Method and device for unmanned aerial vehicle to detect and clean insulator dirt

Abstract

The invention discloses a method and device for detecting and cleaning insulator dirt by an unmanned aerial vehicle, and the device comprises an image collection equipment module, a signal transmission equipment module, a positioning equipment module, an energy management module, a detection module, a discrimination module, an alarm module, a cleaning equipment module, a cleaning control module, and an archiving report module. The image acquisition equipment module is connected with the signal transmission equipment module, the signal transmission equipment module is connected with the cleaning control module, the positioning equipment module is connected with the cleaning equipment module, and the cleaning equipment module is connected with the archiving report module. The method and the device for detecting and cleaning the insulator dirt by the unmanned aerial vehicle are used for rapidly and efficiently detecting the dirt degree of the surface of the insulator and cleaning the insulator, through image acquisition, image detection, cleaning operation and result feedback, the insulator maintenance efficiency is remarkably improved, the manpower inspection cost and the cleaning time consumption are reduced, and the method and the device are suitable for popularization and application. And meanwhile, the method has the advantages of real-time performance and high efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of power system maintenance, and particularly relates to a method and device for detecting and cleaning insulator contamination by using an unmanned aerial vehicle (UAV). Background Art

[0002] With the improvement of the voltage level of transmission lines, insulators play an increasingly important role in the power system. The contamination deposition on the surface of insulators may cause partial discharge or even flashover accidents, threatening the safe operation of the power system. With the continuous development of technology, people's requirements for the method of detecting and cleaning insulator contamination by using UAVs are also getting higher and higher.

[0003] The existing methods for detecting and cleaning insulator contamination by using UAVs have certain drawbacks when in use. The traditional detection and cleaning of insulator contamination mainly rely on manual inspection operations, which are not only inefficient but also have relatively high safety risks. In recent years, the application of UAV technology in power inspection has provided new ideas for intelligent operation and maintenance, but there are still deficiencies in the detection accuracy of insulator contamination and the cleaning operation, bringing certain adverse effects to the using process. Therefore, we propose a method and device for detecting and cleaning insulator contamination by using UAVs. Summary of the Invention

[0004] Technical problems to be solved: Aiming at the deficiencies of the prior art, the present invention provides a method and device for detecting and cleaning insulator contamination by using UAVs, which are used to quickly and efficiently detect the contamination degree on the surface of insulators and perform cleaning. Through image acquisition, image detection, cleaning operation and result feedback, the efficiency of insulator maintenance is significantly improved, the cost of manual inspection and the cleaning time are reduced, and at the same time, it has the advantages of real-time and high efficiency, and can effectively solve the problems in the background art.

[0005] Technical solution: To achieve the above object, the technical solution adopted by the present invention is: A device for detecting and cleaning insulator contamination by using UAVs includes an image acquisition device module, a signal transmission device module, a positioning device module, an energy management module, a detection module, a discrimination module, an alarm module, a cleaning device module, a cleaning control module and an archive report module. The image acquisition device module is connected to the signal transmission device module, the signal transmission device module is connected to the cleaning control module, the positioning device module and the cleaning device module, the cleaning device module is connected to the archive report module, the positioning device module is connected to the energy management module, the energy management module is connected to the detection module, the detection module is connected to the discrimination module, the discrimination module is connected to the alarm module, and the alarm module is connected to the cleaning control module.

[0006] As a preferred technical solution of the present application, the signal transmission device module includes a wireless communication module and a data interface. The wireless communication module is used to transmit the collected image data to the ground terminal on the one hand, and achieve high-speed data interaction between the UAV and the ground terminal. On the other hand, it is used to receive the control signal sent by the ground terminal to control the cleaning work of the UAV. The data interface is responsible for converting the transmitted data into a data format suitable for the subsequent detection module.

[0007] As a preferred technical solution of the present application, the energy management module includes a power supply device, a real-time power monitoring module and a low-power warning module. The power supply device provides power for the flight of the UAV and the motor in the cleaning equipment module. The real-time power monitoring module monitors the remaining power, working temperature and charging status of the UAV battery in real time.

