Bird damage prevention and control method, device and equipment for transformer substation and medium

Abstract

The invention discloses a substation bird damage prevention and control method, device and equipment and a medium, and relates to the field of substation bird repelling, and the method comprises the steps: dividing a plurality of laser bird repelling devices into a plurality of equipment groups according to geographic positions or functional requirements; when one equipment group captures that the birds enter the monitoring area, a bird image is acquired, and a bird intrusion alarm is triggered; preprocessing the bird image to generate a preprocessed bird image; inputting the pre-processed bird image into a neural network model, and determining the type of a target bird in the bird image; the multiple equipment groups are linked to emit bird repelling laser corresponding to the type of the target bird, and bird repelling measures of the laser bird repelling devices in the equipment groups are uploaded to a cloud server; and on the basis of the cloud server, bird repelling measures of each equipment group are dispatched, a bird repelling defense line is formed, accurate real-time response can be made to birds of different types and habits, effective integration and sharing of data are realized, and the data analysis difficulty is reduced.

Description

Technical Field

[0001] The present application relates to the field of bird repelling in substations, and in particular to a method, device, equipment and medium for bird pest control in substations. Background Art

[0002] Bird activity has increased significantly at both urban and suburban substations, leading to a rise in bird damage within substations. This has posed a threat to the reliable and stable operation of power systems and increased the workload for power operators dealing with bird damage. Existing bird control measures at substations are ineffective, with bird repellent methods lacking coverage and birds potentially adapting.

[0003] Bird pest control at substations has always been a major challenge for power supply companies. First, bird nesting poses the greatest threat to substation safety during bird activities. When birds carry debris in their mouths or their nests are blown away by wind and rain and fall on outdoor electrical equipment, this can easily cause grounding faults. Secondly, birds flying in and out of the substation to build nests can also pose a threat to substation operations. Larger birds, when in flight, can short-circuit air gaps, causing short circuits between phases or to the ground, leading to equipment failure. Furthermore, during periods of high bird infestation, operators must conduct numerous special inspections and remove bird nests, increasing maintenance workload and consuming significant manpower and material resources. When operators remove bird nests, if the insulation distances between phases and to ground are short, this can cause electrical discharges between phases or to the ground, causing equipment tripping and posing a significant threat to the safety of on-site personnel. Frequent bird infestations increase the number of power outages, leading to unplanned equipment downtime and compromising power supply reliability.

[0004] Substations are mostly outdoors, creating the potential for frequent bird infestations due to gaps in the equipment. The gate structures within substations primarily include the main transformer and busbar gate structures. If a bird's nest falls due to external forces or a wire in its mouth falls, it can directly cause a transformer or busbar short circuit. Similarly, if the disconnector within the substation has bird infestation defects, this can cause a short circuit. Some substations in certain cities have already experienced emergency power outages due to bird nest management. Frequent bird infestations have become a significant potential safety hazard threatening the safe operation of substations.

[0005] In recent years, research institutions have systematically studied bird image recognition, pan / tilt motor control, target tracking, and bird repellent technologies, analyzing the impact of various technologies on bird repellent effectiveness. To address bird infestations in substations, relevant research institutions have also conducted research on a variety of substation-specific bird repellent products based on artificial intelligence, motor control, and acoustic bird repellent.

[0006] In 2010, Japan Electric Power Company (TEPCO) developed a drone inspection and bird-repellent system, using drones for aerial inspections and bird repellent. Equipped with cameras and acoustic wave devices, the drones ensure the safety of power facilities through real-time monitoring and bird-repellent operations. In 2015, the Department of Electrical Engineering and Applied Electronics at Tsinghua University, in collaboration with a power company, developed an intelligent system combining image recognition and acoustic bird repellent. This system uses high-definition cameras to capture bird activity, employs artificial intelligence algorithms for identification, and employs acoustic wave devices to repel birds. In 2019, the Chongqing Research Institute of Shanghai Jiao Tong University launched a project on integrated intelligent bird-repellent equipment for airports, integrating technologies such as Doppler radar for detecting approaching birds, ultrasonic bird repellent technology, simulated eagle sound sources, and nighttime strobe light repellent. In 2023, Zhejiang University developed a bionic bird-repellent robot. This robot mimics the appearance and flight patterns of birds of prey and patrols around power facilities to repel birds. Equipped with a high-resolution camera and AI recognition system, the robot monitors bird activity in real time and intelligently repels birds.

