A power grid bird damage early warning method and system, a storage medium and an electronic device

Abstract

The application provides a power grid bird damage early warning method, system, storage medium and electronic equipment, and relates to the technical field of power grid protection. The method comprises the following steps: determining a first bird damage distribution map according to historical bird damage information and preset bird repelling device information, and determining a first unmanned aerial vehicle (UAV) inspection path according to the first bird damage distribution map and UAV nest information; determining difference information according to first inspection information, historical bird damage information and the first bird damage distribution map, and determining real-time bird damage conditions of each region on the first UAV inspection path according to the difference information; determining a second UAV inspection path according to the real-time bird damage conditions and the UAV nest information, and determining comprehensive bird damage information according to second inspection information; determining bird damage evaluation information according to the comprehensive bird damage information and the historical bird damage information, and generating a corresponding early warning report according to the bird damage evaluation information. The application solves the problem that the existing technology cannot effectively solve the power grid bird damage problem in time, resulting in a high bird damage failure rate of the overall power transmission line.

Description

Technical Field

[0001] This invention relates to the field of power grid protection technology, and in particular to a method, system, storage medium, and electronic device for early warning of bird damage to power grids. Background Technology

[0002] In recent years, with the increase in bird populations and numbers, their activity areas have been expanding, directly threatening the safe operation of power transmission lines. Bird-related faults include insulator contamination and corrosion caused by bird droppings; short circuits caused by birds touching conductors while in flight; some birds pecking at composite insulator sheaths, accelerating equipment aging; and wires, sticks, and other materials used by birds to build nests on towers, which may fall and cause short circuits. Nests of large birds of prey can even cause conductor breakage or insulator contamination, making bird damage one of the main causes of power transmission line tripping.

[0003] Currently, bird damage prevention and maintenance of power transmission lines mostly involve installing bird-repelling devices in areas with severe bird damage, combined with patrols along the transmission lines by maintenance personnel or drones. When birds or nests are found on the transmission lines, these targets are dealt with individually. However, traditional bird damage prevention and maintenance methods lack real-time and targeted capabilities. Furthermore, due to the uncontrollable nature of bird activity, pre-set bird-repelling devices and specific inspection routes cannot guarantee the overall safety of the power transmission lines. Summary of the Invention

[0004] Based on this, the purpose of the present invention is to provide a power grid bird damage early warning method, which aims to solve the problem that the existing technology cannot effectively and timely solve the problem of power grid bird damage, resulting in a high overall bird damage failure rate of transmission lines.

[0005] A method for early warning of bird damage to power grids according to an embodiment of the present invention includes:

[0006] The first bird damage distribution map is determined based on historical bird damage information and preset bird deterrence device information, and the first drone inspection route is determined based on the first bird damage distribution map and drone nest information.

[0007] The system acquires first inspection information collected by the drone along the first drone inspection path, determines difference information based on the first inspection information, the historical bird damage information, and the first bird damage distribution map, and determines the real-time bird damage status of each area along the first drone inspection path based on the difference information.

[0008] The second drone inspection path is determined based on the real-time bird damage situation and the drone nest information, and the second inspection information collected by the drone on the second drone inspection path within a preset time period is obtained, so as to determine the comprehensive bird damage information based on the second inspection information.

[0009] Bird damage assessment information is determined based on the comprehensive bird damage information and the historical bird damage information, and a corresponding early warning report is generated based on the bird damage assessment information.

[0010] In addition, the power grid bird hazard early warning method according to the above embodiments of the present invention may also have the following additional technical features:

[0011] Furthermore, the steps for determining the first bird damage distribution map based on historical bird damage information and preset bird deterrent device location information include:

[0012] The first bird damage data is determined based on the historical bird activity data and historical line fault data of the first area. The first area is the area on the power transmission line without bird deterrence devices.

[0013] The second bird damage data is determined based on the historical bird activity data of the second area, the historical line fault data of the second area, and the data of bird deterrence devices in the area. The second area is the area on the power transmission line equipped with bird deterrence devices.