[0008] As a preferred technical solution of the present application, the cleaning equipment module includes an electric motor device, a cleaning agent spraying device, an electric brush head device and a multi-functional robotic arm device. The electric motor device controls the spraying of the cleaning agent by the cleaning agent spraying device and the vibration of the electric brush head device by using the mechanical power provided by the electric motor through connecting to the power supply equipment carried by the UAV. The cleaning agent spraying device accurately transports the cleaning agent to the polluted area of the insulator by using a high-pressure nozzle. The electric brush head device is driven by an electric motor to rotate or vibrate at a high frequency to remove deep dirt in the area after the cleaning agent is sprayed. The multi-functional robotic arm device fixes the cleaning agent spraying device, the electric brush head device and their electric motor modules and connects them to the power supply equipment.

[0009] As a preferred technical solution of the present application, the cleaning control module includes a control module and a real-time monitoring module. The control module controls the spraying of the cleaning agent and the grinding of the electric brush head through the remote control device of the ground terminal. The real-time monitoring module monitors the cleaning process in real time and obtains the pollution removal situation through the high-definition camera device on the UAV.

[0010] As a preferred technical solution of the present application, the image acquisition device module includes an image data acquisition module, an image data transmission module, an image data management module, an image data output module, an image data analysis module and an image data storage library. The image data acquisition module is connected to the image data transmission module, the image data transmission module is connected to the image data management module, and the image data management module is connected to the image data output module, the image data analysis module and the image data storage library.

[0011] As a preferred technical solution of the present application, the image data acquisition module includes an image acquisition module, an image training node module, a real-time resource data module, an image model construction module, and an image model optimization module. The image acquisition module is connected to the image training node module, the image training node module is connected to the real-time resource data module, the real-time resource data module is connected to the image model construction module, and the image model construction module is connected to the image model optimization module.

[0012] A method for detecting and cleaning insulator contamination by an unmanned aerial vehicle (UAV) includes the following operating steps:

[0013] S1: The UAV is equipped with a high-definition camera device to conduct aerial photography of the surface of the target area, i.e., the insulator group, and the collected image data is transmitted to the ground terminal through the data transmission module.

[0014] S2: The ground terminal uses the Retinex image enhancement algorithm and an improved YOLO11 algorithm model to enhance and detect the transmitted pictures and generate detection information. This information includes two parts: one part is the collected image information, which includes the detected bounding boxes, categories, and confidence levels; the other part is the text information, which includes the coordinates, categories, and confidence levels of the detection boxes.

[0015] S3: The detection information is sent to the discrimination module. If the category in the text information is the same as the pre-set contamination category name and the confidence level is greater than the pre-given score, it is determined that a contaminated area has been detected. Then, the alarm device is triggered, and the detection information is saved simultaneously.

[0016] S4: The background staff starts and controls the cleaning module of the UAV according to the reserved detection information, turns on the cleaning agent and the electric brush head on the UAV, and conducts fixed-point cleaning of the contaminated area. At the same time, the removal of contamination during the cleaning process is monitored in real time through the high-definition camera device.

[0017] S5: After the cleaning is completed, repeat the steps of S1 - S3 to take pictures and detect the cleaning effect again. If the alarm device is triggered, the staff determines whether further cleaning is required based on the detection information. If so, re-execute S4 and S5. If not, proceed to the next step. If the alarm device is not triggered, proceed to the next step.

[0018] S6: Generate a result report before and after cleaning through the archiving and reporting module and archive it locally.

[0019] Advantages: Compared with the prior art, the present invention provides a method and device for detecting and cleaning insulator contamination using a drone, having the following advantages: The method and device for detecting and cleaning insulator contamination using a drone are used to quickly and efficiently detect the contamination degree on the surface of the insulator and perform cleaning. Through image acquisition, image detection, cleaning operation, and result feedback, the efficiency of insulator maintenance is significantly improved, the manual inspection cost and cleaning time are reduced, and at the same time, it has the advantages of real-time and high efficiency. The drone is equipped with a high-definition camera device to conduct an aerial survey of the surface of the target area, namely the insulator group, and transmit the collected image data to the ground terminal through the data transmission module. The ground terminal uses the Retinex image enhancement algorithm and an improved YOLO11 algorithm model to enhance and detect the transmitted pictures and generate detection information. This information includes two parts: one part is the collected image information, which includes the detected bounding boxes, categories, and confidence levels; the other part is the text information, which includes the coordinates, categories, and confidence levels of the detection boxes. The detection information is sent to the discrimination module. If the category in the text information is the same as the pre-set contamination category name and the confidence level is greater than the pre-given score, it is determined that a contaminated area is detected. Then, the alarm device is triggered, and at the same time, the detection information is saved. The background staff starts and controls the cleaning module of the drone according to the saved detection information, turns on the cleaning agent and the electric brush head on the drone, and performs fixed-point cleaning on the contaminated area. At the same time, the removal of contamination during the cleaning process is monitored in real time through the high-definition camera device. After the cleaning is completed, repeat the steps of S1-S3 to take pictures and detect the cleaning effect again. If the alarm device is triggered, the staff determines whether further cleaning is required based on the detection information. If so, re-execute S4 and S5. If not, proceed to the next step. If the alarm device is not triggered, proceed to the next step. Through the archiving and reporting module, generate the result reports before and after cleaning and archive them locally. The entire method for detecting and cleaning insulator contamination using a drone has a simple structure, is convenient to operate, and has a better effect than the traditional method. Brief Description of the Drawings