[0007] The prevention and control of bird pests in substations is progressing steadily. At present, laser bird repellers, ultrasonic bird repellers, loudspeaker bird repellers, bird-proof baffles, bird-proof windmills, bird-proof thorns, bird-proof nets, etc. are still commonly used. Among them, passive equipment (does not contain intelligent recognition units and can only work mechanically according to the corresponding mode) has the problems of low equipment operation efficiency, short effective time (bird adaptation), poor equipment stability, serious light pollution and sound pollution. Intelligent equipment has problems such as poor recognition rate, inability to accurately lock and strike, high cost, and large size.

[0008] The effectiveness of prevention and control measures is limited, and the current problems are as follows:

[0009] (1) Difficulty in precise prevention and control: Bird species and habits vary from region to region, and the extent and manner of their harm to substations are also different. The effectiveness of traditional laser bird repellents and ultrasonic bird repellents currently used in substations is limited to specific environments and bird types. They lack precision and flexibility, and are difficult to respond effectively to different situations. For example, traditional laser bird repellents use a fixed-setting scanning method, which cannot accurately respond to birds of different species and habits. Birds also have different sensitivities to sound waves, and the currently used ultrasonic bird repellent method is also difficult to achieve precise prevention and control.

[0010] (2) Difficulty in real-time response: The occurrence of bird damage in substations is unpredictable and often causes serious consequences in a short period of time. Existing monitoring methods often rely on manual inspections or passive alarm systems. Even if bird activity is detected, existing response measures may still require manual intervention, which is a time-consuming process and cannot effectively prevent bird damage before it causes actual damage. For example, traditional laser bird repellent equipment lacks linkage with monitoring equipment such as cameras, making it impossible to achieve real-time monitoring and automatic response. Ultrasonic bird repellent equipment is easily affected by environmental factors, resulting in unstable real-time prevention and control effects.

[0011] (3) Difficulty in data analysis: In the prevention and control of bird pests in substations, the collection and analysis of effective data are crucial, but the current challenge lies in the lack of data and insufficient utilization. First, the data collected by different systems are not effectively integrated and shared, resulting in the inability to maximize the value of the data; second, even if the data is collected, due to the lack of professional data analysis tools or platforms, the data is often not fully analyzed, and thus cannot provide support for the formulation of targeted prevention and control strategies. For example, the ultrasonic and laser bird repellents currently used in some substations are not equipped with data monitoring platforms, and the data lacks effective integration and sharing, and the value of the data cannot be maximized. Summary of the Invention

[0012] The purpose of this application is to provide a method, device, equipment and medium for bird pest control in substations to solve the problems of difficulty in accurate prevention and control, difficulty in real-time response and difficulty in data analysis.

[0013] To achieve the above objectives, this application provides the following solutions:

[0014] In a first aspect, the present application provides a method for preventing and controlling bird pests in a substation, comprising:

[0015] Divide multiple laser bird repellent devices into multiple device groups according to geographical location or functional requirements; the laser bird repellent devices in the device groups communicate and collaborate with each other to share monitoring data and bird intrusion alarm information;

[0016] When a device group captures a bird entering the monitoring area, it obtains an image of the bird and triggers a bird intrusion alarm;

[0017] preprocessing the bird image to generate a preprocessed bird image;

[0018] Inputting the pre-processed bird image into a neural network model to identify the type of target bird in the bird image;

[0019] Linking multiple device groups to emit bird-repelling lasers corresponding to the types of target birds, and uploading bird-repelling measures of the laser bird-repelling devices in the device groups to a cloud server;

[0020] Based on the cloud server, bird-repelling measures for each of the device groups are dispatched to form a bird-repelling defense line.