[0014] The preset model is trained based on the first bird damage data, the second bird damage data, and the regional bird control device data, so that the preset model can determine the first bird damage distribution map based on the historical bird damage information and the preset bird control device information of the current area.

[0015] Furthermore, the step of determining the first drone inspection path based on the first bird damage distribution map and drone nest information includes:

[0016] The first drone inspection efficiency of each drone nest is determined based on the drone nest information.

[0017] Determine the required second UAV inspection efficiency for each area of ​​the transmission line based on the first bird damage distribution map.

[0018] Based on the location information of each drone nest, the inspection efficiency of the first drone and the inspection efficiency of the second drone, the first bird damage distribution map is divided into units to determine multiple inspection units, so that the inspection efficiency of the first drone in each inspection unit is not less than the inspection efficiency of the second drone.

[0019] The inspection path of the first UAV is determined based on the inspection unit and the UAV nest information within the inspection unit.

[0020] Further, the steps of determining the difference information based on the first inspection information, the historical bird damage information, and the first bird damage distribution map, and determining the real-time bird damage status of each area on the first UAV inspection path based on the difference information, include:

[0021] The first inspection information is analyzed to determine bird activity information, and preliminary real-time bird damage information is determined based on the bird activity information and the historical bird damage information.

[0022] Theoretical bird damage information is determined based on the historical bird damage information and the first bird damage distribution map, and the difference information is determined based on the theoretical bird damage information and the preliminary real-time bird damage information. The preliminary real-time bird damage information and the theoretical bird damage information both include at least bird species and quantity information, bird activity frequency information, bird nest quantity information, and bird droppings distribution frequency information. The difference information is the ratio information of the same dimension information in the preliminary real-time bird damage information and the theoretical bird damage information.

[0023] The real-time bird damage status of each area along the first UAV inspection path is determined based on the difference information.

[0024] Furthermore, the step of determining the real-time bird damage status of each area on the first UAV inspection path based on the difference information includes:

[0025] The ratio data of each item in the difference information are weighted and summed using a preset weighting algorithm to determine the difference value, and it is determined whether the difference value is greater than a preset value.

[0026] If so, the real-time bird damage situation is determined based on the preliminary real-time bird damage information and the first bird damage distribution map;

[0027] If not, the real-time bird damage situation is determined based on the theoretical bird damage information and the first bird damage distribution map.

[0028] Furthermore, the step of determining the second drone inspection path based on the real-time bird damage situation and the drone nest information includes:

[0029] The bird damage stage is determined based on the real-time bird damage situation, and the bird damage type is determined based on the bird damage stage, the preliminary real-time bird damage information, and the historical bird damage information.

[0030] The inspection target is determined based on the type of bird damage, and the area to be inspected is determined based on the environmental information of the area corresponding to the real-time bird damage situation and the inspection target.

[0031] The second drone inspection path is determined based on the drone nest information and the area to be inspected.

[0032] Further, the step of determining bird damage assessment information based on the comprehensive bird damage information and the historical bird damage information includes:

[0033] The first bird damage distribution map is adjusted based on the bird damage assessment information to determine the second bird damage distribution map;

[0034] The number and distribution of the preset bird deterrent devices are adjusted according to the second bird damage distribution map to determine the adjusted preset bird deterrent device information;

[0035] Based on the comprehensive bird damage information and the adjusted preset bird deterrence device information, a third bird damage distribution map is determined through the preset model.

[0036] The inspection path of the first UAV is adjusted based on the third bird damage distribution map and the UAV nest information.

[0037] Another objective of this invention is to provide a power grid bird hazard early warning system, the system comprising:

[0038] The first inspection determination module is used to determine the first bird damage distribution map based on historical bird damage information and preset bird deterrence device information, and to determine the first drone inspection path based on the first bird damage distribution map and drone nest information.

[0039] The real-time bird damage determination module is used to acquire the first inspection information collected by the drone along the first drone inspection path, to determine the difference information based on the first inspection information, the historical bird damage information and the first bird damage distribution map, and to determine the real-time bird damage status of each area along the first drone inspection path based on the difference information.

