An unmanned aerial vehicle (UAV) based intelligent inspection method and system for a wind farm

Abstract

The application discloses an unmanned aerial vehicle (UAV) based intelligent inspection method and system for a wind farm, and belongs to the technical field of UAV inspection. The method comprises the following steps: a control end determines a wind farm inspection scheme and sends the wind farm inspection scheme to an inspection UAV; the inspection UAV inspects each inspection device according to the wind farm inspection scheme, obtains inspection data of each inspection device, and sends the inspection data to the control end; the control end determines target abnormal data, corresponding target abnormal wind turbine devices and a wind turbine repair scheme, sends the wind turbine repair scheme to the inspection UAV, and sends a stop running instruction to each target abnormal wind turbine device; and the inspection UAV repairs each target abnormal wind turbine device according to the wind turbine repair scheme and a wind turbine spraying device. The scheme can quickly and comprehensively inspect the wind farm, improves the inspection efficiency and reduces the labor cost. When the repair standard is met, the wind turbine is automatically repaired, the repair efficiency is improved, and the repair safety is improved.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) inspection technology, and in particular to an intelligent inspection method and system for wind power plants based on UAVs. Background Technology

[0002] With the increasing global demand for renewable energy, wind power, as a clean and renewable energy source, is playing an increasingly important role. To ensure the stable and safe operation of wind farms, regular inspections are crucial.

[0003] Traditional wind farm inspection methods mainly rely on manual inspection. Inspectors need to climb to the height of the wind turbine to check them one by one, and then check the appearance and performance of the cables along the cable route. When the inspection finds a fault in the wind turbine or cable, the maintenance personnel are notified to carry out repairs.

[0004] However, manual inspection is not only inefficient but also poses a high safety risk. Notifying maintenance personnel to repair problems after they occur during inspections also results in low fault repair efficiency and increases labor costs. Summary of the Invention

[0005] This application provides an intelligent inspection method and system for wind power plants based on unmanned aerial vehicles (UAVs). It solves the problems that manual inspection of wind power plants is not only inefficient and poses a high safety risk, but also that the efficiency of fault repair is low and the labor cost is increased when problems are notified to maintenance personnel after they are discovered during inspection.

[0006] According to a first aspect of this application, an intelligent inspection method for wind power farms based on unmanned aerial vehicles (UAVs) is provided, the method comprising:

[0007] The control terminal acquires equipment information, environmental information, and inspection drone information for each inspection device in the wind farm. Based on the equipment information, environmental information, and inspection drone information, it determines the wind farm inspection plan and sends the wind farm inspection plan to the inspection drone. The inspection device consists of wind turbine equipment and cables.

[0008] The inspection drone inspects each inspection device according to the wind power plant inspection plan, obtains inspection data for each inspection device in the wind power plant, and sends the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data, and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data, and cable electrical data;

[0009] The control terminal identifies the inspection data of each inspection device according to the preset inspection data identification scheme. If abnormal fan inspection data is identified, the abnormal fan device is determined based on the abnormal fan inspection data, and it is also determined whether there is abnormal fan inspection data that meets the preset automatic fan repair standard; wherein, the number of abnormal fan inspection data is at least one, and the number of abnormal fan devices is at least one.

[0010] If there is abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards, the control terminal will take the abnormal wind turbine inspection data as target abnormal data and determine the target abnormal wind turbine equipment corresponding to the target abnormal data; wherein, the number of target abnormal data is at least one, and the number of target abnormal wind turbine equipment is at least one.

[0011] The control terminal acquires the equipment information of each target abnormal wind turbine, determines the wind turbine repair plan for each target abnormal wind turbine based on the equipment information and the target abnormal data of each target abnormal wind turbine, sends the wind turbine repair plan to the inspection drone, and sends a stop operation command to each target abnormal wind turbine.

[0012] The inspection drone repaired the abnormal wind turbine equipment of each target according to the aforementioned wind turbine repair plan and wind turbine spraying device.

[0013] Furthermore, after determining whether there is abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards, the method further includes:

[0014] If there is no abnormal fan inspection data that meets the preset automatic fan repair standard, the control terminal sends a stop operation command to the abnormal fan equipment.

[0015] The control terminal acquires the equipment information of the abnormal fan equipment and sends the abnormal fan inspection data and the equipment information to the staff's handheld terminal, so that the staff can carry out on-site repair of the abnormal fan equipment based on the abnormal fan inspection data and the equipment information.

[0016] Furthermore, the control terminal acquires equipment information, environmental information, and inspection drone information for each inspection device at the wind farm, and determines a wind farm inspection plan based on the equipment information, environmental information, and inspection drone information, including:

[0017] The control terminal acquires environmental information of the wind farm. If the environmental information meets the preset acquisition standard, the location information and parameter information of each inspection device are determined based on the equipment information.

[0018] The inspection route of the inspection drone in the wind farm is determined based on the equipment location information, and the inspection data collection route of the inspection drone in front of each inspection device is determined based on the parameter information, the environmental information and the inspection drone information.

[0019] The inspection plan for the wind power plant is determined based on the inspection route and the inspection data collection route.

[0020] Furthermore, based on the parameter information, the environmental information, and the inspection drone information, the inspection data collection route of the inspection drone in front of each inspection device is determined, including:

[0021] The type of the inspection equipment is determined based on the parameter information. If it is a wind turbine, the blade type, tower size, temperature monitoring point, and mechanical condition monitoring point of the wind turbine are determined based on the parameter information.

[0022] The blade rotation trajectory of the wind turbine is determined based on the blade type, the wind speed and wind direction are determined based on the environmental information, and the speed information of the inspection drone is determined based on the inspection drone information.

[0023] The inspection drone determines the wind turbine image acquisition route in front of the wind turbine equipment based on the blade rotation trajectory, wind speed information, wind direction information, tower size, and speed information; wherein, the wind turbine image acquisition route includes the blade opening posture;

[0024] The inspection drone determines the data collection route for wind turbine status in front of the wind turbine equipment based on the temperature monitoring point, the mechanical status monitoring point, the wind speed information, the wind direction information, and the speed information.

[0025] The inspection drone determines the wind turbine data acquisition route in front of the wind turbine equipment based on the wind turbine image acquisition route and the wind turbine status data acquisition route.

[0026] Furthermore, after determining the type information of the inspection equipment based on the parameter information, the method further includes:

[0027] If it is a cable, then the length information of the cable, the location information of the accessory equipment, the temperature monitoring point and the electrical data monitoring point are determined according to the parameter information; the wind speed information and the wind direction information are determined according to the environmental information; and the speed information of the inspection drone is determined according to the inspection drone information.

[0028] The inspection drone determines the cable image acquisition route in front of the cable based on the length information, the location information of the accessory equipment, the wind speed information, the wind direction information, and the speed information.

[0029] The inspection drone determines the cable status data collection route in front of the cable based on the temperature monitoring point, the electrical data monitoring point, the wind speed information, the wind direction information, and the speed information.

[0030] The cable data acquisition route of the inspection drone in front of the cable is determined based on the cable image acquisition route and the cable status data acquisition route.

[0031] Furthermore, determine whether there is any abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards, including:

[0032] Determine the data type of each abnormal wind turbine inspection data. If it is wind turbine image data, determine the degree of wind turbine damage, the area of ​​wind turbine damage, and the location of wind turbine damage based on the wind turbine image data.

[0033] Determine whether the degree of damage to the fan, the area of ​​damage to the fan, and the location of damage to the fan meet the preset automatic repair standards for the fan.

[0034] Furthermore, after the control terminal identifies the inspection data of each inspection device according to the preset inspection data identification scheme, the method further includes:

[0035] If abnormal cable inspection data is detected, the abnormal cable is identified based on the abnormal cable inspection data, and it is determined whether there is abnormal cable inspection data that meets the preset cable automatic repair standard; wherein, the number of abnormal cable inspection data is at least one, and the number of abnormal cables is at least one.

[0036] If abnormal cable inspection data that meets the preset automatic cable repair standard exists, the control terminal will use the abnormal cable inspection data as target abnormal data and determine the target abnormal cable corresponding to the target abnormal data; wherein, the number of target abnormal data is at least one, and the number of target abnormal cables is at least one.

[0037] The control terminal acquires the equipment information of the target abnormal cable, determines a cable repair plan based on the equipment information and the target abnormal data, and sends the cable repair plan to the inspection drone.

[0038] The inspection drone repairs the target abnormal cable according to the cable repair plan and the cable spraying device and / or cable accessory equipment repair device.

[0039] Furthermore, after determining whether there is abnormal cable inspection data that meets the preset automatic cable repair standards, the method further includes:

[0040] If no abnormal cable inspection data that meets the preset automatic cable repair standards is found, the control terminal acquires the equipment information of the abnormal cable and sends the abnormal cable inspection data and the equipment information to the staff's handheld terminal, so that the staff can repair the abnormal cable on-site based on the abnormal cable inspection data and the equipment information.

[0041] Furthermore, determine whether there is any abnormal cable inspection data that meets the preset automatic cable repair standards, including:

[0042] Determine the data type of the abnormal cable inspection data. If it is cable image data, determine the cable repair type based on the cable image data.

[0043] If the damage is cable, the degree of cable damage, the area of ​​cable damage, and the location of cable damage are determined based on the cable image data. It is then determined whether the degree of cable damage, the area of ​​cable damage, and the location of cable damage meet the preset automatic cable repair standards.

[0044] If the loose cable accessory is identified, the type of loose accessory is determined based on the cable image data, and it is then determined whether the type of loose accessory meets the preset automatic cable repair standard.