[0020] Figure 1 It is a schematic flowchart of a method for detecting and cleaning insulator contamination using a drone according to the present invention.

[0021] Figure 2 It is a schematic diagram of the overall structure of a device for detecting and cleaning insulator contamination using a drone according to the present invention.

[0022] Figure 3 It is a frame diagram of the improved yolo11 in a device for detecting and cleaning insulator contamination using a drone according to the present invention.

[0023] Figure 4It is the architecture diagram of the newly added GCGA module in yolo11 in a device for detecting and cleaning insulator contamination using an unmanned aerial vehicle according to the present invention.

[0024] Figure 5 It is the schematic structural diagram of the image acquisition device module in a device for detecting and cleaning insulator contamination using an unmanned aerial vehicle according to the present invention.

[0025] Figure 6 It is the schematic structural diagram of the image data acquisition module in a device for detecting and cleaning insulator contamination using an unmanned aerial vehicle according to the present invention. Detailed implementation manners

[0026] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and specific implementation manners. However, those skilled in the art will understand that the following described embodiments are some embodiments of the present invention, rather than all embodiments, and are only used to illustrate the present invention and should not be construed as limiting the scope of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention. Conditions not specified in the embodiments are carried out according to conventional conditions or conditions recommended by the manufacturer. Reagents or instruments not specified by the manufacturer can all be obtained as conventional products through commercial purchase.

[0027] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0028] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0029] Such as Figure 1-6As shown in the figure, a device for detecting and cleaning the dirt on insulators by an unmanned aerial vehicle (UAV) includes an image acquisition device module, a signal transmission device module, a positioning device module, an energy management module, a detection module, a discrimination module, an alarm module, a cleaning device module, a cleaning control module and an archive reporting module. The image acquisition device module is connected to the signal transmission device module, the signal transmission device module is connected to the cleaning control module, the positioning device module and the cleaning device module, the cleaning device module is connected to the archive reporting module, the positioning device module is connected to the energy management module, the energy management module is connected to the detection module, the detection module is connected to the discrimination module, and the discrimination module is connected to the alarm module. The alarm module is connected to the cleaning control module, which is used to quickly and efficiently detect the dirt degree on the insulator surface and clean it. Through image acquisition, image detection, cleaning operation and result feedback, the efficiency of insulator maintenance is significantly improved, the labor inspection cost and cleaning time consumption are reduced, and at the same time, it has the advantages of real-time and high efficiency.

[0030] Furthermore, the signal transmission device module includes a wireless communication module and a data interface. The wireless communication module is used to transmit the acquired image data to the ground terminal on the one hand and realize high-speed data interaction between the UAV and the ground terminal on the other hand. It is also used to receive the control signals sent by the ground terminal to control the cleaning work of the UAV. The data interface is responsible for converting the transmitted data into the data format suitable for the subsequent detection module.

[0031] Furthermore, the energy management module includes a power supply device, a real-time battery monitoring module and a low battery warning module. The power supply device provides power for the flight of the UAV and the motor in the cleaning device module. The real-time battery monitoring module monitors the remaining battery power, working temperature and charging status of the UAV battery in real time.