[0021] In a second aspect, the present application provides a substation bird pest control device, comprising:

[0022] A division module is used to divide multiple laser bird repellent devices into multiple device groups according to geographical location or functional requirements; the laser bird repellent devices in the device group communicate and cooperate with each other to share monitoring data and bird intrusion alarm information;

[0023] a bird image acquisition module, configured to acquire bird images and trigger a bird intrusion alarm when one of the device groups captures a bird entering the monitoring area;

[0024] a preprocessing module, configured to preprocess the bird image to generate a preprocessed bird image;

[0025] a target bird recognition module, configured to input the pre-processed bird image into a neural network model and identify the type of target bird in the bird image;

[0026] A linkage module is used to link multiple device groups to emit bird-repelling lasers corresponding to the types of target birds, and upload the bird-repelling measures of the laser bird-repelling devices in the device groups to the cloud server;

[0027] The scheduling module is used to schedule the bird-repelling measures of each device group based on the cloud server to form a bird-repelling defense line.

[0028] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-described methods for controlling bird pests in substations.

[0029] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned methods for preventing and controlling bird pests in substations.

[0030] According to the specific embodiments provided by this application, this application discloses the following technical effects: this application sets up multiple laser bird-repelling devices and divides them into multiple equipment groups to identify birds entering the monitoring area. Without manual inspection or passive alarm system, bird activities can be detected and real-time response can be achieved; at the same time, the type of target bird in the bird image is identified through a neural network model, and based on the type, the laser bird-repelling device emits the corresponding bird-repelling laser to make accurate responses to birds of different types and habits; in addition, the bird-repelling measures of each laser-driven device are uploaded to the cloud server, so as to schedule the bird-repelling measures of each of the equipment groups to form a bird-repelling defense line, so as to achieve effective integration and sharing of data and reduce the difficulty of data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 This is a flow chart of a method for preventing and controlling bird damage in a substation in one embodiment of the present application;

[0033] Figure 2 A schematic diagram of data uploading provided in an embodiment of the present application;

[0034] Figure 3 A statistical chart of bird data from June 12 to June 30 provided in an embodiment of the present application;

[0035] Figure 4 A monitoring chart of bird population changes during different periods from June 12 to June 30, provided in an embodiment of the present application;

[0036] Figure 5 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0038] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0039] This application utilizes advanced laser technology, high-definition monitoring equipment, and artificial intelligence algorithms to accurately identify and harmlessly remove birds. It also optimizes prevention strategies through data analysis, reducing manpower and material resources and improving the safety and reliability of the power grid system. This application not only improves the efficiency and effectiveness of bird control at substations, but also demonstrates a commitment to ecological and environmental protection, in line with current trends in sustainable development.

[0040] The embodiment of the present application provides a method for preventing and controlling bird damage in a substation, such as Figure 1 As shown, the method is executed by a computer device, specifically, it can be executed by a computer device such as a terminal or a server alone, or it can be executed by a terminal and a server together. In the embodiment of the present application, the method includes the following steps 101 to 106. Among them:

[0041] Step 101: Divide a plurality of laser bird-repelling devices into a plurality of device groups according to geographical locations or functional requirements; the laser bird-repelling devices in the device groups communicate and collaborate with each other to share monitoring data and bird intrusion alarm information.

[0042] Step 102: When one of the device groups captures a bird entering the monitoring area, an image of the bird is acquired and a bird intrusion alarm is triggered.

[0043] Step 103: pre-processing the bird image to generate a pre-processed bird image.

[0044] Step 104: Input the pre-processed bird image into a neural network model to identify the type of target bird in the bird image.

[0045] Step 105: Linking multiple device groups to emit bird-repelling lasers corresponding to the types of the target birds, and uploading the bird-repelling measures of the laser bird-repelling devices in the device groups to the cloud server.