[0045] According to a second aspect of this application, an intelligent inspection system for wind farms based on unmanned aerial vehicles (UAVs) is provided, characterized in that the system comprises:

[0046] The inspection plan determination module is used by the control terminal to acquire equipment information, environmental information, and inspection drone information of each inspection device in the wind power plant, determine the wind power plant inspection plan based on the equipment information, environmental information, and inspection drone information, and send the wind power plant inspection plan to the inspection drone; wherein, the inspection device consists of wind turbine equipment and cables;

[0047] The inspection data acquisition module is used for the inspection drone to inspect each inspection device according to the wind power plant inspection plan, obtain the inspection data of each inspection device in the wind power plant, and send the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data and cable electrical data;

[0048] The inspection data identification module is used by the control terminal to identify the inspection data of each inspection device according to the preset inspection data identification scheme. If abnormal fan inspection data is identified, the abnormal fan device is determined based on the abnormal fan inspection data, and it is also determined whether there is abnormal fan inspection data that meets the preset automatic fan repair standard. The number of abnormal fan inspection data is at least one, and the number of abnormal fan devices is at least one.

[0049] The abnormal fan data determination module is used to determine the target abnormal fan equipment corresponding to the abnormal fan inspection data if there is abnormal fan inspection data that meets the preset automatic fan repair standards; wherein, the number of target abnormal data is at least one, and the number of target abnormal fan equipment is at least one.

[0050] The wind turbine repair plan determination module is used to obtain equipment information of each target abnormal wind turbine equipment from the control terminal, determine the wind turbine repair plan of each target abnormal wind turbine equipment based on the equipment information and the target abnormal data of each target abnormal wind turbine equipment, send the wind turbine repair plan to the inspection drone, and send a stop operation command to each target abnormal wind turbine equipment.

[0051] The wind turbine repair module is used by the inspection drone to repair abnormal wind turbine equipment of each target according to the wind turbine repair plan and the wind turbine spraying device.

[0052] In this embodiment, the control terminal acquires equipment information, environmental information, and inspection drone information for each inspection device in the wind power plant. Based on this information, the control terminal determines a wind power plant inspection plan and sends it to the inspection drone. The inspection devices consist of wind turbines and cables. The inspection drone inspects each device according to the wind power plant inspection plan, obtaining inspection data for each device, and sends this data to the control terminal. The inspection data consists of wind turbine inspection data and cable inspection data. The wind turbine inspection data includes wind turbine image data, wind turbine temperature data, and wind turbine mechanical status data. The cable inspection data includes cable image data, cable temperature data, and cable electrical data. The control terminal identifies the inspection data of each device according to a preset inspection data identification scheme. If abnormal wind turbine inspection data is identified, the abnormal wind turbine inspection data is processed. The system identifies abnormal wind turbine equipment and determines whether there is abnormal wind turbine inspection data that meets preset automatic wind turbine repair standards. The number of abnormal wind turbine inspection data and the number of abnormal wind turbine equipment are both at least one. If abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards exists, the control terminal uses this abnormal wind turbine inspection data as target abnormal data and identifies the target abnormal wind turbine equipment corresponding to the target abnormal data. The number of target abnormal data and the number of target abnormal wind turbine equipment are both at least one. The control terminal acquires equipment information for each target abnormal wind turbine equipment, determines a wind turbine repair plan for each target abnormal wind turbine equipment based on the equipment information and the target abnormal data for each target abnormal wind turbine equipment, sends the wind turbine repair plan to the inspection drone, and sends a stop-operation command to each target abnormal wind turbine equipment. The inspection drone repairs each target abnormal wind turbine equipment according to the wind turbine repair plan and the wind turbine spraying device. The aforementioned intelligent inspection method for wind farms based on drones enables automated inspections of wind farms, allowing for rapid and comprehensive checks, shortening inspection time, improving efficiency, and reducing labor costs. Automatic repair of wind turbines when repair standards are met improves repair efficiency; eliminating the need for manual repair reduces labor costs and enhances repair safety.

[0053] It should be understood that the description in the Summary Section is not intended to limit the key or essential features of the embodiments of this application, nor is it intended to restrict the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0054] The above and other features, advantages, and aspects of the embodiments of this application will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the scope of the application. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0055] Figure 1 This is a flowchart illustrating the intelligent inspection method for wind farms based on unmanned aerial vehicles (UAVs) provided in Embodiment 1 of this application.

[0056] Figure 2 This is a flowchart illustrating the intelligent inspection method for wind farms based on unmanned aerial vehicles (UAVs) provided in Embodiment 2 of this application.

[0057] Figure 3 This is a flowchart illustrating the intelligent inspection method for wind power plants based on unmanned aerial vehicles (UAVs) provided in Embodiment 3 of this application.

[0058] Figure 4 This is a schematic diagram of the structure of the intelligent inspection system for wind farms based on unmanned aerial vehicles provided in Embodiment 4 of this application. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0060] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0061] The intelligent inspection method for wind farms based on unmanned aerial vehicles (UAVs) provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0062] Example 1

[0063] Figure 1 This is a flowchart illustrating the intelligent inspection method for wind farms based on unmanned aerial vehicles (UAVs) provided in Embodiment 1 of this application. Figure 1 As shown, the specific steps include the following:

[0064] S101, the control terminal acquires equipment information, environmental information, and inspection drone information of each inspection device in the wind power plant, determines the wind power plant inspection plan based on the equipment information, environmental information, and inspection drone information, and sends the wind power plant inspection plan to the inspection drone; wherein, the inspection device consists of wind turbine equipment and cables.

[0065] Firstly, the application scenario of this solution can be as follows: the control terminal determines the inspection plan for the wind power plant and sends it to the inspection drone; the inspection drone collects inspection data according to the inspection plan and sends it to the control terminal; the control terminal identifies whether there is abnormal data and whether it can be automatically repaired by the inspection drone; if so, it determines the automatic repair plan and sends it to the inspection drone; the inspection drone then calls the corresponding repair device to repair the abnormal equipment corresponding to the abnormal data according to the automatic repair plan.

[0066] Based on the above usage scenarios, it is understood that the implementing entity of this application may be an intelligent inspection system for wind power plants based on drones that integrates functions such as determining inspection plans, collecting inspection data, formulating repair plans for abnormal equipment, and repairing abnormal equipment. No further limitations are imposed here.

[0067] In this scheme, the control end can be a command center or a computer system, which is responsible for collecting, processing and analyzing information from various inspection equipment in the wind power plant, and formulating inspection plans based on this information.

[0068] A wind farm can be a collection of all wind turbine generators and supporting power transmission and transformation equipment in an area with good wind energy resources. Specifically, it can be a place where multiple grid-connected wind turbine generators are installed in a site with good wind resources, arranged in an array according to the terrain and prevailing wind direction, forming a group to supply power to the grid.

[0069] Equipment information can include various parameters of the wind turbine equipment and cables, such as equipment location, equipment model, and equipment performance parameters. Among these, equipment performance parameters can be specific values ​​or indicators that describe the performance and characteristics of these devices under specific operating conditions.

[0070] Environmental information can refer to the meteorological conditions around the wind farm, that is, various meteorological factors that affect the operation and performance of the wind farm. Specifically, it can include wind speed, wind direction, precipitation, extreme weather, air pressure, temperature, and humidity.

[0071] The information on the inspection drone can include the drone's model, identification, remaining battery power, and flight speed.

[0072] A wind farm inspection plan can be a specific inspection plan developed based on equipment information, environmental information, and inspection drone information. Specifically, it can include inspection time, inspection route, inspection frequency, and inspection methods for each piece of equipment.

[0073] Inspection drones refer to drones that use unmanned driving technology to carry out aerial inspection missions. They can be equipped with various sensors and cameras to inspect the equipment in wind power plants.

[0074] Wind turbine equipment can refer to wind turbine generators in wind farms, which are devices that can directly convert wind energy into electrical energy.

[0075] Cables can refer to cable systems used for power transmission and connection within wind farms.

[0076] Information can be collected from various sources, including equipment data from databases, environmental data from weather stations, and drone data from built-in sensors. The control unit then integrates this information via wireless communication. Pre-set environmental conditions for inspection can be configured; if these conditions are met, the drone can proceed with the inspection, avoiding deployment in extreme weather conditions. Based on the equipment data, the distribution of each device is determined, and an inspection route is planned. This route should cover all equipment while minimizing overlapping areas. Appropriate inspection methods can be determined for different equipment types. For wind turbines, visual inspection, vibration analysis, and infrared thermal imaging scanning can be used; for cables, visual inspection and electrical performance testing can be performed. Combining the inspection route and methods, a detailed inspection plan can be developed. This plan includes the inspection route, inspection time points for each device, specific inspection content, and expected completion time. The wind farm inspection plan is then transmitted to the inspection drone via wireless communication.

[0077] S102, the inspection drone inspects each inspection device according to the wind power plant inspection plan, obtains inspection data for each inspection device in the wind power plant, and sends the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data, and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data, and cable electrical data. 。

[0078] Inspection data can refer to data obtained from drones inspecting various inspection equipment in a wind power plant, used to assess the equipment status and operation.

[0079] Wind turbine inspection data refers to the inspection data obtained for wind turbine equipment in a wind farm, including wind turbine image data, wind turbine temperature data, and wind turbine mechanical status data.

[0080] Wind turbine image data can be images or video data of wind turbine equipment captured by a camera. It is used to check the appearance and surface condition of the wind turbine, as well as any possible damage or abnormalities, such as whether the blades have cracks, corrosion or other visible damage.

[0081] Fan temperature data can be the temperature data of the fan equipment surface or inside, used to assess the heat distribution and operating status of the fan. Specifically, it can include generator temperature, bearing temperature, and gearbox temperature, etc.

[0082] Wind turbine mechanical condition data can include various operating parameters of the wind turbine's mechanical components, such as vibration data, noise levels, speed, and torque, which can help detect whether there are mechanical problems with the wind turbine.

[0083] Cable inspection data can refer to the inspection data obtained for cable equipment in wind farms, including cable image data, cable temperature data, and cable electrical data.

[0084] Cable image data can be image data of cable equipment captured by a camera or other image acquisition device, used to inspect the appearance of the cable and identify any damage, aging, or abnormalities.