[0032] Furthermore, the cleaning device module includes an electric motor device, a cleaning agent spraying device, an electric brush head device and a multi-functional robotic arm device. The electric motor device is connected to the power supply equipment carried by the UAV. Using the mechanical power provided by the electric motor, it controls the cleaning agent spraying device to spray the cleaning agent and the electric brush head device to vibrate. The cleaning agent spraying device accurately transports the cleaning agent to the dirty area of the insulator by using a high-pressure nozzle. The electric brush head device is driven by the electric motor to rotate or vibrate the brush head at a high frequency to remove the deep dirt in the area after the cleaning agent is sprayed. The multi-functional robotic arm device fixes the cleaning agent spraying device, the electric brush head device and their electric motor modules and is connected to the power supply equipment.

[0033] Furthermore, the cleaning control module includes a control module and a real-time monitoring module. The control module controls the spraying of the cleaning agent and the grinding of the electric brush head through the remote control equipment of the ground terminal. The real-time monitoring module monitors the cleaning process in real time and obtains the dirt removal situation through the high-definition camera equipment on the UAV.

[0034] Further, the image acquisition device module includes an image data acquisition module, an image data transmission module, an image data management module, an image data output module, an image data analysis module, and an image data repository. The image data acquisition module is connected to the image data transmission module, the image data transmission module is connected to the image data management module, and the image data management module is connected to the image data output module, the image data analysis module, and the image data repository.

[0035] Further, the image data acquisition module includes an image acquisition module, an image training node module, a real-time resource data module, an image model building module, and an image model optimization module. The image acquisition module is connected to the image training node module, the image training node module is connected to the real-time resource data module, the real-time resource data module is connected to the image model building module, and the image model building module is connected to the image model optimization module.

[0036] A method for detecting and cleaning insulator contamination by an unmanned aerial vehicle includes the following steps:

[0037] S1: Use an unmanned aerial vehicle to carry a high-definition camera device to conduct an aerial survey of the surface of the target area (insulator group), and transmit the collected image data to the ground terminal through the data transmission module;

[0038] Among them, the unmanned aerial vehicle is equipped with a high-resolution camera device. The staff operates the unmanned aerial vehicle to take images of the target area (insulator group) according to the set aerial survey path and record the video stream images in real time. The unmanned aerial vehicle is also equipped with a GPS positioning module to collect the position information and timestamp during the aerial survey to ensure the accuracy of subsequent analysis.

[0039] S2: The ground terminal uses the Retinex image enhancement algorithm and the improved YOLO11 algorithm model to enhance and detect the transmitted pictures and generate detection information. This information includes two parts: one part is the collected image information, which includes the detected bounding boxes, categories, and confidences; the other part is the text information, which includes the coordinates, categories, and confidences of the detection boxes;

[0040] In the above example, the input of the Retinex image enhancement algorithm is the original image. The pixel values of the image are normalized to the range of [0, 1] or [0, 255] to prevent overflow. And RGB is converted to HSV to obtain the original luminance value I(x, y). Then, the original image is smoothed using a Gaussian filter to obtain the illumination component L(x, y) as shown in formula (1):

[0041] L(x, y) = G(x, y) * I(x, y) (1)

[0042] Where G(x, y) is the Gaussian kernel, and * represents the convolution operation.

[0043] Then, by dividing the original image by the illumination component, illumination normalization is achieved to enhance the reflection characteristics, as shown in Equation (2):

[0044]

[0045] where ∈ is a small constant to prevent the denominator from being zero (usually taken as 10e-6). The above formula can be in logarithmic form, which helps to enhance the contrast and convert the multiplicative relationship into an additive relationship, as shown in Equation (3):

[0046] R(x,y) = logI(x,y) - logL(x,y) (3)

[0047] In the above example, the improved YOLO11 model diagram is as shown in Figure 3 and the detailed detection steps are as follows:

[0048] S201. The picture is scaled to a pre-set fixed size by the model;

[0049] S202. The picture with a fixed size is input into the Backbone layer of the model for feature extraction, where the main feature extraction modules are the downsampling Conv module and the C3K2 module;

[0050] S203. The three feature maps with different sizes extracted by the Backbone layer are sent to the Neck layer for feature fusion and further extraction;