[0046] Step 106: Based on the cloud server, dispatch bird-repelling measures for each of the device groups to form a bird-repelling defense line.

[0047] In an exemplary embodiment, triggering a bird intrusion alarm may be replaced by the following steps.

[0048] Based on multiple consecutive frames of bird images, determine whether the bird's stay time in the monitoring area exceeds the set time; if so, trigger the bird intrusion alarm and convey the bird intrusion alarm information to the monitoring personnel; if not, do not trigger the bird intrusion alarm.

[0049] Furthermore, when the intelligent laser bird repellent device (i.e., laser bird repellent device) captures a bird entering the preset monitoring area through its high-definition camera (or camera), the intelligent event detection system immediately recognizes this behavior and triggers a bird intrusion alarm. This alarm can be transmitted to monitoring personnel through sound, light, or remote notification, so that timely measures can be taken. If a bird stays in the monitoring area for more than a preset time, the intelligent event detection system can also identify and trigger a stay alarm.

[0050] In an exemplary embodiment, step 103 may be replaced by the following steps.

[0051] The bird image is segmented and denoised to generate a pre-processed bird image; the pre-processed bird image can highlight the characteristics of the target bird while suppressing noise and interference from the environmental background.

[0052] Furthermore, we collected images and videos containing birds at various angles and magnifications in substation scenarios, and studied image preprocessing techniques such as bird image enhancement, segmentation, and denoising to highlight target features while suppressing noise and interference from the environmental background, thereby improving the recognition rate of target images.

[0053] In an exemplary embodiment, step 104 may be replaced by the following steps.

[0054] The neural network model is used to analyze the characteristic distribution of target birds of different scales in the preprocessed bird image; based on the characteristic distribution, a multi-scale, adaptive anchor frame strategy is used to optimize the neural network model and construct an enhanced model; and the type of target bird in the bird image is identified according to the enhanced model.

[0055] Furthermore, we will study multi-scale and adaptive AnchorBoxes strategies, end-to-end target detection training methods, and optimize the network model architecture of the YOLO-v5 model to achieve high-precision recognition of bird images.

[0056] First, we thoroughly analyzed the characteristic distribution of objects of different scales in images and developed a multi-scale, adaptive AnchorBoxes strategy to adapt to the detection needs of birds of varying sizes. Then, based on these strategies, we developed an end-to-end object detection training method and optimized the network architecture of the YOLO-v5 model to enhance the model's ability to recognize a variety of bird images. Finally, we experimentally validated the proposed multi-scale adaptive AnchorBoxes strategy and the optimized YOLO-v5 model, achieving high-precision recognition of bird images and improving the accuracy and robustness of object detection. These studies significantly improve the efficiency and effectiveness of bird detection, providing strong technical support for substation-related application scenarios.

[0057] In an exemplary embodiment, step 105 includes the following steps.

[0058] The above-mentioned bird recognition is specially optimized for complex power grid environments. It can accurately identify a variety of birds, immediately record alarms, and link bird-repelling devices to drive them away.

[0059] Once the laser bird repellent device detects a bird, the camera can automatically adjust its angle and focal length to accurately monitor the target and trigger the laser bird repellent function to emit a green laser of a specific wavelength and power. This green laser is not only relatively safe for the human eye, but also for birds, its specific wavelength characteristics and brightness can effectively attract their attention without causing harm to the birds, and stimulate their natural reaction to avoid the area, thereby prompting them to leave the monitored area.

[0060] The laser bird repellent mode of the laser bird repellent device can be intelligently selected and adjusted according to the activities of birds and environmental conditions to achieve the best bird repellent effect.

[0061] In an exemplary embodiment, uploading the bird repelling measures of the laser bird repelling devices in the device group to the cloud server specifically includes:

[0062] Based on the time synchronization mechanism, gating scheduling strategy and traffic filtering management solution of the TSN switch, the bird-repelling measures of the laser bird-repelling device are uploaded to the cloud server through the TSN switch to form a substation network architecture.