[0040] The second inspection determination module is used to determine the second drone inspection path based on the real-time bird damage situation and the drone nest information, and to obtain the second inspection information collected by the drone on the second drone inspection path within a preset time period, so as to determine the comprehensive bird damage information based on the second inspection information.

[0041] The early warning module is used to determine bird damage assessment information based on the comprehensive bird damage information and the historical bird damage information, and to generate a corresponding early warning report based on the bird damage assessment information.

[0042] Another objective of this invention is to provide a storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described power grid bird hazard early warning method.

[0043] Another objective of this invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the above-described power grid bird hazard early warning method.

[0044] This invention combines historical and existing situational data to predict and determine a first bird damage distribution map for the current area. Then, based on existing drone nest information and the first bird damage distribution map, it plans a first drone inspection path for the current area to conduct targeted inspections for predicted bird damage conditions in different areas, improving the targeting and efficiency of bird damage early warning. Real-time inspection information from the initial targeted inspections is used to assess the current bird damage situation at various locations within the current area. Based on the real-time bird damage situation, a second inspection path and plan are determined for different locations to avoid the impact of uncertain bird activity on bird damage early warning, thus ensuring the real-time nature of the warning. After comprehensive inspections of abnormal locations, comprehensive bird damage information for those locations is determined. A third bird damage distribution map is generated based on this comprehensive information, and the first drone inspection path is adjusted accordingly. This achieves dynamic and targeted adjustments to the bird damage early warning method, ensuring the accuracy and real-time nature of the warning. Furthermore, the location and quantity of preset bird deterrent devices are adjusted based on the comprehensive bird damage information to prevent bird damage before it occurs. Therefore, the present invention solves the problem that the existing technology cannot effectively and promptly resolve the problem of bird damage to power grids, resulting in a high overall bird damage failure rate of transmission lines. Attached Figure Description

[0045] Figure 1 This is a flowchart of the power grid bird hazard early warning method in the first embodiment of the present invention;

[0046] Figure 2 This is a structural block diagram of the power grid bird hazard early warning system in the second embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of the structure of the electronic device in the current regional embodiment of the present invention;

[0048] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0049] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0051] Example 1

[0052] Please see Figure 1 The figure shows a power grid bird hazard early warning method in the first embodiment of the present invention, which specifically includes steps S01-S04.

[0053] S01, determine the first bird damage distribution map based on historical bird damage information and preset bird deterrence device information, and determine the first drone inspection path based on the first bird damage distribution map and drone nest information.

[0054] Specifically, first bird damage data is determined based on historical bird activity data and historical line fault data of the first region, where the first region is an area on a power transmission line without bird deterrence devices; second bird damage data is determined based on historical bird activity data, historical line fault data, and regional bird deterrence device data of the second region, where the second region is an area on a power transmission line with bird deterrence devices; a preset model is trained based on the first bird damage data, the second bird damage data, and the regional bird deterrence device data, so that the preset model can determine the first bird damage distribution map based on the historical bird damage information and the preset bird deterrence device information of the current region. In practical implementation, the process begins by using extensive historical data to determine historical bird activity and corresponding line fault data in the power transmission line area before bird deterrence devices were installed. This establishes the correlation between the two. Then, based on historical bird activity and line fault data in areas with bird deterrence devices, the impact of the devices on line faults is determined, i.e., the impact of bird deterrence devices on bird damage. Through extensive data training and iteration, the system can predict and assess bird damage in the target area based on historical bird activity data and the existing distribution of bird deterrence devices, thus establishing a primary bird damage distribution map for the target area. This allows for targeted adjustments to the drone's inspection route, enabling timely early warnings of bird damage.