[0051] S204. The three feature maps output by the Neck layer are sent into the detection head (Detect) in the Head layer for detection, where detection boxes and class scores will be generated, and then non-maximum suppression (NMS) is used to remove duplicate detection boxes to generate the final detection information. Among them, a global coordinate grouped attention algorithm module (GCGA) is added before the C3K2 module in the Neck, as shown in Figure 4 By introducing global coordinates and a grouping mechanism during the feature extraction process, this module can effectively capture the long-range dependence relationships and important region features in the image, thereby significantly enhancing the model's ability to perceive global information and the expression ability of fine-grained features. This design not only makes up for the deficiency of the ordinary convolution module in extracting global information when dealing with large-scale targets or complex backgrounds, but also improves the robustness and detection accuracy of the model in multi-scale object detection tasks while maintaining a relatively low computational complexity. Specifically, for a given feature map:

[0052]

[0053] We divide it into G groups according to the number of channels, and each group contains C / G channels. Here, B is the batch size, C is the number of channels, and H and W are the height and width of the feature map respectively. The grouped feature map is expressed as:

[0054]

[0055] Then, we perform global average pooling and global max pooling operations on the grouped feature map in the height direction and width direction respectively:

[0056]

[0057] For each pooled grouped feature map, we apply a shared convolutional layer for feature processing. This shared convolutional layer consists of two 1×1 convolutional layers, a batch normalization layer, and a ReLU activation function, which are used to reduce and restore the channel dimension:

[0058] Y h,avg = Conv(X h,avg ), Y h,max = Conv(X h,max )

[0059] Y w,avg = Conv(X w,avg ), Y w,max = Conv(X w,max )

[0060] By adding the outputs of the convolutional layers and applying the Sigmoid activation function, the attention weights in the height direction and width direction are generated:

[0061]

[0062] where σ represents the Sigmoid activation function. Finally, the input feature map is weighted according to the attention weights to obtain the output feature map O:

[0063]

[0064] where the attention weights Ah and Aw will be expanded in the height and width directions respectively to match the size of the input feature map.

[0065] S3: Send the detection information into the discriminant module. If the category in the text information is the same as the pre-set fouling category name and the confidence level is greater than the pre-given score, it is judged that a fouling area is detected, then the alarm device is triggered, and at the same time, the detection information is saved;

[0066] S4: Based on the reserved detection information, the backstage staff activates and controls the cleaning module of the drone, turns on the cleaning agent and the electric brush head on the drone, and performs fixed-point cleaning on the soiled area. At the same time, the soiled removal situation during the cleaning process is monitored in real time through a high-definition camera device;

[0067] S5: After the cleaning is completed, repeat the steps of S1 - S3 to take pictures and detect the cleaning effect again. If the alarm device is triggered, the staff judges whether further cleaning is required based on the detection information. If so, re-execute S4 and S5. If not, proceed to the next step; if the alarm device is not triggered, proceed to the next step.

[0068] S6: Generate a result report before and after cleaning through the archiving and reporting module, and archive it locally.

[0069] The present invention provides a device for detecting and cleaning insulator dirt by using a drone, including the following modules:

[0070] Image acquisition device module, which is composed of a high-definition camera device carried by the drone and is used to collect high-definition images of the insulator surface in real time. The device supports the acquisition of high-definition images and video streams, and can conduct all-round aerial photography of the target insulator to ensure obtaining detailed visual data of the insulator area. The camera device can work under different lighting and weather conditions, and ensures image clarity for subsequent processing by intelligently adjusting the lens focal length and exposure time.

[0071] Signal transmission device module, which is composed of a wireless communication module carried by the drone and a data interface of the ground terminal. The specific functions include:

[0072] Wireless communication module: On the one hand, it is used to transmit the collected image data to the ground terminal and achieve high-speed data interaction between the drone and the ground terminal. On the other hand, it is used to receive the control signal sent by the ground terminal to control the cleaning work of the drone. This module supports multiple communication methods such as 5G, Wi-Fi or dedicated radio frequency bands to ensure the real-time transmission and efficient storage of image data and control signals.

[0073] Data interface: is responsible for converting the transmitted data into a data format suitable for the subsequent detection module.

[0074] Positioning device module, which is composed of a GPS module carried by the drone, realizes precise positioning and navigation of the drone in a complex environment, and ensures the efficient completion of detection and cleaning tasks.