[0085] Cable temperature data can be collected from the surface or interior of the cable, and is used to assess the temperature distribution and operating condition of the cable.

[0086] Cable electrical data can include electrical parameters such as voltage, current, and resistance, which are used to evaluate the electrical performance and operating status of the cable.

[0087] The inspection drone can receive wind farm inspection plans from the control terminal, which may include information such as inspection route, inspection time, type of equipment to be inspected, and inspection method. According to the inspection plan, the drone can take off and fly to the location of each piece of equipment within the wind farm along the predetermined inspection route. Upon arrival at each piece of equipment, the drone can perform corresponding inspection tasks according to the plan. For wind turbines, the drone can use its onboard camera to capture images of the turbine and its onboard temperature sensor to measure the surface or internal temperature of the turbine, obtaining turbine temperature data. Vibration sensors and other devices can be used to monitor the vibration of the turbine, obtaining mechanical status data. For cable equipment, the drone can use its camera to capture images of the cable and its temperature sensor to measure the surface or internal temperature of the cable, obtaining cable temperature data. Current sensors and other devices can be used to detect the electrical parameters of the cable, obtaining cable electrical data. Finally, the data is integrated into the inspection data and transmitted to the control terminal via wireless communication technology.

[0088] S103, the control terminal identifies the inspection data of each inspection device according to the preset inspection data identification scheme. If abnormal fan inspection data is identified, the abnormal fan device is determined according to the abnormal fan inspection data, and it is determined whether there is abnormal fan inspection data that meets the preset automatic fan repair standard; wherein, the number of abnormal fan inspection data is at least one, and the number of abnormal fan devices is at least one.

[0089] The pre-defined inspection data identification scheme can be a method for processing and analyzing inspection data collected by drones. Specifically, for wind turbine inspection data, image recognition technology can be used to analyze wind turbine image data and identify defects such as surface damage and corrosion. Temperature sensor data analysis technology can be used to assess wind turbine temperature data and identify abnormalities such as overheating. Vibration analysis technology can be used to process wind turbine mechanical condition data and diagnose problems such as imbalance and loosening. For cable inspection data, image recognition technology can be used to analyze cable image data and identify problems such as cable damage and wear. Cable temperature data can be analyzed to identify hot spots that may lead to insulation aging. Electrical testing equipment can be used to analyze cable electrical performance data and assess the cable's conductivity and insulation condition.

[0090] Abnormal fan inspection data refers to fan inspection data that is identified as being outside the normal operating range during the analysis process. The causes of the abnormality may include abnormal temperature, abnormal vibration, and signs of damage in the images.

[0091] Abnormal wind turbine equipment can refer to wind turbine generators in wind farms that exhibit abnormalities detected through inspection drones or other monitoring methods. Specifically, these abnormal wind turbines can manifest in various forms, such as abnormal temperature, abnormal vibration, and signs of damage in images. These may all indicate abnormal conditions during the wind turbine's operation, requiring further inspection and maintenance.

[0092] The preset automatic wind turbine repair criteria refer to the conditions used to determine whether an automatic repair operation by drone is suitable when an abnormality is detected in the wind turbine. Specifically, these criteria may include the type, location, severity, and safety requirements of the fault. In this solution, the criteria are set to meet the automatic repair condition only when image data acquired by the inspection drone shows damage to the wind power generation equipment, and this damage can be repaired using the spraying device carried by the drone, and the repair process does not threaten the safe operation of the wind turbine or the normal operation of the drone. In other words, the automatic repair program will only be initiated when the type, size, and location of the damage are within the repair capabilities of the drone's spraying technology and the process can be safely executed. Therefore, if the abnormal wind turbine inspection data is wind turbine temperature data or wind turbine mechanical status data, it can be directly determined that it does not meet the preset automatic wind turbine repair criteria. If it is wind turbine image data, further determination of whether the preset automatic wind turbine repair criteria are met is required based on the analysis results of the wind turbine image data.

[0093] Abnormal indicators or thresholds for inspection data can be preset, and abnormal situations can be classified. The control terminal can analyze the inspection data according to the preset inspection data identification scheme. By comparing the analysis results with the preset abnormal indicators or thresholds, abnormal fans and cables can be identified and classified. Based on the preset automatic fan repair standards, it can be determined whether there are abnormal fans that meet the automatic repair conditions. Specifically, the degree of damage, location, type, and suitability for drone spraying repair can be assessed. For example, a preset abnormal indicator for judging abnormal fan temperature data could be that the temperature of the fan generator exceeds 85°C. If the analysis result after identification by the control terminal is that the temperature sensor data shows that the real-time temperature of a certain fan generator reaches 90°C, since the temperature exceeds the preset 85°C threshold, the fan temperature data is identified as abnormal fan inspection data. The pre-set automatic wind turbine repair criteria stipulate that automatic repair is only considered complete when images acquired by inspection drones show damage to the wind power equipment, and this damage can be repaired using a spraying device carried by the drone without threatening the safe operation of the wind turbine or the normal operation of the drone. In such cases, the wind turbine temperature data is deemed not to meet the pre-set automatic repair criteria. Since a wind farm contains multiple wind turbines, there may be multiple turbines malfunctioning. Each turbine has corresponding inspection data, leading to multiple instances of abnormal turbine inspection data and potentially multiple instances of abnormal turbines.

[0094] Based on the above technical solution, optionally, after determining whether there is abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards, the method further includes:

[0095] If there is no abnormal fan inspection data that meets the preset automatic fan repair standard, the control terminal sends a stop operation command to the abnormal fan equipment.

[0096] The control terminal acquires the equipment information of the abnormal fan equipment and sends the abnormal fan inspection data and the equipment information to the staff's handheld terminal, so that the staff can carry out on-site repair of the abnormal fan equipment based on the abnormal fan inspection data and the equipment information.

[0097] In this solution, the handheld terminal can be a portable data processing terminal, specifically, it can include devices such as mobile phones and tablets, which have data transmission and processing capabilities.

[0098] The control unit can transmit abnormal fan inspection data and equipment information to a handheld terminal via wireless communication technology. Upon receiving the data, the handheld terminal will display the abnormal fan inspection data and equipment information on its screen. Personnel can then use the abnormal fan inspection data and equipment information displayed on the handheld terminal to locate the abnormal fan and perform on-site repairs.

[0099] In this solution, if automatic repair is not possible, staff will be notified to perform manual repair, which improves the flexibility of the repair process.

[0100] Based on the above technical solution, optionally, it can be determined whether there is abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards, including:

[0101] Determine the data type of each abnormal wind turbine inspection data. If it is wind turbine image data, determine the degree of wind turbine damage, the area of ​​wind turbine damage, and the location of wind turbine damage based on the wind turbine image data.

[0102] Determine whether the degree of damage to the fan, the area of ​​damage to the fan, and the location of damage to the fan meet the preset automatic repair standards for the fan.

[0103] In this solution, the data types may include wind turbine image data, wind turbine temperature data, and wind turbine mechanical status data.

[0104] The degree of wind turbine damage can be used to describe the severity of the damage to the wind turbine. Specifically, it can be a level, such as minor, moderate, or severe.

[0105] The damaged area of ​​a wind turbine can be determined by identifying the number of pixels in the damaged area of ​​an image and converting it into the actual area.

[0106] The location of the wind turbine damage can be the specific location of the damaged area on the wind turbine. Specifically, it can be a coordinate and a corresponding description. The coordinate can be described using the wind turbine's own image coordinate system. For example, the coordinates of the damage location are (x1, y1), located on the third segment of the blade, near the left side of the blade tip.

[0107] Once all abnormal wind turbine inspection data is acquired, it's necessary to identify the data type of the anomaly, as this data includes wind turbine image data, temperature data, and mechanical status data. If it's wind turbine image data, image processing techniques such as edge detection, threshold segmentation, and deep learning are used to identify damaged areas in the image. Specifically, this includes distinguishing damaged parts from normal parts of the image. Based on the area, shape, and color characteristics of the damaged area, the severity of the damage is assessed, specifically by calculating the area ratio of the damaged area and the degree of color change. Then, image processing software or algorithms are used to measure the number of pixels in the damaged area and convert it into an actual area according to the image resolution and scale. Based on the coordinate system in the image, the specific location of the damaged area on the wind turbine is determined. Pre-defined automatic wind turbine repair standards can specify which damage levels, areas, and locations are suitable for automatic drone-based spray painting repair. The determined damage level, damaged area, and damaged location are compared and analyzed with preset standards. If all indicators meet or exceed the standards, the preset automatic repair standard for the wind turbine is considered to be met, meaning that the wind turbine is suitable for automatic spraying repair using a drone. This process is repeated to determine all wind turbine image data.

[0108] In this solution, by automatically determining whether the damage to the fan meets the automatic repair criteria, the fan that meets the preset automatic repair criteria can be identified, thereby eliminating the need for manual intervention in subsequent repairs, saving labor costs and improving repair efficiency.

[0109] S104, if there is abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standard, the control terminal will take the abnormal wind turbine inspection data as target abnormal data and determine the target abnormal wind turbine equipment corresponding to the target abnormal data; wherein, the number of target abnormal data is at least one, and the number of target abnormal wind turbine equipment is at least one.

[0110] The target abnormal data can be abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards, as determined by analysis at the control terminal. For example, if the abnormal wind turbine inspection data is wind turbine image data, and analysis reveals damage to a component of the wind turbine, and the type, size, and location of the damage are suitable for drone-based spray painting repair, then this wind turbine image data is the target abnormal data. If the abnormal wind turbine inspection data is wind turbine temperature data or wind turbine mechanical status data, it can be directly determined that it does not meet the preset automatic wind turbine repair standards.

[0111] The target abnormal wind turbine equipment can refer to the wind turbine equipment that has generated target abnormal data, that is, the wind turbine equipment that is identified by the control terminal and decided to be automatically repaired.