[0055] More specifically, the step of determining the first drone inspection path based on the first bird damage distribution map and drone nest information includes: determining the first drone inspection efficiency of each drone nest based on the drone nest information; determining the second drone inspection efficiency required for each area of ​​the transmission line based on the first bird damage distribution map; dividing the first bird damage distribution map into units based on the location information of each drone nest, the first drone inspection efficiency, and the second drone inspection efficiency to determine multiple inspection units, so that the first drone inspection efficiency within each inspection unit is not less than the second drone inspection efficiency; and determining the first drone inspection path based on the inspection units and the drone nest information within the inspection units. In specific implementation, the first bird damage distribution map is used to determine the required inspection efficiency, i.e., the drone inspection time, for areas with different bird damage levels. Due to different bird damage levels, the time required for drones to conduct preliminary inspections of areas of the same size is not entirely consistent. Then, based on the location information of each drone nest and the model and quantity information of the drones within the nest, the inspection efficiency of the drone nest is determined. Thus, by using the same judgment dimension, the area is accurately divided into units so that each unit can complete its inspection target, ensuring the effectiveness of bird damage inspection and early warning. In addition, during implementation, the division of units can be adjusted according to the inspection tasks of each drone nest itself. For example, if there are other inspection tasks at the current drone nest, or if each drone nest needs to keep a certain number of standby drones for emergency use, etc.

[0056] S02, acquire the first inspection information collected by the drone on the first drone inspection path, determine the difference information based on the first inspection information, the historical bird damage information and the first bird damage distribution map, and determine the real-time bird damage status of each area on the first drone inspection path based on the difference information.

[0057] Specifically, the first inspection information is analyzed to determine bird activity information, and preliminary real-time bird damage information is determined based on the bird activity information and the historical bird damage information. Theoretical bird damage information is determined based on the historical bird damage information and the first bird damage distribution map, and the difference information is determined based on the theoretical bird damage information and the preliminary real-time bird damage information. Both the preliminary real-time bird damage information and the theoretical bird damage information include at least information on the number of bird species, the frequency of bird activity, the number of bird nests, and the frequency of bird droppings distribution. The difference information is the ratio of the same dimension information in the preliminary real-time bird damage information and the theoretical bird damage information. The real-time bird damage status of each area along the first UAV inspection path is determined based on the difference information. In practical implementation, real-time bird damage information, i.e., the real-time bird activity status, can be obtained from the images captured and audio recorded during the inspection. Then, based on the first bird damage distribution map and historical bird damage information, the theoretical bird damage information of the inspection area at this time can be inferred to judge the current bird damage information, thereby determining whether the current bird damage status is within the predicted range. If yes, it means that the current bird damage situation is still within the control range and there is no uncertainty in bird activity. Therefore, the bird damage malfunction can be avoided by using the preset response methods or devices. If no, it means that the real-time bird damage situation may be beyond the prediction range, and more comprehensive data is needed for judgment.

[0058] More specifically, the step of determining the real-time bird damage status of each area on the first UAV inspection path based on the difference information includes: performing a weighted summation operation on the ratio data of each item in the difference information using a preset weighted algorithm to determine the difference value, and determining whether the difference value is greater than a preset value; if so, determining the real-time bird damage status based on the preliminary real-time bird damage information and the first bird damage distribution map; if not, determining the real-time bird damage status based on the theoretical bird damage information and the first bird damage distribution map. In specific implementation, preliminary inspections are used to judge possible abnormal situations, and then targeted comprehensive inspections are conducted based on the abnormal situations, thereby achieving real-time and targeted bird damage early warning. Then, based on the information from the comprehensive inspection, an accurate and comprehensive judgment is made on the abnormal situations, and based on the judgment results, the bird damage status is predicted and warned.

[0059] S03, determine the second drone inspection path based on the real-time bird damage situation and the drone nest information, and obtain the second inspection information collected by the drone on the second drone inspection path within a preset time period, so as to determine the comprehensive bird damage information based on the second inspection information.