[0075] Energy management module, which is composed of a power supply device carried by the drone and an energy monitoring module of the ground terminal, and optimizes the energy consumption distribution during the task execution process. The specific functions include:

[0076] Power supply device: It can supply power to the motors in the flight and cleaning equipment modules of the drone;

[0077] Real-time power monitoring module: It monitors the remaining power, operating temperature and charging status of the drone battery in real time. Through the monitored data, it ensures that the drone has sufficient power during mission execution, avoiding mission interruption or the risk of crashing due to power exhaustion;

[0078] Low power warning: When the power is below the preset threshold, the energy management module will issue a warning and automatically turn off other power-consuming devices, only powering the drone for flight.

[0079] Detection module, which consists of the improved YOLO11 algorithm model and image enhancement algorithm deployed on the ground terminal. This detection algorithm model is used to detect the enhanced image, generating detection information including bounding boxes, categories, confidence levels, etc.

[0080] Discrimination module: This module consists of a discrimination algorithm deployed on the terminal. It judges the text information in the detection information. If the category in the text information is the same as the preset dirt category name and the confidence level is greater than the preset score, it is judged that a dirty area has been detected, and the alarm module is executed and the detection information is retained at the terminal.

[0081] Alarm module, which issues visual or audible alarms if there is dirt; the alarm module can also be customized for different types of dirt (such as bird droppings, dust, oil stains, etc.) to remind the staff to handle it in time.

[0082] Cleaning equipment module, which consists of a cleaning agent spraying device and an electric brush head device carried by the drone, specifically:

[0083] Electric motor device: This device is the core device of the cleaning equipment module. By connecting to the power supply equipment carried by the drone, it uses the mechanical power provided by the electric motor to control the cleaning agent spraying device to spray the cleaning agent and the electric brush head device to vibrate, so as to complete the high-efficiency cleaning task;

[0084] Cleaning agent spraying device: This device accurately delivers the cleaning agent to the dirt area of the insulator using a high-pressure nozzle. In addition, the high-pressure nozzle can adjust the angle and switch the spraying mode through the cleaning control module (such as the spot spraying mode for small-area dirt and the atomizing spraying mode for larger-area dirt);

[0085] Electric brush head device: This device is driven by an electric motor to make the brush head rotate or vibrate at a high frequency, removing deep dirt from the area after the cleaning agent is sprayed, further improving the cleaning effect. The rotation speed and angle of the electric brush head are adjustable to adapt to dirt of different degrees and positions;

[0086] Multifunctional robotic arm device: The main purpose of this device is to fix the cleaning agent spraying device, the electric brush head device and their electric motor modules, and connect them to the power supply equipment to achieve stable cleaning operations.

[0087] Cleaning control module, located at the ground terminal, is used for the drone operator to control the drone cleaning operation, specifically including:

[0088] Control module: This module controls the spraying of the cleaning agent and the grinding of the electric brush head through the remote control equipment at the ground terminal to perform point cleaning on the target dirty area.

[0089] Real-time monitoring module: Through the high-definition camera equipment on the drone, it monitors the cleaning process in real time and obtains the situation of dirt removal.

[0090] Archiving and reporting module, responsible for generating a complete data report of the cleaning task, including detection information, comparison results of images before and after cleaning, task timestamps, etc., and saving the results locally for subsequent query and analysis.

[0091] The device for detecting and cleaning insulator dirt of the present invention has highly automated and intelligent characteristics. Each module cooperates with each other, providing a fast, accurate and efficient solution for insulator dirt detection and cleaning.

[0092] It should be noted that in this article, relational terms such as first and second (No. 1, No. 2) are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0093] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed.

Claims

1. A device for detecting and cleaning the contamination of insulators by an unmanned aerial vehicle, comprising an image acquisition device module, a signal transmission device module, a positioning device module, an energy management module, a detection module, a discrimination module, an alarm module, a cleaning device module, a cleaning control module and an archive reporting module, characterized in that: The image acquisition device module is connected to the signal transmission device module. The signal transmission device module is connected to the cleaning control module, the positioning device module, and the cleaning device module. The cleaning device module is connected to the archiving and reporting module. The positioning device module is connected to the energy management module. The energy management module is connected to the detection module. The detection module is connected to the discrimination module. The discrimination module is connected to the alarm module. The alarm module is connected to the cleaning control module.