[0112] After the control terminal compares the abnormal wind turbine inspection data with the preset automatic wind turbine repair standards one by one, the abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards is selected and used as the target abnormal data for further processing. The wind turbine equipment associated with these target abnormal data is then obtained as the target abnormal wind turbine equipment. Specifically, when the drone collects the inspection data of each inspection equipment, the inspection data can be associated with the corresponding equipment information. In this way, after the control terminal identifies the abnormal wind turbine inspection data, it can directly determine the target abnormal wind turbine equipment from the associated equipment information.

[0113] S105, the control terminal obtains the equipment information of each target abnormal wind turbine, determines the wind turbine repair plan for each target abnormal wind turbine based on the equipment information and the target abnormal data of each target abnormal wind turbine, sends the wind turbine repair plan to the inspection drone, and sends a stop operation command to each target abnormal wind turbine.

[0114] A wind turbine repair plan is a detailed repair plan developed after an anomaly is detected in the wind turbine equipment. Specifically, it may include: the type of spraying material (i.e., the repair material used, including its specifications, performance, and applicable scope); the spraying location (precise location information of the damaged area of ​​the wind turbine to ensure the drone can accurately reach and spray); the spraying parameters (setting parameters such as spraying pressure, speed, and distance to ensure the repair material can evenly and correctly cover the damaged area); and the spraying sequence (if multiple damaged areas need repair, a reasonable spraying order can be determined).

[0115] A stop operation command can be used to notify each target malfunctioning wind turbine to temporarily shut down in order to carry out necessary repair work.

[0116] Once the target malfunctioning wind turbine is identified, equipment information for each target malfunctioning wind turbine can be retrieved from the database. Based on the target malfunction data, appropriate repair materials can be selected, such as high-temperature resistant, high-strength composite materials or anti-corrosion coatings. The spraying location can be determined, and spraying parameters, such as pressure, speed, and distance, can be set, as well as the spraying sequence can be planned. Then, the equipment information, repair materials, spraying location, spraying parameters, and spraying sequence can be combined into a wind turbine repair plan. The wind turbine repair plan can be sent to the inspection drone via wireless communication technology, and a stop operation command can be sent to each target malfunctioning wind turbine.

[0117] S106, the inspection drone repairs the abnormal wind turbine equipment of each target according to the wind turbine repair plan and the wind turbine spraying device.

[0118] A wind turbine spraying device can be a system used by drones for spraying wind turbines. Specifically, it can include a spraying system responsible for uniformly spraying paint onto the wind turbine surface, employing high-pressure airless spraying technology to ensure even coverage of the wind turbine blades or other components. A paint storage and delivery system is responsible for storing and delivering paint to the spraying system. Specifically, it can include one or more paint tanks, pumps, pipes, and valves to ensure a continuous supply of paint as needed. A control system is responsible for coordinating and controlling the entire spraying process. Specifically, it can include one or more sensors, a computer processor, a display screen, and a user interface to precisely control spraying parameters such as spraying speed, spray volume, and spraying angle. A drone mounting system is responsible for safely and stably mounting the spraying device onto the drone. Specifically, it can include brackets, clamps, and shock absorbers to ensure the spraying device remains stable and operates normally during drone flight. A safety protection system is responsible for monitoring and preventing potential hazards during the spraying process. For example, when the paint in the paint can runs out or the spraying system malfunctions, the safety protection system may automatically stop spraying and issue an alarm.

[0119] The inspection drone can obtain the location information of the target abnormal wind turbine equipment according to the wind turbine repair plan, fly to the location of the target abnormal wind turbine equipment, and call the wind turbine spraying device to carry out precise spraying of each target abnormal wind turbine equipment according to the wind turbine repair plan. During the spraying process, the spraying effect can be monitored in real time through the onboard camera until the damaged area is repaired. After the repair of one target abnormal wind turbine equipment is completed, the repair of all target abnormal wind turbine equipment is completed in the same way.

[0120] In this embodiment, the control terminal acquires equipment information, environmental information, and inspection drone information for each inspection device in the wind power plant. Based on this information, the control terminal determines a wind power plant inspection plan and sends it to the inspection drone. The inspection devices consist of wind turbines and cables. The inspection drone inspects each device according to the wind power plant inspection plan, obtaining inspection data for each device, and sends this data to the control terminal. The inspection data consists of wind turbine inspection data and cable inspection data. The wind turbine inspection data includes wind turbine image data, wind turbine temperature data, and wind turbine mechanical status data. The cable inspection data includes cable image data, cable temperature data, and cable electrical data. The control terminal identifies the inspection data of each device according to a preset inspection data identification scheme. If abnormal wind turbine inspection data is identified, the abnormal wind turbine inspection data is processed. The system identifies abnormal wind turbine equipment and determines whether there is abnormal wind turbine inspection data that meets preset automatic wind turbine repair standards. The number of abnormal wind turbine inspection data and the number of abnormal wind turbine equipment are both at least one. If abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards exists, the control terminal uses this abnormal wind turbine inspection data as target abnormal data and identifies the target abnormal wind turbine equipment corresponding to the target abnormal data. The number of target abnormal data and the number of target abnormal wind turbine equipment are both at least one. The control terminal acquires equipment information for each target abnormal wind turbine equipment, determines a wind turbine repair plan for each target abnormal wind turbine equipment based on the equipment information and the target abnormal data for each target abnormal wind turbine equipment, sends the wind turbine repair plan to the inspection drone, and sends a stop-operation command to each target abnormal wind turbine equipment. The inspection drone repairs each target abnormal wind turbine equipment according to the wind turbine repair plan and the wind turbine spraying device. The aforementioned intelligent inspection method for wind farms based on drones enables automated inspections of wind farms, allowing for rapid and comprehensive checks, shortening inspection time, improving efficiency, and reducing labor costs. Automatic repair of wind turbines when repair standards are met improves repair efficiency; eliminating the need for manual repair reduces labor costs and enhances repair safety.

[0121] Example 2

[0122] Figure 2 This is a flowchart illustrating the intelligent inspection method for wind farms based on unmanned aerial vehicles (UAVs) provided in Embodiment 2 of this application. Figure 2 As shown, the specific method includes the following steps:

[0123] S201, the control terminal acquires environmental information of the wind power plant. If the environmental information meets the preset acquisition standard, the equipment location information and parameter information of each inspection device are determined according to the equipment information. The inspection device consists of wind turbine equipment and cables.

[0124] Preset data collection criteria refer to a series of pre-defined conditions or standards that the environmental information of a wind farm needs to meet. These conditions can be set based on the safety and effectiveness of drone inspections. For example, environmental information may include meteorological data such as wind speed, wind direction, temperature, humidity, visibility, and extreme weather, as well as geographical information such as terrain and obstacle distribution. Preset data collection criteria may require wind speed within a certain range, good visibility, no serious obstacles, and no extreme weather to ensure that drones can conduct inspections safely.

[0125] Equipment location information refers to the specific location of each inspection device in the wind farm, determined by the control terminal according to preset data collection standards.

[0126] The parameter information can be specific data related to the operating performance and status of each inspection device, including wind power equipment parameter information and cable parameter information. Specifically, wind power equipment parameter information can include dimensional information, such as the height and diameter of the wind turbine tower, the length and diameter of the wind turbine blades, the dimensions of the nacelle and hub, the rotor diameter, rated wind speed, rated power, cut-in wind speed, cut-out wind speed, limiting wind speed, and rotational speed. Cable parameter information can include cable cross-sectional area, length, number of conductors, rated voltage, and rated current.

[0127] The control unit can determine whether the current environment allows the drone to perform automatic inspection based on environmental information, and whether the preset data collection standards are met. If the preset data collection standards are met, the control unit will query the database to determine the device location information and parameter information.

[0128] S202, determine the inspection route of the inspection drone in the wind power plant based on the equipment location information, and determine the inspection data collection route of the inspection drone in front of each inspection device based on the parameter information, the environmental information and the inspection drone information.

[0129] The inspection route can be the path that a drone needs to fly when inspecting the entire wind farm, and this route can cover all the wind power equipment and cables that need to be inspected.

[0130] Inspection data acquisition routes refer to the precise flight paths planned by the UAV for each wind turbine and cable based on pre-set parameters, environmental information, and the UAV's own performance parameters. For wind turbine equipment, the inspection data acquisition route can include hovering positions, where the UAV selects one or more hovering locations near the wind turbine equipment to collect detailed inspection data. Image acquisition routes involve the UAV acquiring images of various parts of the wind turbine equipment in a specific order and angle while hovering, including the front, back, root, and tip of the blades, the surface of the tower, and flange connections. Temperature data acquisition points involve the UAV approaching specific locations on the wind turbine equipment, such as the nacelle's heat vents, generators, and gearboxes, to collect temperature data using infrared thermal imagers or other temperature measurement equipment. Mechanical condition data acquisition points involve the UAV approaching the corresponding locations on the wind turbine equipment to collect mechanical condition data using appropriate sensors. For cables, inspection data collection routes can include image acquisition routes, where the drone flies along the cable path, hovers and takes pictures at key locations, and collects images of important parts such as cable connection points, corners, and crossing points. Temperature data acquisition points are where the drone, carrying an infrared thermal imager or other temperature measurement equipment, collects temperature data from the cable. Electrical data acquisition points are where the drone uses specialized sensors to collect electrical data from the cable.

