAV can be directly controlled by the PID control algorithm, and the PID control algorithm specifically controls the flight control parameters of the UAV.

[0050] In the embodiment of the present application, in order to enable the UAV to adapt to complex environmental changes more accurately and ensure flight stability and operation safety, an adaptive learning algorithm is used to dynamically adjust the flight control parameters and introduce an adaptive learning rate. , used to adjust the control parameters in the PID control algorithm: in, To preset the initial learning rate, is the deviation between the target value and the actual value in the PID control algorithm, is the time constant, It is an exponential function. Through this adaptive learning rate, the control parameters are optimized, so that the UAV can adapt to complex environmental changes more accurately, ensure flight stability and operation safety, and use the adaptive learning algorithm to dynamically adjust the parameters in the PID control, so that the UAV can adapt to changes in complex environments and maintain flight stability and safety. Through the adaptive learning rate, the control parameters can be optimized to further improve the accuracy and success rate of the operation.

[0051] The embodiment of the present application provides a method for controlling a drone inspection and power transmission operation based on path planning, by constructing a three-dimensional environmental model of the target area; for the three-dimensional environmental model, constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs; taking the minimum total cost function as the goal, obtaining the inspection path of the drone in the target area, so that the drone can fly based on the inspection path; during the flight of the drone, the inspection path is corrected in combination with the dynamic obstacle influence factor; the dynamic obstacle influence factor is determined by the distance between the drone and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle; during the flight of the drone, the airborne electrical test device is controlled to measure the line voltage, and the airborne grounding wire hanging and removing device is controlled according to the measured line voltage to perform the grounding wire hanging and removing operation. It can be seen that the embodiment of the present application can avoid dynamic obstacles encountered by the drone during flight and avoid collision by correcting the inspection path of the drone based on the distance between the drone and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle. In addition, the embodiments of the present application realize fully autonomous operation of drones in power transmission operations, covering the entire process from environmental perception, path planning to specific operations, especially key operations such as electrical testing and grounding wire hanging and removal, which do not require human participation. This not only reduces dependence on manual operation, reduces the need for operators to directly participate in high-altitude operations, significantly reduces operational risks, but also can cope with various complex operating environments, significantly improving the intelligence level, operational efficiency and operational safety of drones in power line inspections and power transmission operations.

[0052] See also Figure 2 , Figure 2 1 is a structural block diagram of a UAV inspection and power transmission operation control system 10 based on path planning provided in an embodiment of the present application. The UAV inspection and power transmission operation control system 10 based on path planning includes: A model building module 11 is used to build a three-dimensional environment model of the target area; A cost construction module 12 is used to construct a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs for the three-dimensional environment model; A path acquisition module 13, used to acquire the inspection path of the UAV in the target area with the minimum total cost function as the goal, so that the UAV flies based on the inspection path; A path correction module 14 is used to correct the inspection path in combination with a dynamic obstacle influence factor during the flight of the UAV; the dynamic obstacle influence factor is determined by the distance between the UAV and the dynamic obstacle, the speed of the dynamic obstacle, and the acceleration of the dynamic obstacle; The hanging and removing operation module 15 is used to control the onboard electric testing device to measure the line voltage during the flight of the UAV, and control the onboard hanging and removing grounding wire device to perform the hanging and removing operation of the grounding wire according to the measured line voltage.

[0053] Optionally, during the flight of the UAV, the inspection path is corrected in combination with the dynamic obstacle influence factor, including: When the dynamic obstacle impact factor is greater than the preset impact factor threshold, the path correction is calculated: in, is the current path correction, is the preset correction factor, is the current dynamic obstacle impact factor, To preset the impact factor threshold, is the preset constant, is the time constant; According to the path correction amount, the total cost function is updated to correct the inspection path.

[0054] Optionally, the dynamic obstacle impact factor is calculated according to the following formula: in, is the current risk factor of dynamic obstacle j, is the preset basic risk factor of dynamic obstacle j, is the current speed of the dynamic obstacle j, is the maximum speed of dynamic obstacles in the target area, is the current acceleration of the dynamic obstacle j, is the maximum acceleration of the dynamic obstacle in the target area, is the time constant; in, is the current dynamic obstacle impact factor, is the current risk factor of dynamic obstacle j, is the current distance between the UAV and the dynamic obstacle j, is the preset influence range parameter of dynamic obstacle j, N is the total number of dynamic obstacles in the target area, is the time constant, is an exponential function.