2. The device for detecting and cleaning the pollution of insulators by an unmanned aerial vehicle according to claim 1, characterized in that: The signal transmission device module includes a wireless communication module and a data interface. The wireless communication module is used to transmit the acquired image data to the ground terminal on the one hand, and to achieve high-speed data interaction between the drone and the ground terminal. On the other hand, it is used to receive the control signals sent by the ground terminal to control the cleaning work of the drone. The data interface is responsible for converting the transmitted data into the data format required by the subsequent detection module.

3. The device for detecting and cleaning insulator contamination of an unmanned aerial vehicle according to claim 1, characterized in that: The energy management module includes a power supply device, a real-time battery level monitoring module, and a low battery warning module. The power supply device provides power for the flight of the drone and the motor in the cleaning device module. The real-time battery level monitoring module monitors the remaining battery level, operating temperature, and charging status of the drone battery in real time.

4. The device for detecting and cleaning insulator contamination by an unmanned aerial vehicle according to claim 1, characterized in that: The cleaning device module includes an electric motor device, a cleaning agent spraying device, an electric brush head device, and a multi-functional robotic arm device. The electric motor device is connected to the power supply equipment carried by the drone. Using the mechanical power provided by the electric motor, it controls the cleaning agent spraying device to spray the cleaning agent and the electric brush head device to vibrate. The cleaning agent spraying device uses a high-pressure nozzle to accurately deliver the cleaning agent to the contaminated area of the insulator. The electric brush head device is driven by an electric motor to rotate or vibrate at a high frequency to remove deep dirt from the area after the cleaning agent is sprayed. The multi-functional robotic arm device fixes the cleaning agent spraying device, the electric brush head device, and their electric motor modules, and is connected to the power supply equipment.

5. The device for detecting and cleaning insulator contamination by an unmanned aerial vehicle according to claim 1, characterized in that: The cleaning control module includes a control module and a real-time monitoring module. The control module controls the spraying of the cleaning agent and the polishing of the electric brush head through the remote control equipment of the ground terminal. The real-time monitoring module monitors the cleaning process in real time through the high-definition camera equipment on the drone and obtains the removal of dirt.

6. The device for detecting and cleaning insulator contamination by an unmanned aerial vehicle according to claim 1, characterized in that: The image acquisition device module includes an image data acquisition module, an image data transmission module, an image data management module, an image data output module, an image data analysis module, and an image data repository. The image data acquisition module is connected to the image data transmission module. The image data transmission module is connected to the image data management module. The image data management module is connected to the image data output module, the image data analysis module, and the image data repository.

7. A device for detecting and cleaning the contamination of insulators by an unmanned aerial vehicle according to claim 6, characterized in that: The image data acquisition module includes an image acquisition module, an image training node module, a real-time resource data module, an image model building module, and an image model optimization module. The image acquisition module is connected to the image training node module. The image training node module is connected to the real-time resource data module. The real-time resource data module is connected to the image model building module. The image model building module is connected to the image model optimization module.

8. A method for detecting and cleaning the contamination of insulators by an unmanned aerial vehicle, characterized in that: It includes the following operating steps: S1: Use a drone equipped with a high-definition camera to conduct an aerial survey of the surface of the target area, i.e., the insulator group, and transmit the collected image data to the ground terminal through a data transmission module; S2: The ground terminal uses the Retinex image enhancement algorithm and an improved YOLO11 algorithm model to enhance and detect the transmitted pictures, and generates detection information, which contains two parts: one part is the collected image information, which contains the detected bounding boxes, classes, and confidence levels; the other part is the text information, which contains the coordinates, classes, and confidence levels of the detection boxes; S3: Send the detection information to the discrimination module. If the class in the text information is the same as the pre-set fouling class name and the confidence level is greater than the pre-given score, it is determined that a fouled area has been detected. Then, trigger the alarm device and save the detection information at the same time; S4: According to the reserved detection information, the back-end staff starts and controls the cleaning module of the drone, turns on the cleaning agent and the electric brush head on the drone, and conducts fixed-point cleaning of the fouled area. At the same time, the fouling removal situation during the cleaning process is monitored in real time through the high-definition camera; S5: After the cleaning is completed, repeat the steps of S1-S3 to take pictures and detect the cleaning effect again. If the alarm device is triggered, the staff judges whether further cleaning is required based on the detection information. If so, re-execute S4 and S5. If not, proceed to the next step. If the alarm device is not triggered, proceed to the next step; S6: Generate a result report before and after cleaning through the archiving and reporting module, and archive it locally.

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