[0060] Specifically, the bird damage stage is determined based on the real-time bird damage situation, and the bird damage type is determined based on the bird damage stage, the preliminary real-time bird damage information, and the historical bird damage information; the inspection target is determined based on the bird damage type, and the area to be inspected is determined based on the environmental information of the area corresponding to the real-time bird damage situation and the inspection target; the second drone inspection path is determined based on the drone nest information and the area to be inspected. In practical implementation, by targeting different bird damage stages and bird damage types, the inspection targets that need to be specifically inspected and detected are determined. Then, the area to be inspected is determined based on the environmental information of the location where the abnormal situation occurs. Thus, the path is designed for the inspection area and the inspection target to ensure the targeting and accuracy of the comprehensive inspection, and to avoid high-frequency over-inspection in unnecessary places, thereby reducing inspection efficiency.

[0061] S04, determine bird damage assessment information based on the comprehensive bird damage information and the historical bird damage information, and generate a corresponding early warning report based on the bird damage assessment information.

[0062] Specifically, by using real-time bird damage assessment information to determine corresponding early warning reports, staff can obtain real-time information on bird damage conditions and then make targeted adjustments to bird damage prevention measures to reduce the probability of bird damage failures or even avoid them altogether.

[0063] Specifically, after step S04, the process further includes: adjusting the first bird damage distribution map based on the bird damage assessment information to determine a second bird damage distribution map; adjusting the number and distribution of the preset bird deterrent devices based on the second bird damage distribution map to determine the adjusted preset bird deterrent device information; determining a third bird damage distribution map based on the comprehensive bird damage information and the adjusted preset bird deterrent device information using the preset model; and adjusting the first UAV inspection path based on the third bird damage distribution map and the UAV nest information. By adjusting the first bird damage distribution map using bird damage assessment information to obtain a second bird damage distribution map under the current condition without intervention, the subsequent bird damage failure situation can be predicted using the second bird damage distribution map. Furthermore, by adjusting the location and number of preset bird deterrent devices based on the second bird damage distribution map, bird damage failures can be prevented in advance, or even avoided through bird deterrent devices. Furthermore, based on the adjusted status of the preset bird deterrent device, the second bird damage distribution map is adjusted to determine a third bird damage distribution map that matches the current real-time situation. Based on the third bird damage distribution map, the bird damage early warning method of this scheme can be implemented to ensure the real-time nature and pertinence of this method, thus ensuring both the accuracy and efficiency of this method.

[0064] In summary, the power grid bird damage early warning method in the above embodiments of the present invention predicts and determines a first bird damage distribution map of the current area by combining historical data and existing situation data. Then, based on existing drone nest information and the first bird damage distribution map, it plans the first drone inspection path of the current area to conduct targeted inspections for the predicted bird damage situation in different areas, thereby improving the targeting and efficiency of bird damage early warning. Then, it judges the current bird damage situation at various locations in the current area by using the real-time inspection information of the initial targeted inspection. Then, it determines the second inspection path and planning for different locations based on the real-time bird damage situation to avoid the impact of the uncertainty of bird activity on bird damage early warning, thereby ensuring the real-time nature of bird damage early warning. After a comprehensive inspection of abnormal locations, it determines the comprehensive bird damage information of the abnormal locations. Then, it generates a third bird damage distribution map based on the comprehensive bird damage information and adjusts the first drone inspection path, thereby realizing the dynamic and targeted adjustment of the bird damage early warning method to ensure the accuracy and real-time nature of bird damage early warning. Furthermore, it adjusts the location and number of preset bird deterrent devices based on the comprehensive bird damage information so that bird damage is prevented before it occurs. Therefore, the present invention solves the problem that the existing technology cannot effectively and promptly resolve the problem of bird damage to power grids, resulting in a high overall bird damage failure rate of transmission lines.

[0065] Example 2

[0066] Please see Figure 2 The diagram shown is a structural block diagram of the power grid bird damage early warning system proposed in the second embodiment of the present invention. The power grid bird damage early warning system 200 includes: a first inspection and determination module 21, a real-time bird damage determination module 22, a second inspection and determination module 23, and an early warning module 24, wherein:

[0067] The first inspection determination module 21 is used to determine the first bird damage distribution map based on historical bird damage information and preset bird deterrence device information, and to determine the first drone inspection path based on the first bird damage distribution map and drone nest information.