[0055] Optionally, constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs for the three-dimensional environment model includes: Build distance cost for: in, , , is the i+1th position that the drone flies over, , , is the i-th position that the drone flies over, and n is the total number of positions that the drone flies over; Constructing the cost of weather risk for: in, Indicates the type of weather factor. represents the preset weight of the jth weather factor, represents the risk index of the jth weather factor; Building energy cost for: in, Indicates the speed at which the drone is flying and tilt angle The power consumption under the condition, M is the flight type of the UAV; Constructing electromagnetic interference costs for: in, Indicates the electromagnetic interference intensity of the drone at its current location. Indicates the maximum electromagnetic interference intensity that the drone can withstand; Constructing the total cost function for: in, The cost of distance The preset weights of The price of weather risk The preset weights of Energy cost The preset weights of The cost of electromagnetic interference The preset weights.

[0056] Optionally, the weather risk cost Specifically, it is composed of wind speed factors, precipitation factors, temperature factors and humidity factors; Among them, the weather risk cost of wind speed factor for: In the formula, is the current wind speed, The maximum wind speed for safe drone flight; Weather risk cost of precipitation factor for: In the formula, is the current precipitation, is the maximum amount of precipitation that the drone can withstand; Temperature-related weather risk costs for: In the formula, is the current temperature, The best operating temperature for drones. is the operating temperature tolerance of the drone; Weather risk cost of humidity factor for: In the formula, is the current humidity, Maximum humidity for safe drone flight; Weather risk cost Specifically: in, , , and They are the preset weights of weather wind speed cost, weather precipitation cost, weather temperature cost and weather humidity cost respectively.

[0057] Optionally, controlling the onboard electric testing device to measure the line voltage, and controlling the onboard grounding wire hanging and removing device to perform the grounding wire hanging and removing operation according to the measured line voltage, includes: Control the onboard electric test device to measure the line voltage; If a hanging operation is required, when the measured line voltage is less than or equal to the preset voltage, the grounding wire tension is measured, and when the grounding wire tension is greater than or equal to the preset tension, the onboard grounding wire hanging and removing device is controlled to perform the grounding wire hanging operation; If removal operation is required, when the measured line voltage is less than or equal to the preset voltage, the electromagnetic field strength is measured. When the electromagnetic field strength is less than or equal to the preset strength, the onboard grounding wire removal device is controlled to perform the grounding wire removal operation.

[0058] Optionally, the UAV inspection and power transmission operation control device based on path planning also includes: The flight control module is used to combine the current learning rate during the flight of the drone Adjusting control parameters of a PID control algorithm, and controlling the flight of the UAV with the adjusted control parameters; in, , To preset the initial learning rate, is the deviation between the target value and the actual value in the PID control algorithm, is the time constant, is an exponential function.

[0059] Optionally, constructing a three-dimensional environment model of the target area includes: Acquire a first depth map of the target area; Preprocessing and extracting features from the first depth map to obtain a second depth map; generating point cloud data according to the second depth map; A three-dimensional environment model is constructed according to the point cloud data.

[0060] Optionally, acquiring a first depth map of the target area includes: Acquire a third depth map of the target area captured by multiple cameras; A weighted average fusion is performed on the plurality of the third depth maps to obtain a first depth map of the target area.

[0061] It is worth noting that the working process of each module in the path planning-based UAV inspection and power transmission operation control system 10 described in the embodiment of the present application can refer to the working process of the path planning-based UAV inspection and power transmission operation control method described in the above embodiment, and will not be repeated here.

[0062] The embodiment of the present application provides a UAV inspection and power transmission operation control system 10 based on path planning, by constructing a three-dimensional environmental model of the target area; for the three-dimensional environmental model, constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as the cost; taking the minimum total cost function as the goal, obtaining the inspection path of the UAV in the target area, so that the UAV can fly based on the inspection path; during the flight of the UAV, the inspection path is corrected in combination with the dynamic obstacle influence factor; the dynamic obstacle influence factor is determined by the distance between the UAV and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle; during the flight of the UAV, the airborne electrical test device is controlled to measure the line voltage, and the airborne grounding wire hanging and removing device is controlled according to the measured line voltage to perform the grounding wire hanging and removing operation. It can be seen that the embodiment of the present application can avoid dynamic obstacles encountered by the UAV during flight and avoid collision by correcting the inspection path of the UAV based on the distance between the UAV and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle. In addition, the embodiments of the present application realize fully autonomous operation of drones in power transmission operations, covering the entire process from environmental perception, path planning to specific operations, especially key operations such as electrical testing and grounding wire hanging and removal, which do not require human participation. This not only reduces dependence on manual operation, reduces the need for operators to directly participate in high-altitude operations, significantly reduces operational risks, but also can cope with various complex operating environments, significantly improving the intelligence level, operational efficiency and operational safety of drones in power line inspections and power transmission operations.