[0131] The control unit can acquire precise location information of all wind power equipment and cables in the wind farm, plan a flight path to ensure the drone can cover all equipment and cables, and reduce unnecessary turns and flight distances. Along the flight path, the control unit can set inspection points, i.e., the precise locations of wind turbine equipment or cables. Then, the parameter information is analyzed to understand the characteristics of each inspected device, such as the blade size of the wind turbine and the laying path of the cable, to determine the appropriate data collection distance and angle. Environmental information is assessed, including current wind speed and direction, predicting potential impacts on the drone during flight, such as flight stability and drift, to determine the hovering position, shooting angle, and flight speed. Performance parameters are determined through the drone's inspection data, i.e., understanding the drone's performance parameters, such as flight speed and hovering stability. For wind turbine equipment, a preliminary flight path can be planned based on the location of the turbine and the surrounding environment to cover all key areas requiring inspection. Considering environmental factors such as wind speed and direction, the direction and altitude of the flight path are adjusted to ensure the drone remains stable during flight and avoids the impact of strong winds. Simultaneously considering the size and structure of the wind turbine equipment, which is typically located at a high position surrounded by towers, blades, and other structures, the flight path must avoid these obstacles to ensure the drone can safely approach and hover over critical parts of the wind turbine. The size and structure of the wind turbine equipment will affect the drone's approach and hovering methods. The flight path must also consider the equipment's size and structure to ensure the drone can find a suitable hovering position above the equipment. The flight speed should be adjusted appropriately based on the drone's speed performance to ensure accurate arrival at each inspection point and stable hovering when necessary. Finally, all collected information is synthesized, and a final flight route is determined using professional drone flight simulation software. For cables, the range of cable lines to be inspected and the key points to be checked, such as cable joints and bends, can be clearly defined. Based on the cable line path and the location of key points, an inspection path covering all key points to be inspected is planned, and data collection points are set at appropriate locations above or near each key point on the cable line.

[0132] Based on the above technical solution, optionally, the inspection data collection route of the inspection drone in front of each inspection device is determined according to the parameter information, the environmental information, and the inspection drone information, including:

[0133] The type of the inspection equipment is determined based on the parameter information. If it is a wind turbine, the blade type, tower size, temperature monitoring point, and mechanical condition monitoring point of the wind turbine are determined based on the parameter information.

[0134] The blade rotation trajectory of the wind turbine is determined based on the blade type, the wind speed and wind direction are determined based on the environmental information, and the speed information of the inspection drone is determined based on the inspection drone information.

[0135] The inspection drone determines the wind turbine image acquisition route in front of the wind turbine equipment based on the blade rotation trajectory, wind speed information, wind direction information, tower size, and speed information; wherein, the wind turbine image acquisition route includes the blade opening posture;

[0136] The inspection drone determines the data collection route for wind turbine status in front of the wind turbine equipment based on the temperature monitoring point, the mechanical status monitoring point, the wind speed information, the wind direction information, and the speed information.

[0137] The inspection drone determines the wind turbine data acquisition route in front of the wind turbine equipment based on the wind turbine image acquisition route and the wind turbine status data acquisition route.

[0138] In this scheme, the blade type of the wind turbine equipment can include the shape and size of the blades to assess the spatial and dynamic requirements when the drone flies through.

[0139] Tower dimensions can include the tower's diameter and height.

[0140] Temperature monitoring points can identify key temperature monitoring locations on wind turbine equipment, enabling drones to accurately collect temperature data during flight.

[0141] Mechanical condition monitoring points can be specific locations on the wind turbine equipment used to monitor the mechanical condition.

[0142] The blade rotation trajectory refers to the path or trajectory formed by the wind turbine blades during rotation. Different types of wind turbines can have different blade rotation trajectories. Specifically, it can include the trajectory shape, which is the main parameter describing the path or shape of the blade during rotation. Because the blades undergo complex motion under the influence of wind, their trajectories may exhibit various forms such as arcs, ellipses, and spirals. Rotation angle and speed refer to the angle and speed at which the blade rotates around its axis. The rotation angle determines the arc length traversed by the blade from its initial position to its final position, while the rotation speed reflects how fast the blade rotates per unit time. Horizontal and vertical motion also occur; the blades can also produce certain displacements in the horizontal and vertical directions.

[0143] Wind speed information can be the speed of the wind, specifically described in meters per second or kilometers per hour.

[0144] Wind direction information can be the direction of the wind, or more specifically, it can be expressed in degrees, such as north wind being 0 degrees and east wind being 90 degrees.

[0145] The speed information of an inspection drone refers to its flight speed during inspection missions, specifically described in meters per second (m / s) or kilometers per hour (km / h). This can include: ground speed (the horizontal component of the drone's absolute velocity relative to the ground); airspeed (the speed of the drone relative to the surrounding air); indicated airspeed (the speed displayed on the drone's airspeed gauge, corrected for airspeed data from atmospheric data to account for atmospheric density variations); vertical speed (the vertical component of the drone's velocity relative to the ground, i.e., its vertical climb and fall); and angular rate information, describing the rate of rotation of the drone around its axis, which helps in understanding its dynamic performance and attitude control.

[0146] The blade's initial shooting posture refers to the specific position and orientation of the blade relative to the drone and camera when the drone begins collecting image data from the wind turbine blades. Once the drone detects that the blade is in this specific posture, it will begin capturing image data.

[0147] A wind turbine image acquisition route can be a complete path or plan for a drone to acquire images in front of the wind turbine equipment. Specifically, it can include multiple steps such as how the drone approaches the wind turbine, how to avoid the blades to avoid collision, how to photograph the blades, and how to photograph the tower.

[0148] The wind turbine status data acquisition route can refer to the path taken by a drone flying in front of the wind turbine equipment to collect data such as temperature and mechanical status.

[0149] The control terminal can receive parameter information about the inspected equipment. By analyzing these parameters, the control terminal can determine the type of equipment, such as whether it is a wind turbine or a cable system. If the inspected equipment is a wind turbine, the control terminal can further determine the specific parameters of the wind turbine based on the parameter information, such as blade type, tower size, location and number of temperature monitoring points, and location and type of mechanical condition monitoring points. Based on the blade type of the wind turbine, the control terminal can query the corresponding blade rotation trajectory in the database. This is because after the wind turbine is manufactured, the manufacturer can provide performance data about the wind turbine, including the blade rotation trajectory, which can also be found. A simple database query based on the blade type is sufficient to determine the blade rotation trajectory.

[0150] When constructing a wind turbine image acquisition route, it is necessary to consider the acquisition routes for both the blades and the tower. When determining the blade acquisition route, a preliminary flight path can be planned based on the layout and number of wind turbine blades to ensure that the drone can cover all blades requiring acquisition. Then, based on the collected blade rotation trajectory data, the period, frequency, and phase of blade rotation are analyzed. The time required for a blade to rotate from one position to another is calculated, and the safe interval between blades, i.e., the time period without obstruction between blades, is determined. Based on the drone's current speed and acceleration, the distance the drone travels within the blade rotation period is predicted. The impact of wind speed and direction on the drone's flight trajectory and stability is analyzed, predicting the drone's offset caused by wind speed and direction, and adjusting the drone's speed and direction accordingly. Combining the blade rotation trajectory, drone speed information, and wind speed and direction information, the optimal time period for the drone to safely traverse between blades, i.e., the safety window, is calculated. The determination of the safety window should consider various uncertainties and risks that the drone may encounter during flight, ensuring that the drone has sufficient time to pass through the gaps between blades. Based on the calculated blade rotation trajectory and safety window, the time periods matching the blade's image acquisition posture can be identified; that is, within which safety windows will the blade be in the required image acquisition posture? Specific stop points or flight points can be set in the initial flight path, corresponding to the time points of the blade's image acquisition posture. Ensure the drone can stably approach and capture images of the blade within these time points. Finally, the safety window and blade image acquisition posture are integrated into the flight path. During the safe intervals of blade rotation, the drone should be able to safely approach and acquire images of the blade. Multiple stop points or flight points can be set in the path planning to allow the drone to acquire images at appropriate times, ultimately combining them into a blade acquisition route. For the tower acquisition route, the height, diameter, and other relevant dimensional information of the wind turbine tower can be obtained. Based on the tower's height and diameter, the minimum flight altitude for the drone to acquire tower images is determined. Ensure the drone's flight path maintains a sufficient safe distance from the tower to avoid collisions. Plan shooting points at different angles to obtain all-round images of the tower, and finally form the image acquisition route of the tower. Combine the acquisition routes of the blades and the tower to form the image acquisition route of the wind turbine.

[0151] Parameter information can be obtained from the wind turbine management system to determine the location of key temperature monitoring points on the wind turbine, such as generators, gearboxes, and bearings. Monitoring points for key mechanical components on the wind turbine, such as blades, bearings, and drive shafts, can also be identified. Real-time or predicted wind speed and direction information can be acquired, and their impact on the UAV's flight stability, path selection, and data acquisition can be analyzed. The maximum speed, acceleration, and maneuverability of the UAV can be determined based on speed information, considering its flight performance and speed adjustment capabilities under different wind speeds and directions. A preliminary flight path can be planned based on the layout of the wind turbine equipment and the location of the monitoring points, ensuring that the flight path covers all key temperature and mechanical status monitoring points. Multiple stop points or flight points can be set along the flight path, corresponding to the monitoring points where data needs to be collected. The location and number of stop points can be adjusted based on wind speed and direction information to ensure that the UAV can stably collect data upon reaching these points. Considering the UAV's speed information, sufficient time should be allocated for data collection at stop points, and the UAV should be able to move quickly between monitoring points. Based on the above information, the wind turbine status data collection route for the inspection UAV in front of the wind turbine equipment can be determined. Finally, the wind turbine image acquisition route and the wind turbine status data acquisition route are combined to obtain the wind turbine data acquisition route of the inspection drone in front of the wind turbine equipment.

[0152] This solution comprehensively considers various types of information to determine the wind turbine image acquisition route and wind turbine status data acquisition route for the inspection drone, which can improve the efficiency and effectiveness of the inspection, ensure the accuracy and reliability of the data, and enhance flight safety.

[0153] Based on the above technical solution, optionally, after determining the type information of the inspection equipment according to the parameter information, the method further includes:

[0154] If it is a cable, then the length information of the cable, the location information of the accessory equipment, the temperature monitoring point and the electrical data monitoring point are determined according to the parameter information; the wind speed information and the wind direction information are determined according to the environmental information; and the speed information of the inspection drone is determined according to the inspection drone information.