[0068] The real-time bird damage determination module 22 is used to acquire the first inspection information collected by the drone on the first drone inspection path, to determine the difference information based on the first inspection information, the historical bird damage information and the first bird damage distribution map, and to determine the real-time bird damage status of each area on the first drone inspection path based on the difference information.

[0069] The second inspection determination module 23 is used to determine the second drone inspection path based on the real-time bird damage situation and the drone nest information, and to obtain the second inspection information collected by the drone on the second drone inspection path within a preset time period, so as to determine the comprehensive bird damage information based on the second inspection information.

[0070] The early warning module 24 is used to determine bird damage assessment information based on the comprehensive bird damage information and the historical bird damage information, so as to generate a corresponding early warning report based on the bird damage assessment information.

[0071] The functions or operation steps implemented by the above modules are largely the same as those in the above method embodiments, and will not be repeated here.

[0072] Example 3

[0073] In another aspect, the present invention also proposes an electronic device, please refer to [link to relevant documentation]. Figure 3 The diagram shows an electronic device in the current regional embodiment of the present invention, including a memory 20, a processor 10, and a computer program 30 stored in the memory and executable on the processor. When the processor 10 executes the computer program 30, it implements the above-described power grid bird hazard early warning method.

[0074] In some embodiments, the processor 10 may be a central processing unit (CPU), controller, microcontroller, microprocessor or other data processing chip, used to run program code stored in memory 20 or process data, such as executing access restriction programs.

[0075] The memory 20 includes at least one type of readable storage medium, such as flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 20 can be an internal storage unit of an electronic device, such as the hard disk of the electronic device. In other embodiments, the memory 20 can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. Furthermore, the memory 20 can include both internal and external storage units of the electronic device. The memory 20 can be used not only to store application software and various types of data of the electronic device, but also to temporarily store data that has been output or will be output.

[0076] It should be pointed out that, Figure 3 The structure shown does not constitute a limitation on the electronic device. In other embodiments, the electronic device may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0077] This invention also proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described power grid bird hazard early warning method.

[0078] Those skilled in the art will understand that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0079] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0080] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0081] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0082] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for early warning of bird damage to power grids, characterized in that, The method includes: The first bird damage distribution map is determined based on historical bird damage information and preset bird deterrence device information, and the first drone inspection route is determined based on the first bird damage distribution map and drone nest information. The system acquires first inspection information collected by the drone along the first drone inspection path, determines difference information based on the first inspection information, the historical bird damage information, and the first bird damage distribution map, and determines the real-time bird damage status of each area along the first drone inspection path based on the difference information. The second drone inspection path is determined based on the real-time bird damage situation and the drone nest information, and the second inspection information collected by the drone on the second drone inspection path within a preset time period is obtained, so as to determine the comprehensive bird damage information based on the second inspection information. Bird damage assessment information is determined based on the comprehensive bird damage information and the historical bird damage information, and a corresponding early warning report is generated based on the bird damage assessment information; The steps of determining the difference information based on the first inspection information, the historical bird damage information, and the first bird damage distribution map, and determining the real-time bird damage status of each area on the first UAV inspection path based on the difference information, include: The first inspection information is analyzed to determine bird activity information, and preliminary real-time bird damage information is determined based on the bird activity information and the historical bird damage information. Theoretical bird damage information is determined based on the historical bird damage information and the first bird damage distribution map, and the difference information is determined based on the theoretical bird damage information and the preliminary real-time bird damage information. The preliminary real-time bird damage information and the theoretical bird damage information both include at least bird species and quantity information, bird activity frequency information, bird nest quantity information, and bird droppings distribution frequency information. The difference information is the ratio information of the same dimension information in the preliminary real-time bird damage information and the theoretical bird damage information. Based on the difference information, determine the real-time bird damage status of each area on the first UAV inspection path; The step of determining the real-time bird damage status of each area on the first UAV inspection path based on the difference information includes: The ratio data of each item in the difference information are weighted and summed using a preset weighting algorithm to determine the difference value, and it is determined whether the difference value is greater than a preset value. If so, the real-time bird damage situation is determined based on the preliminary real-time bird damage information and the first bird damage distribution map; If not, determine the real-time bird damage situation based on the theoretical bird damage information and the first bird damage distribution map; The step of determining bird damage assessment information based on the comprehensive bird damage information and the historical bird damage information includes: The first bird damage distribution map is adjusted based on the bird damage assessment information to determine the second bird damage distribution map; The number and distribution of the preset bird deterrent devices are adjusted according to the second bird damage distribution map to determine the adjusted preset bird deterrent device information; Based on the comprehensive bird damage information and the adjusted preset bird deterrence device information, a third bird damage distribution map is determined through the preset model. The inspection path of the first UAV is adjusted based on the third bird damage distribution map and the UAV nest information.