[0063] In addition, an embodiment of the present application further provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute the path planning-based drone inspection and power transmission operation control method as described in any of the above embodiments.

[0064] See also Figure 3 , Figure 3 : is a structural block diagram of a UAV inspection and power transmission operation control device 20 based on path planning provided in an embodiment of the present application, and the UAV inspection and power transmission operation control device 20 based on path planning includes: a processor 21, a memory 22, and a computer program stored in the memory 22 and executable on the processor 21. When the processor 21 executes the computer program, the steps in the above-mentioned UAV inspection and power transmission operation control method embodiment based on path planning are implemented. Alternatively, when the processor 21 executes the computer program, the functions of each module / unit in the above-mentioned device embodiments are implemented.

[0065] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory 22 and executed by the processor 21 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program in the path planning-based UAV inspection and power transmission operation control device 20.

[0066] The UAV inspection and power transmission operation control device 20 based on path planning may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will appreciate that the schematic diagram is merely an example of the UAV inspection and power transmission operation control device 20 based on path planning, and does not constitute a limitation on the UAV inspection and power transmission operation control device 20 based on path planning, and may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, the UAV inspection and power transmission operation control device 20 based on path planning may also include input and output devices, network access devices, buses, etc.

[0067] The processor 21 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor 21 is the control center of the path planning-based UAV inspection and power transmission operation control device 20, and uses various interfaces and lines to connect various parts of the entire path planning-based UAV inspection and power transmission operation control device 20.

[0068] The memory 22 can be used to store the computer program and / or module. The processor 21 realizes various functions of the unmanned aerial vehicle inspection and power transmission operation control device 20 based on path planning by running or executing the computer program and / or module stored in the memory 22 and calling the data stored in the memory 22. The memory 22 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory 22 can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart MediaCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0069] Wherein, if the module / unit integrated in the path planning-based UAV inspection and power transmission operation control device 20 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor 21, the steps of the above-mentioned method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0070] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0071] The above is a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications are also considered to be within the scope of protection of the present application.

Claims

1. A method for controlling UAV inspection and power transmission operations based on path planning, characterized in that: include: Construct a three-dimensional environmental model of the target area; For the three-dimensional environment model, construct a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs; Taking the minimum total cost function as the goal, obtaining the inspection path of the UAV in the target area, so that the UAV flies based on the inspection path; During the flight of the UAV, the inspection path is corrected in combination with the dynamic obstacle influence factor; the dynamic obstacle influence factor is determined by the distance between the UAV and the dynamic obstacle, the speed of the dynamic obstacle and the acceleration of the dynamic obstacle; During the flight of the UAV, the onboard electrical testing device is controlled to measure the line voltage, and the onboard grounding wire hanging and removing device is controlled to perform the grounding wire hanging and removing operation according to the measured line voltage.

2. The method for controlling UAV inspection and power transmission operations based on path planning according to claim 1, characterized in that: During the flight of the UAV, the inspection path is corrected in combination with the dynamic obstacle influence factor, including: When the dynamic obstacle impact factor is greater than the preset impact factor threshold, the path correction is calculated: in, is the current path correction, is the preset correction factor, is the current dynamic obstacle impact factor, To preset the impact factor threshold, is the preset constant, is the time constant; According to the path correction amount, the total cost function is updated to correct the inspection path.

3. The method for controlling UAV inspection and power transmission operations based on path planning according to claim 2, characterized in that: The dynamic obstacle impact factor is calculated according to the following formula: in, is the current risk factor of dynamic obstacle j, is the preset basic risk factor of dynamic obstacle j, is the current speed of the dynamic obstacle j, is the maximum speed of dynamic obstacles in the target area, is the current acceleration of the dynamic obstacle j, is the maximum acceleration of the dynamic obstacle in the target area, is the time constant; in, is the current dynamic obstacle impact factor, is the current risk factor of dynamic obstacle j, is the current distance between the UAV and the dynamic obstacle j, is the preset influence range parameter of dynamic obstacle j, N is the total number of dynamic obstacles in the target area, is the time constant, is an exponential function.