[0155] The inspection drone determines the cable image acquisition route in front of the cable based on the length information, the location information of the accessory equipment, the wind speed information, the wind direction information, and the speed information.

[0156] The inspection drone determines the cable status data collection route in front of the cable based on the temperature monitoring point, the electrical data monitoring point, the wind speed information, the wind direction information, and the speed information.

[0157] The cable data acquisition route of the inspection drone in front of the cable is determined based on the cable image acquisition route and the cable status data acquisition route.

[0158] In this scheme, the length information can be the total length of the cable.

[0159] The location information of accessory equipment can be the specific location of various accessory equipment installed on the cable, such as joints, branch points, and terminals.

[0160] Temperature monitoring points can be points installed in the cable to monitor changes in cable temperature in real time.

[0161] Electrical data monitoring points can be points set up in a cable system to monitor electrical parameters.

[0162] A cable image acquisition route can refer to the path planned by an inspection drone when it flies over a cable in order to acquire images of the cable and its accessory equipment.

[0163] The cable status data acquisition route can refer to the path planned by the inspection drone when it flies over the cable in order to collect status information such as the cable's temperature and electrical data.

[0164] The cable data acquisition route can be a complete inspection route that combines the cable image acquisition route and the cable status data acquisition route.

[0165] Cable parameter information can be obtained from the cable management system. Based on this information, the total cable length and the location information of all key accessories on the cable, such as joints, branch points, and terminals, can be determined. Temperature monitoring points for drone-based cable temperature data collection can be obtained from the parameter information; these points can be set at critical locations on the cable, such as joints and bends. Electrical data monitoring points for drone-based cable electrical data collection can also be obtained from the parameter information. Wind speed and direction information can be extracted from environmental data, and speed information can be extracted from inspection drone data. Based on the total cable length, the approximate flight distance of the drone is planned, forming a preliminary cable image acquisition route. The locations of all accessories are marked on the cable image acquisition route to ensure that the drone can capture these key areas. The cable image acquisition route is adjusted based on real-time wind speed, wind direction, and drone speed information to ensure the drone remains stable during flight.

[0166] The locations of all temperature and electrical data monitoring points can be marked, ensuring that the drone can accurately collect data from these points and form a preliminary cable status data acquisition route. Considering the impact of wind speed, direction, and velocity information on data acquisition, the cable status data acquisition route is adjusted to ensure the drone remains stable during data collection. Finally, the cable image acquisition route and the cable status data acquisition route are combined to form a complete cable data acquisition route.

[0167] S203, determine the wind farm inspection plan based on the inspection route and the inspection data collection route, and send the wind farm inspection plan to the inspection drone.

[0168] The inspection route and the data collection route of each device can be combined to form the final wind farm inspection plan. This plan includes the overall inspection route that the drone needs to inspect the wind farm equipment, as well as the route it travels to collect data in front of each device.

[0169] S204, the inspection drone inspects each inspection device according to the wind power plant inspection plan, obtains the inspection data of each inspection device in the wind power plant, and sends the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data and cable electrical data.

[0170] S205, the control terminal identifies the inspection data of each inspection device according to the preset inspection data identification scheme. If abnormal fan inspection data is identified, the abnormal fan device is determined according to the abnormal fan inspection data, and it is determined whether there is abnormal fan inspection data that meets the preset automatic fan repair standard; wherein, the number of abnormal fan inspection data is at least one, and the number of abnormal fan devices is at least one.

[0171] S206, if there is abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standard, the control terminal will take the abnormal wind turbine inspection data as target abnormal data and determine the target abnormal wind turbine equipment corresponding to the target abnormal data; wherein, the number of target abnormal data is at least one, and the number of target abnormal wind turbine equipment is at least one.

[0172] S207, the control terminal obtains the equipment information of each target abnormal wind turbine, determines the wind turbine repair plan for each target abnormal wind turbine based on the equipment information and the target abnormal data of each target abnormal wind turbine, sends the wind turbine repair plan to the inspection drone, and sends a stop operation command to each target abnormal wind turbine.

[0173] S208, the inspection drone repairs the abnormal wind turbine equipment of each target according to the wind turbine repair plan and the wind turbine spraying device.

[0174] In this embodiment, by determining the inspection route, the drone can quickly inspect the entire wind farm, saving labor costs and improving inspection efficiency. Through precisely planned data collection routes, the drone can ensure accurate coverage of every key inspection point, avoiding unnecessary flights and repeated checks, thus improving the accuracy and efficiency of the inspection.

[0175] Example 3

[0176] Figure 3 This is a flowchart illustrating the intelligent inspection method for wind farms based on unmanned aerial vehicles (UAVs) provided in Embodiment 3 of this application. Figure 3 As shown, the specific method includes the following steps:

[0177] S301, the control terminal acquires equipment information, environmental information, and inspection drone information of each inspection device in the wind power plant, determines the wind power plant inspection plan based on the equipment information, environmental information, and inspection drone information, and sends the wind power plant inspection plan to the inspection drone; wherein, the inspection device consists of wind turbine equipment and cables.

[0178] S302, the inspection drone inspects each inspection device according to the wind power plant inspection plan, obtains the inspection data of each inspection device in the wind power plant, and sends the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data and cable electrical data.

[0179] S303, the control terminal identifies the inspection data of each inspection device according to the preset inspection data identification scheme. If abnormal cable inspection data is identified, the abnormal cable is determined based on the abnormal cable inspection data, and it is determined whether there is abnormal cable inspection data that meets the preset cable automatic repair standard; wherein, the number of abnormal cable inspection data is at least one, and the number of abnormal cables is at least one.

[0180] Abnormal cable inspection data can be data collected during cable inspection that does not conform to the normal cable operating condition or exceeds the preset threshold.

[0181] Abnormal cables can refer to cables that, based on abnormal cable inspection data, have potential faults or have already experienced faults.

[0182] The preset automatic cable repair standards refer to a series of conditions and requirements that enable drones to automatically perform repair operations for specific types of cable faults. Specifically, this may include fault type identification, such as insulation damage and loose bolts, as well as the severity level of the fault. That is, for different types of faults, a severity level that can be automatically repaired is set, specifically including the degree of insulation damage and whether the drone can tighten loose fasteners. The preset automatic cable repair standards need to consider the drone's operational capabilities and limitations, as well as the safety and effectiveness of the repair operations. For example, for cables with damaged insulation, can the drone spray repair materials to restore insulation performance? For loose bolts, can the drone use a robotic arm or tools to tighten the bolts? If the abnormal cable inspection data is cable temperature data or cable electrical data, it can be directly determined that it does not meet the preset automatic cable repair standards. If it is cable image data, further determination of whether the preset automatic cable repair standards are met is required based on the analysis results of the cable image data.

[0183] The control unit can input the collected inspection data into the analysis system, compare it with the baseline data of normal cables, identify abnormal cable inspection data, and determine relevant information about the abnormal cables from the abnormal cable inspection data, such as location information and serial number information, thereby identifying the abnormal cables. Based on preset automatic cable repair standards, it determines whether there are abnormal cables that meet the automatic repair conditions; specifically, it can assess the degree of damage, location, type, and suitability for UAV spray painting repair and firmware repair.

[0184] Based on the above technical solution, optionally, after determining whether there is abnormal cable inspection data that meets the preset automatic cable repair standards, the method further includes:

[0185] If no abnormal cable inspection data that meets the preset automatic cable repair standards is found, the control terminal acquires the equipment information of the abnormal cable and sends the abnormal cable inspection data and the equipment information to the staff's handheld terminal, so that the staff can repair the abnormal cable on-site based on the abnormal cable inspection data and the equipment information.

[0186] In this solution, the control unit can transmit abnormal cable inspection data and equipment information to a handheld terminal via wireless communication technology. Upon receiving the data, the handheld terminal displays the abnormal cable inspection data and equipment information on its screen. Workers can then use the information displayed on the handheld terminal to locate the abnormal cable and perform on-site repairs.

[0187] In this solution, if automatic repair is not possible, staff will be notified to perform manual repair, which improves the flexibility of the repair process.

[0188] Based on the above technical solution, optionally, it can be determined whether there is abnormal cable inspection data that meets the preset automatic cable repair standards, including:

[0189] Determine the data type of the abnormal cable inspection data. If it is cable image data, determine the cable repair type based on the cable image data.

[0190] If the damage is cable, the degree of cable damage, the area of ​​cable damage, and the location of cable damage are determined based on the cable image data. It is then determined whether the degree of cable damage, the area of ​​cable damage, and the location of cable damage meet the preset automatic cable repair standards.

[0191] If the loose cable accessory is identified, the type of loose accessory is determined based on the cable image data, and it is then determined whether the type of loose accessory meets the preset automatic cable repair standard.

[0192] In this plan, cable repair types can include cable damage and loose cable accessories. Cable damage can be defined as a broken cable, while loose cable accessories can be defined as loose cable connections, fixations, and protective devices.

[0193] The degree of cable damage can be measured by the severity of the damage, specifically by indicators such as the depth and extent of the damage.

[0194] The damaged area of ​​a cable can be the size of the area occupied by the cable breakage.

[0195] The location of cable damage can be the specific location where the cable damage occurred.

[0196] The type of loose cable accessory can refer to the specific type of cable accessory that has become loose. Specifically, this can include cable connectors (devices used to connect two sections of cable), cable clamps (devices used to secure the cable in place), and cable sheaths (devices used to protect the cable from external environmental corrosion).