[0063] Furthermore, in larger areas or situations where multi-angle bird repellent is required, the coverage and effectiveness of a single device may be limited, making it impossible to achieve a comprehensive bird repellent effect. Multi-device linkage can provide more comprehensive coverage and more flexible bird repellent strategies to adapt to different environments and changes in bird behavior.

[0064] like Figure 2 As shown, time-sensitive network (TSN) switches can effectively reduce transmission latency and jitter compared to traditional switches. A TSN-based substation bird-repellent system network architecture optimization method addresses the issues of switch bandwidth waste, complex network environments, and difficulty ensuring critical service messages in smart substations within the State Grid system. By utilizing TSN's time synchronization mechanism, gating scheduling strategies, and traffic filtering management solutions, the substation network architecture is optimized to reduce latency and jitter in sensitive traffic transmission.

[0065] By applying TSN's features to the bird-repelling system, establishing a time-sensitive network not only reduces transmission latency and jitter, enabling rapid fault location and repair, but also improves the robustness of the system and ensures that critical services are not disrupted. Therefore, TSN-enabled switches supporting Qci, Qbv, and Qbu technologies are introduced to rebuild the network architecture. The station control layer and process layer each form their own TSN network, each containing one or more TSN switches. Cross-bay devices can also be used to connect the process and station control layer networks.

[0066] In an exemplary embodiment, step 106 may be replaced by the following steps.

[0067] When a laser bird-repellent device detects bird activity and triggers bird-repellent measures, the laser bird-repellent devices in the same device group will act synchronously; when the laser bird-repellent devices in the same device group detect abnormal bird activity, an alarm will be sent to different device groups on the cloud server, notifying the different device groups to adjust the monitoring strategy to form a bird-repellent defense line.

[0068] Furthermore, device grouping and linkage is to divide multiple laser bird repellent devices into different groups according to geographical location, functional requirements or other standards; the devices in each group can communicate and collaborate with each other to share monitoring data and alarm information.

[0069] When one device detects bird activity and triggers bird repellent measures, other devices in the same group can also act synchronously to enhance the bird repellent effect; this linkage can be cross-group linkage, which means that laser bird repellent devices between different groups can also be linked to deal with a wider range of bird activities.

[0070] When devices in one group detect abnormal bird activity, they can send alerts to other related groups so that they can prepare in advance or adjust their monitoring strategies.

[0071] Device group linkage has the following features:

[0072] 1. Cross-group communication: Establish communication connections between devices in different groups to ensure the exchange of information and the transmission of commands.

[0073] 2. Intelligent scheduling: According to the activities of different groups of birds, intelligent scheduling of bird repellent measures for each group of equipment to achieve optimal resource allocation.

[0074] 3. Collaborative operations: In specific circumstances, such as large-scale bird migration, devices in different groups can work together to use laser strike mode to form a continuous line of defense against bird repellent.

[0075] 4. Data fusion: Integrate monitoring data from different groups to provide comprehensive bird activity analysis and reports.

[0076] Implemented over the local network, ensuring fast response and consistent operation.

[0077] In an exemplary embodiment, step 102 further includes: marking the locations where birds stay according to the bird images, and recording the appearance time and frequency of different birds.

[0078] Furthermore, the laser bird repellent device automatically captures images and videos of the repelling process. Once the capture is complete, the camera immediately sends an alarm message to the monitoring platform, including the captured image and video, and the bird's location is marked on the screen with numbers or graphics, allowing monitoring personnel to intuitively understand the bird's specific behavior and related identification and analysis data. These preset positions are adjusted and optimized based on actual use to ensure that they cover all important monitoring areas and adapt to environmental changes.

[0079] The present application can also establish a bird database and compare the identified birds with the data in the database to determine the species of the birds.

[0080] Laser bird repellent devices identify common birds such as sparrows, pigeons, and crows near substations and record their appearance times and frequencies. By analyzing this data, we can determine which birds are frequent visitors to the area and which are potentially destructive, allowing for more targeted bird repellent strategies.