4. The method for controlling UAV inspection and power transmission operations based on path planning according to claim 1, characterized in that: The method of constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs for the three-dimensional environment model includes: Build distance cost for: in, , , is the i+1th position that the drone flies over, , , is the i-th position that the drone flies over, and n is the total number of positions that the drone flies over; Constructing the cost of weather risk for: in, Indicates the type of weather factor. represents the preset weight of the jth weather factor, represents the risk index of the jth weather factor; Building energy cost for: in, Indicates the speed at which the drone is flying and tilt angle The power consumption under the condition, M is the flight type of the UAV; Constructing electromagnetic interference costs for: in, Indicates the electromagnetic interference intensity of the drone at its current location. Indicates the maximum electromagnetic interference intensity that the drone can withstand; Constructing the total cost function for: in, The cost of distance The preset weights of The price of weather risk The preset weights of Energy cost The preset weights of The cost of electromagnetic interference The preset weights.

5. The method for controlling UAV inspection and power transmission operations based on path planning according to claim 4, characterized in that: Weather risk cost Specifically, it is composed of wind speed factors, precipitation factors, temperature factors and humidity factors; Among them, the weather risk cost of wind speed factor for: In the formula, is the current wind speed, The maximum wind speed for safe drone flight; Weather risk cost of precipitation factor for: In the formula, is the current precipitation, is the maximum amount of precipitation that the drone can withstand; Temperature-related weather risk costs for: In the formula, is the current temperature, The best operating temperature for drones. is the operating temperature tolerance of the drone; Weather risk cost of humidity factor for: In the formula, is the current humidity, Maximum humidity for safe drone flight; Weather risk cost Specifically: in, , , and They are the preset weights of weather wind speed cost, weather precipitation cost, weather temperature cost and weather humidity cost respectively.

6. The method for controlling UAV inspection and power transmission operations based on path planning according to claim 1, characterized in that: The control of the onboard electric test device to measure the line voltage and the control of the onboard ground wire hanging and removing device to perform the ground wire hanging and removing operation according to the measured line voltage includes: Control the onboard electric test device to measure the line voltage; If a hanging operation is required, when the measured line voltage is less than or equal to the preset voltage, the grounding wire tension is measured, and when the grounding wire tension is greater than or equal to the preset tension, the onboard grounding wire hanging and removing device is controlled to perform the grounding wire hanging operation; If removal operation is required, when the measured line voltage is less than or equal to the preset voltage, the electromagnetic field strength is measured. When the electromagnetic field strength is less than or equal to the preset strength, the onboard grounding wire removal device is controlled to perform the grounding wire removal operation.

7. The method for controlling UAV inspection and power transmission operations based on path planning according to claim 1, characterized in that: The UAV inspection and power transmission operation control method based on path planning also includes: During the flight of the drone, combined with the current learning rate Adjusting control parameters of a PID control algorithm, and controlling the flight of the UAV with the adjusted control parameters; in, , To preset the initial learning rate, is the deviation between the target value and the actual value in the PID control algorithm, is the time constant, is an exponential function.

8. The method for controlling UAV inspection and power transmission operations based on path planning according to claim 1, characterized in that: The step of constructing a three-dimensional environment model of the target area includes: Acquire a first depth map of the target area; Preprocessing and extracting features from the first depth map to obtain a second depth map; generating point cloud data according to the second depth map; A three-dimensional environment model is constructed according to the point cloud data.

9. The method for controlling UAV inspection and power transmission operations based on path planning according to claim 8, characterized in that: The step of acquiring a first depth map of the target area includes: Acquire a third depth map of the target area captured by multiple cameras; A weighted average fusion is performed on the plurality of the third depth maps to obtain a first depth map of the target area.

10. A UAV inspection and power transmission operation control system based on path planning, characterized in that: include: A model building module is used to build a three-dimensional environment model of the target area; A cost construction module, for constructing a total cost function with distance, weather risk, energy consumption and electromagnetic interference as costs for the three-dimensional environment model; A path acquisition module, used to acquire the inspection path of the UAV in the target area with the minimum total cost function as the goal, so that the UAV flies based on the inspection path; A path correction module, used to correct the inspection path in combination with a dynamic obstacle influence factor during the flight of the UAV; the dynamic obstacle influence factor is determined by the distance between the UAV and the dynamic obstacle, the speed of the dynamic obstacle, and the acceleration of the dynamic obstacle; The hanging and removing operation module is used to control the airborne electrical testing device to measure the line voltage during the flight of the UAV, and control the airborne hanging and removing grounding wire device to perform the hanging and removing operation of the grounding wire according to the measured line voltage.

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