[0197] The collected data can be analyzed. If the data type is cable image data, image processing software can be used to analyze the images. The type of cable damage can be identified. If it is cable damage, image processing algorithms can be used to analyze the cable image and identify the damaged area. The degree of damage is assessed based on characteristics such as the depth, width, or color changes of the damaged area. Specifically, this can be achieved using specialized image processing software or deep learning models, and the assessed degree of damage is quantified, for example, using numerical values ​​or grades. Then, using the measurement tools in the image processing software, the damaged area is marked on the cable image. By calculating the number of pixels or using the scale in the image, the pixel values ​​of the marked area are converted into the actual damaged area. The specific location of the damage is accurately marked on the cable image. Specifically, geographical location information or a structural diagram of the cable system can be used to further determine the damage location. The assessed degree of damage, damaged area, and damaged location are compared with preset automatic repair standards. If all these parameters meet the preset standards, it is determined that the automatic repair conditions are met. If the loose cable accessory is a problem, image processing algorithms can be used to analyze the cable image, identify the specific type of loose accessory, and match it against preset automatic cable repair standards to determine if the drone can automatically tighten it. If the accessory can be automatically tightened, repair marker lines in the image can be identified. These marker lines can be physical marks or reference points used to guide the drone in re-tightening the loose accessory to the correct position. Then, based on the image data and the repair marker lines, the degree of looseness is assessed, and the drone is instructed on how to tighten the accessory to the marker lines.

[0198] In this solution, by determining the data type of abnormal cable inspection data and adopting corresponding processing strategies based on different data types, the efficiency of cable maintenance and repair work can be improved.

[0199] S304, if there is abnormal cable inspection data that meets the preset cable automatic repair standard, the control terminal will take the abnormal cable inspection data as target abnormal data and determine the target abnormal cable corresponding to the target abnormal data; wherein, the number of target abnormal data is at least one, and the number of target abnormal cables is at least one.

[0200] Target anomaly data can be abnormal cable inspection data that meets preset automatic cable repair standards, determined through analysis at the control end. For example, if the abnormal cable inspection data is cable image data, and analysis reveals damage to a component of the cable, and the type, size, and location of the damage are suitable for drone-based spraying repair, or if the drone can perform firmware repair, then this cable image data is the target anomaly data.

[0201] The target abnormal cable equipment can refer to the cable equipment that has generated target abnormal data, that is, the cable equipment that has been identified by the control end and is subject to automatic repair processing.

[0202] After the control terminal compares the abnormal cable inspection data with the preset automatic cable repair standards one by one, it filters out the abnormal cable inspection data that meets the preset automatic cable repair standards and uses it as the target abnormal data for further processing. It also obtains the cable equipment associated with these target abnormal data as the target abnormal cable equipment. Specifically, when the drone collects the inspection data of each inspection device, it can associate the inspection data with the corresponding equipment information. In this way, after the control terminal identifies the abnormal cable inspection data, it can directly determine the target abnormal cable equipment from the associated equipment information.

[0203] S305, the control terminal obtains the equipment information of the target abnormal cable, determines the cable repair plan based on the equipment information and the target abnormal data, and sends the cable repair plan to the inspection drone.

[0204] A cable repair plan is a set of repair measures and steps determined after assessment of a cable fault or damage. Specifically, it may include: the type of spray material (the repair material used, including its specifications, performance, and applicable scope); the spraying location (precise location information of the damaged area on the wind turbine to ensure the drone can accurately reach and spray); spraying parameters (setting parameters such as spraying pressure, speed, and distance to ensure the repair material covers the damaged area evenly and correctly); the spraying sequence (if multiple damaged areas need repair, a reasonable spraying order can be established); and how to use tools to tighten loose fasteners.

[0205] Once the target abnormal cable is identified, equipment information for each target abnormal cable can be retrieved from the database. Based on the received equipment information and target abnormality data, a preliminary analysis and diagnosis of the cable fault can be performed to determine the necessary repair operations and corresponding steps. If spraying is required, a spraying material with good insulation and weather resistance, compatible with the original cable material, can be selected based on the cable's material and working environment. Then, the spraying location is determined, spraying parameters such as pressure, speed, and distance are set, and the spraying sequence is planned. The equipment information, repair material, spraying location, spraying parameters, and spraying sequence are then combined into a cable repair plan. If fastener tightening is required, appropriate tightening tools, such as wrenches, screwdrivers, or electric tighteners, can be selected based on the specific conditions of the cable connection. Detailed tightening steps are formulated, specifically including identifying the location of the fasteners to be tightened, using appropriate tools for tightening, and ensuring moderate tightening force. The above information is then combined into a cable repair plan, which is transmitted to the inspection drone via wireless communication technology.

[0206] S306, the inspection drone repairs the target abnormal cable according to the cable repair plan and the cable spraying device and / or cable accessory equipment repair device.

[0207] Cable spraying equipment can be a drone-mounted device specifically designed for spraying and repairing the external insulation or protective layers of cables. Specifically, it may include a spray gun, a spray liquid container for storing spraying materials such as insulating varnish and anti-corrosion coatings, and a control system for controlling parameters such as spraying speed and amount. The cable spraying equipment can evenly spray the coating liquid onto damaged or protected areas of the cable, thereby restoring the cable's insulation performance or protective capabilities.

[0208] Cable accessory repair devices can be drone-borne tools used to repair accessories such as cable connections, fixations, and protection. Specifically, they can include cable connectors, cable clamps, and cable fasteners. When these accessories become loose, damaged, or aged, the appropriate repair devices are used to tighten them, ensuring the stability and safety of the cable system.

[0209] The inspection drone can locate the fault position of the target abnormal cable according to the instructions in the repair plan. If spraying repair is required, the inspection drone can move the spraying device to a suitable position and adjust the spraying parameters through the control system to evenly and quickly spray the spraying liquid onto the damaged or protected parts of the cable. If cable accessories need to be repaired, the inspection drone can use the corresponding repair device to tighten them. Specifically, this can include using tools such as screwdrivers and wrenches to tighten loose fasteners.

[0210] In this embodiment, the cable is automatically repaired when the repair criteria are met, which improves repair efficiency, reduces labor costs by eliminating the need for manual repair, and improves repair safety.

[0211] Example 4

[0212] Figure 4 This is a schematic diagram of the structure of the intelligent inspection system for wind farms based on unmanned aerial vehicles (UAVs) provided in Embodiment 4 of this application, as shown below. Figure 4 As shown, it specifically includes the following:

[0213] The inspection plan determination module 401 is used to obtain equipment information, environmental information and inspection drone information of each inspection device in the wind power plant from the control terminal, determine the wind power plant inspection plan based on the equipment information, environmental information and inspection drone information, and send the wind power plant inspection plan to the inspection drone; wherein, the inspection device consists of wind turbine equipment and cables.

[0214] The inspection data acquisition module 402 is used for the inspection drone to inspect each inspection device according to the wind power plant inspection plan, obtain the inspection data of each inspection device in the wind power plant, and send the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data and cable electrical data;

[0215] The inspection data identification module 403 is used by the control terminal to identify the inspection data of each inspection device according to the preset inspection data identification scheme. If abnormal fan inspection data is identified, the abnormal fan device is determined according to the abnormal fan inspection data, and it is determined whether there is abnormal fan inspection data that meets the preset automatic fan repair standard; wherein, the number of abnormal fan inspection data is at least one, and the number of abnormal fan devices is at least one.

[0216] The abnormal fan data determination module 404 is used to determine the target abnormal fan equipment corresponding to the abnormal fan inspection data if there is abnormal fan inspection data that meets the preset automatic fan repair standard; wherein, the number of target abnormal data is at least one, and the number of target abnormal fan equipment is at least one.

[0217] The wind turbine repair scheme determination module 405 is used to obtain the equipment information of each target abnormal wind turbine equipment from the control terminal, determine the wind turbine repair scheme of each target abnormal wind turbine equipment based on the equipment information and the target abnormal data of each target abnormal wind turbine equipment, send the wind turbine repair scheme to the inspection drone, and send a stop operation command to each target abnormal wind turbine equipment.

[0218] The wind turbine repair module 406 is used by the inspection drone to repair the abnormal wind turbine equipment of each target according to the wind turbine repair plan and the wind turbine spraying device.

[0219] In this embodiment, the inspection plan determination module is used by the control terminal to acquire equipment information, environmental information, and inspection drone information of each inspection device in the wind power plant, determine the wind power plant inspection plan based on the equipment information, environmental information, and inspection drone information, and send the wind power plant inspection plan to the inspection drone; wherein, the inspection device consists of wind turbine equipment and cables; the inspection data acquisition module is used by the inspection drone to inspect each inspection device according to the wind power plant inspection plan, obtain the inspection data of each inspection device in the wind power plant, and send the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data, and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data, and cable electrical data; the inspection data identification module is used by the control terminal to identify the inspection data of each inspection device according to a preset inspection data identification scheme, and if abnormal wind turbine inspection data is identified, the abnormal wind turbine inspection data is used to identify the abnormal wind turbine inspection data. The system identifies abnormal wind turbine equipment and determines whether there is abnormal wind turbine inspection data that meets preset automatic wind turbine repair standards. The number of abnormal wind turbine inspection data is at least one, and the number of abnormal wind turbine equipment is at least one. An abnormal wind turbine data identification module is used to, if there is abnormal wind turbine inspection data that meets preset automatic wind turbine repair standards, use the abnormal wind turbine inspection data as target abnormal data and identify the target abnormal wind turbine equipment corresponding to the target abnormal data. The number of target abnormal data is at least one, and the number of target abnormal wind turbine equipment is at least one. A wind turbine repair plan identification module is used for the control terminal to acquire equipment information for each target abnormal wind turbine equipment, determine a wind turbine repair plan for each target abnormal wind turbine equipment based on the equipment information and the target abnormal data of each target abnormal wind turbine equipment, send the wind turbine repair plan to the inspection drone, and send a stop-operation command to each target abnormal wind turbine equipment. A wind turbine repair module is used for the inspection drone to repair each target abnormal wind turbine equipment according to the wind turbine repair plan and the wind turbine spraying device. The aforementioned intelligent inspection system for wind farms based on drones enables rapid and comprehensive inspections of wind farms, shortening inspection time, improving efficiency, and reducing labor costs. It automatically repairs wind turbines when repair standards are met, increasing repair efficiency; eliminating the need for manual repairs reduces labor costs and enhances repair safety.