[0081] The system also records the number of times each bird species is repelled, providing data support for evaluating the effectiveness of bird repelling. The system supports data storage, recording information such as the time, date, bird species, and number of repelling events for subsequent analysis and evaluation.

[0082] By analyzing the number of bird repellent events, this application can evaluate the activity patterns of different birds and the degree of impact on substation facilities, thereby adjusting the bird repellent strategy and improving the bird repellent effect.

[0083] Based on the same inventive concept, embodiments of the present application also provide a substation bird pest control device for implementing the aforementioned substation bird pest control method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more substation bird pest control device embodiments provided below can be found in the above-described limitations of the substation bird pest control method and will not be further elaborated here.

[0084] In an exemplary embodiment, a substation bird pest control device is provided, comprising:

[0085] The division module is used to divide multiple laser bird-repelling devices into multiple device groups according to geographical locations or functional requirements; the laser bird-repelling devices in the device groups communicate and cooperate with each other to share monitoring data and bird invasion alarm information.

[0086] The bird image acquisition module is used to acquire bird images and trigger a bird intrusion alarm when one of the device groups captures a bird entering the monitoring area.

[0087] The preprocessing module is used to preprocess the bird image to generate a preprocessed bird image.

[0088] The target bird recognition module is used to input the pre-processed bird image into the neural network model to identify the type of target bird in the bird image.

[0089] The linkage module is used to link multiple equipment groups to emit bird-repelling lasers corresponding to the types of target birds, and upload the bird-repelling measures of the laser bird-repelling devices in the equipment groups to the cloud server.

[0090] The scheduling module is used to schedule the bird-repelling measures of each device group based on the cloud server to form a bird-repelling defense line.

[0091] During actual operation, the substation bird pest control device provided by this application has demonstrated efficient and environmentally friendly bird-repelling capabilities after several days of operation, successfully reducing the incidence of bird pest incidents, and no harm to birds was found. It meets safety and environmental protection standards and basically achieves the functions and goals set by the project. It can effectively identify, monitor and alarm and drive away birds, and at the same time achieves safe and efficient interactive transmission of data, and the data also feeds back to the business, achieving the goal of business bringing data and data enhancing business value.

[0092] The substation bird pest control device provided in this application shows good stability, without serious failures or abnormal conditions, ensuring the normal operation of the monitoring platform; at the same time, it can effectively collect, process and display image and video data, and perform alarm processing in a timely manner, meeting the basic needs of monitoring and identification and expulsion.

[0093] The running effect is as follows Figure 3-Figure 4 As shown, it includes daily monitoring of bird population changes and monitoring of bird population changes at different time periods.

[0094] like Figure 3The following chart shows daily bird population changes at the substation from June 12th to 30th. The chart shows that since the system went online on June 12th, bird sightings have gradually decreased by 13% from June 12th to June 30th, with an average daily decrease of 0.7%. This indicates that the laser bird repellent system is gradually taking effect. Birds are beginning to avoid certain areas or change their flight paths after receiving the laser stimulation. Over time, the changes in bird populations will become more pronounced.

[0095] like Figure 4 As shown in the figure, the number of birds in different periods of time is monitored: the number of birds in the substation is counted on June 12, June 20 and June 30. Figure 4 The data shows that bird sightings peak at the substation between 6:00 AM and 9:00 AM and 4:00 PM and 7:00 PM, while bird sightings dip between 11:00 AM and 2:00 PM. Since the system went online, bird populations have shown a significant downward trend across different time periods, demonstrating that the laser bird repellent system is impacting bird behavior, forcing them to visit less frequently in the substation area.

[0096] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store substation bird pest control data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a substation bird pest control method is implemented.