2. The power grid bird hazard early warning method according to claim 1, characterized in that, The steps for determining the first bird damage distribution map based on historical bird damage information and preset bird deterrent device location information include: The first bird damage data is determined based on the historical bird activity data and historical line fault data of the first area. The first area is the area on the power transmission line without bird deterrence devices. The second bird damage data is determined based on the historical bird activity data of the second area, the historical line fault data of the second area, and the data of bird deterrence devices in the area. The second area is the area on the power transmission line equipped with bird deterrence devices. The preset model is trained based on the first bird damage data, the second bird damage data, and the regional bird control device data, so that the preset model can determine the first bird damage distribution map based on the historical bird damage information and the preset bird control device information of the current area.

3. The power grid bird hazard early warning method according to claim 1, characterized in that, The steps for determining the first drone inspection path based on the first bird damage distribution map and drone nest information include: The first drone inspection efficiency of each drone nest is determined based on the drone nest information. Determine the required second UAV inspection efficiency for each area of ​​the transmission line based on the first bird damage distribution map. Based on the location information of each drone nest, the inspection efficiency of the first drone and the inspection efficiency of the second drone, the first bird damage distribution map is divided into multiple inspection units to ensure that the inspection efficiency of the first drone in each inspection unit is not less than the inspection efficiency of the second drone. The inspection path of the first drone is determined based on the inspection unit and the drone nest information within the inspection unit.

4. The power grid bird damage early warning method according to claim 1, characterized in that, The steps for determining the second drone inspection path based on the real-time bird damage situation and the drone nest information include: The bird damage stage is determined based on the real-time bird damage situation, and the bird damage type is determined based on the bird damage stage, the preliminary real-time bird damage information, and the historical bird damage information. The inspection target is determined based on the type of bird damage, and the area to be inspected is determined based on the environmental information of the area corresponding to the real-time bird damage situation and the inspection target. The second drone inspection path is determined based on the drone nest information and the area to be inspected.

5. A power grid bird damage early warning system, characterized in that, For implementing the power grid bird hazard early warning method as described in any one of claims 1 to 4, the system comprises: The first inspection determination module is used to determine the first bird damage distribution map based on historical bird damage information and preset bird deterrence device information, and to determine the first drone inspection path based on the first bird damage distribution map and drone nest information. The real-time bird damage determination module is used to acquire the first inspection information collected by the drone along the first drone inspection path, to determine the difference information based on the first inspection information, the historical bird damage information and the first bird damage distribution map, and to determine the real-time bird damage status of each area along the first drone inspection path based on the difference information. The second inspection determination module is used to determine the second drone inspection path based on the real-time bird damage situation and the drone nest information, and to obtain the second inspection information collected by the drone on the second drone inspection path within a preset time period, so as to determine the comprehensive bird damage information based on the second inspection information. The early warning module is used to determine bird damage assessment information based on the comprehensive bird damage information and the historical bird damage information, and to generate a corresponding early warning report based on the bird damage assessment information.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the power grid bird hazard early warning method as described in any one of claims 1 to 4.

7. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the power grid bird hazard early warning method as described in any one of claims 1-4.

Images