[0220] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of this application.

[0221] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, and this is not limited herein.

Claims

1. A smart inspection method for wind power plants based on unmanned aerial vehicles (UAVs), characterized in that, The method includes: The control terminal acquires equipment information, environmental information, and inspection drone information for each inspection device in the wind farm. Based on the equipment information, environmental information, and inspection drone information, it determines the wind farm inspection plan and sends the wind farm inspection plan to the inspection drone. The inspection device consists of wind turbine equipment and cables. The inspection drone inspects each inspection device according to the wind power plant inspection plan, obtains inspection data for each inspection device in the wind power plant, and sends the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data, and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data, and cable electrical data; The control terminal identifies the inspection data of each inspection device according to the preset inspection data identification scheme. If abnormal fan inspection data is identified, the abnormal fan device is determined based on the abnormal fan inspection data, and it is also determined whether there is abnormal fan inspection data that meets the preset automatic fan repair standard; wherein, the number of abnormal fan inspection data is at least one, and the number of abnormal fan devices is at least one. If there is abnormal wind turbine inspection data that meets the preset automatic wind turbine repair standards, the control terminal will take the abnormal wind turbine inspection data as target abnormal data and determine the target abnormal wind turbine equipment corresponding to the target abnormal data; wherein, the number of target abnormal data is at least one, and the number of target abnormal wind turbine equipment is at least one. The control terminal acquires the equipment information of each target abnormal wind turbine, determines the wind turbine repair plan for each target abnormal wind turbine based on the equipment information and the target abnormal data of each target abnormal wind turbine, sends the wind turbine repair plan to the inspection drone, and sends a stop operation command to each target abnormal wind turbine. The inspection drone repaired the abnormal wind turbine equipment of each target according to the aforementioned wind turbine repair plan and wind turbine spraying device; After determining whether there is abnormal wind turbine inspection data that meets the preset automatic wind turbine repair criteria, the method further includes: If there is no abnormal fan inspection data that meets the preset automatic fan repair standard, the control terminal sends a stop operation command to the abnormal fan equipment. The control terminal acquires the equipment information of the abnormal fan equipment and sends the abnormal fan inspection data and the equipment information to the staff's handheld terminal, so that the staff can repair the abnormal fan equipment on-site based on the abnormal fan inspection data and equipment information; The control terminal acquires equipment information, environmental information, and inspection drone information for each inspection device at the wind farm. Based on this equipment information, environmental information, and inspection drone information, it determines a wind farm inspection plan, including: The control terminal acquires environmental information of the wind farm. If the environmental information meets the preset acquisition standard, the location information and parameter information of each inspection device are determined based on the equipment information. The inspection route of the inspection drone in the wind farm is determined based on the equipment location information, and the inspection data collection route of the inspection drone in front of each inspection device is determined based on the parameter information, the environmental information and the inspection drone information. A wind farm inspection plan is determined based on the inspection route and the inspection data collection route. Based on the parameter information, the environmental information, and the inspection drone information, the inspection data collection route of the inspection drone in front of each inspection device is determined, including: The type of the inspection equipment is determined based on the parameter information. If it is a wind turbine, the blade type, tower size, temperature monitoring point, and mechanical condition monitoring point of the wind turbine are determined based on the parameter information. The blade rotation trajectory of the wind turbine is determined based on the blade type, the wind speed and wind direction are determined based on the environmental information, and the speed information of the inspection drone is determined based on the inspection drone information. The inspection drone determines the wind turbine image acquisition route in front of the wind turbine equipment based on the blade rotation trajectory, wind speed information, wind direction information, tower size, and speed information; wherein, the wind turbine image acquisition route includes the blade opening posture; The inspection drone determines the data collection route for wind turbine status in front of the wind turbine equipment based on the temperature monitoring point, the mechanical status monitoring point, the wind speed information, the wind direction information, and the speed information. The inspection drone's wind turbine data acquisition route in front of the wind turbine equipment is determined based on the wind turbine image acquisition route and the wind turbine status data acquisition route. After determining the type information of the inspection equipment based on the parameter information, the method further includes: If it is a cable, then the length information of the cable, the location information of the accessory equipment, the temperature monitoring point and the electrical data monitoring point are determined according to the parameter information; the wind speed information and the wind direction information are determined according to the environmental information; and the speed information of the inspection drone is determined according to the inspection drone information. The inspection drone determines the cable image acquisition route in front of the cable based on the length information, the location information of the accessory equipment, the wind speed information, the wind direction information, and the speed information. The inspection drone determines the cable status data collection route in front of the cable based on the temperature monitoring point, the electrical data monitoring point, the wind speed information, the wind direction information, and the speed information. The cable data acquisition route of the inspection drone in front of the cable is determined based on the cable image acquisition route and the cable status data acquisition route.

2. The intelligent inspection method for wind power plants based on unmanned aerial vehicles (UAVs) according to claim 1, characterized in that, Determine if there is any abnormal wind turbine inspection data that meets the preset automatic wind turbine repair criteria, including: Determine the data type of each abnormal wind turbine inspection data. If it is wind turbine image data, determine the degree of wind turbine damage, the area of ​​wind turbine damage, and the location of wind turbine damage based on the wind turbine image data. Determine whether the degree of damage to the fan, the area of ​​damage to the fan, and the location of damage to the fan meet the preset automatic repair standards for the fan.

3. The intelligent inspection method for wind power plants based on unmanned aerial vehicles (UAVs) according to claim 1, characterized in that, After the control terminal identifies the inspection data of each inspection device according to the preset inspection data identification scheme, the method further includes: If abnormal cable inspection data is detected, the abnormal cable is identified based on the abnormal cable inspection data, and it is determined whether there is abnormal cable inspection data that meets the preset cable automatic repair standard; wherein, the number of abnormal cable inspection data is at least one, and the number of abnormal cables is at least one. If abnormal cable inspection data that meets the preset automatic cable repair standard exists, the control terminal will use the abnormal cable inspection data as target abnormal data and determine the target abnormal cable corresponding to the target abnormal data; wherein, the number of target abnormal data is at least one, and the number of target abnormal cables is at least one. The control terminal acquires the equipment information of the target abnormal cable, determines a cable repair plan based on the equipment information and the target abnormal data, and sends the cable repair plan to the inspection drone. The inspection drone repairs the target abnormal cable according to the cable repair plan and the cable spraying device and / or cable accessory equipment repair device.

4. The intelligent inspection method for wind power plants based on unmanned aerial vehicles (UAVs) according to claim 3, characterized in that, After determining whether there is abnormal cable inspection data that meets the preset automatic cable repair criteria, the method further includes: If no abnormal cable inspection data that meets the preset automatic cable repair standards is found, the control terminal acquires the equipment information of the abnormal cable and sends the abnormal cable inspection data and the equipment information to the staff's handheld terminal, so that the staff can repair the abnormal cable on-site based on the abnormal cable inspection data and the equipment information.

5. The intelligent inspection method for wind power plants based on unmanned aerial vehicles (UAVs) according to claim 3, characterized in that, Determine if there is any abnormal cable inspection data that meets the preset automatic cable repair criteria, including: Determine the data type of the abnormal cable inspection data. If it is cable image data, determine the cable repair type based on the cable image data. If the damage is cable, the degree of cable damage, the area of ​​cable damage, and the location of cable damage are determined based on the cable image data. It is then determined whether the degree of cable damage, the area of ​​cable damage, and the location of cable damage meet the preset automatic cable repair standards. If the loose cable accessory is identified, the type of loose accessory is determined based on the cable image data, and it is then determined whether the type of loose accessory meets the preset automatic cable repair standard.

6. An intelligent inspection system for wind power plants based on unmanned aerial vehicles (UAVs), characterized in that, The system for implementing the method according to any one of claims 1-5, the system comprising: The inspection plan determination module is used by the control terminal to acquire equipment information, environmental information, and inspection drone information of each inspection device in the wind power plant, determine the wind power plant inspection plan based on the equipment information, environmental information, and inspection drone information, and send the wind power plant inspection plan to the inspection drone; wherein, the inspection device consists of wind turbine equipment and cables; The inspection data acquisition module is used for the inspection drone to inspect each inspection device according to the wind power plant inspection plan, obtain the inspection data of each inspection device in the wind power plant, and send the inspection data to the control terminal; wherein, the inspection data consists of wind turbine inspection data and cable inspection data, the wind turbine inspection data consists of wind turbine image data, wind turbine temperature data and wind turbine mechanical status data, and the cable inspection data consists of cable image data, cable temperature data and cable electrical data; The inspection data identification module is used by the control terminal to identify the inspection data of each inspection device according to the preset inspection data identification scheme. If abnormal fan inspection data is identified, the abnormal fan device is determined based on the abnormal fan inspection data, and it is also determined whether there is abnormal fan inspection data that meets the preset automatic fan repair standard. The number of abnormal fan inspection data is at least one, and the number of abnormal fan devices is at least one. The abnormal fan data determination module is used to determine the target abnormal fan equipment corresponding to the abnormal fan inspection data if there is abnormal fan inspection data that meets the preset automatic fan repair standards; wherein, the number of target abnormal data is at least one, and the number of target abnormal fan equipment is at least one. The wind turbine repair plan determination module is used to obtain equipment information of each target abnormal wind turbine equipment from the control terminal, determine the wind turbine repair plan of each target abnormal wind turbine equipment based on the equipment information and the target abnormal data of each target abnormal wind turbine equipment, send the wind turbine repair plan to the inspection drone, and send a stop operation command to each target abnormal wind turbine equipment. The wind turbine repair module is used by the inspection drone to repair abnormal wind turbine equipment of each target according to the wind turbine repair plan and the wind turbine spraying device.

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