[0097] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0098] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0099] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0100] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0101] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0102] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0103] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for preventing and controlling bird damage in a substation, characterized in that: The substation bird damage prevention method comprises: Divide multiple laser bird repellent devices into multiple device groups according to geographical location or functional requirements; the laser bird repellent devices in the device groups communicate and collaborate with each other to share monitoring data and bird intrusion alarm information; When a device group captures a bird entering the monitoring area, it obtains an image of the bird and triggers a bird intrusion alarm; preprocessing the bird image to generate a preprocessed bird image; Inputting the pre-processed bird image into a neural network model to identify the type of target bird in the bird image; Linking multiple device groups to emit bird-repelling lasers corresponding to the types of target birds, and uploading bird-repelling measures of the laser bird-repelling devices in the device groups to a cloud server; Based on the cloud server, bird-repelling measures for each of the device groups are dispatched to form a bird-repelling defense line.

2. The method for preventing and controlling bird damage in a substation according to claim 1, characterized in that: Triggering bird intrusion alarms, including: Determining whether the bird's stay time in the monitoring area exceeds a set time based on multiple consecutive frames of bird images; If so, a bird intrusion alarm is triggered and the bird intrusion alarm information is transmitted to the monitoring personnel; If not, the bird intrusion alarm is not triggered.

3. The method for preventing and controlling bird damage in a substation according to claim 1, characterized in that: Preprocessing the bird image to generate a preprocessed bird image specifically includes: The bird image is segmented and denoised to generate a pre-processed bird image; the pre-processed bird image can highlight the characteristics of the target bird while suppressing noise and interference from the environmental background.

4. The method for preventing and controlling bird damage in a substation according to claim 1, characterized in that: The pre-processed bird image is input into the neural network model, and the type of the target bird in the bird image is determined, specifically including: Analyzing the characteristic distribution of target birds of different scales in the preprocessed bird images using the neural network model; Based on the feature distribution, a multi-scale, adaptive anchor box strategy is adopted to optimize the neural network model and construct an enhanced model; The type of the target bird in the bird image is identified according to the enhanced model.

5. The method for preventing and controlling bird damage in a substation according to claim 1, characterized in that: The bird repellent measures of the laser bird repellent device in the equipment group are uploaded to the cloud server, specifically including: Based on the time synchronization mechanism, gating scheduling strategy and traffic filtering management solution of the TSN switch, the bird-repelling measures of the laser bird-repelling device are uploaded to the cloud server through the TSN switch to form a substation network architecture.

6. The method for preventing and controlling bird damage in a substation according to claim 1, characterized in that: Based on the cloud server, bird repellent measures are dispatched for each of the device groups to form a bird repellent defense line, specifically including: When a laser bird repellent device detects bird activity and triggers bird repellent measures, the laser bird repellent devices in the same device group will act synchronously; When the laser bird-repellent device in the same device group detects abnormal bird activity, an alarm is sent to different device groups on the cloud server, informing the different device groups to adjust the monitoring strategy to form a bird-repellent defense line.

7. The method for preventing and controlling bird damage in a substation according to claim 1, characterized in that: When a device group captures a bird entering the monitoring area, it obtains a bird image and triggers a bird intrusion alarm, which then includes: The bird's stay location is marked according to the bird image, and the appearance time and frequency of different birds are recorded.

8. A bird pest control device for a substation, characterized in that: The substation bird pest control device comprises: A division module is used to divide multiple laser bird repellent devices into multiple device groups according to geographical location or functional requirements; the laser bird repellent devices in the device group communicate and cooperate with each other to share monitoring data and bird intrusion alarm information; a bird image acquisition module, configured to acquire bird images and trigger a bird intrusion alarm when one of the device groups captures a bird entering the monitoring area; a preprocessing module, configured to preprocess the bird image to generate a preprocessed bird image; a target bird recognition module, configured to input the pre-processed bird image into a neural network model and identify the type of target bird in the bird image; A linkage module is used to link multiple device groups to emit bird-repelling lasers corresponding to the types of target birds, and upload the bird-repelling measures of the laser bird-repelling devices in the device groups to the cloud server; The scheduling module is used to schedule the bird-repelling measures of each device group based on the cloud server to form a bird-repelling defense line.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the substation bird pest control method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the substation bird damage control method according to any one of claims 1 to 7 is implemented.

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