Device, method, system and terminal for quickly identifying overhigh tree barrier near line

Abstract

The invention relates to the technical field of forest hidden danger prediction and management of an overhead distribution line channel, and particularly provides a device, a method, a system and a terminal for quickly identifying an overhigh tree barrier near a line, and the device is characterized in that a single-chip microcomputer is connected with an infrared ray transmitting device and is used for controlling the infrared ray transmitting device to transmit infrared rays to an infrared ray receiving device; the single chip microcomputer is in signal connection with the infrared receiving device and is used for controlling the camera to shoot when the infrared receiving device cannot receive the infrared rays; the single chip microcomputer is in signal connection with the camera and is used for controlling the camera to shoot an image in a preset area; a pre-constructed tree obstacle recognition model is built in the single-chip microcomputer and used for recognizing whether tree obstacles exist in the images, shot by the camera, in the preset area or not. The problems that the timeliness is poor, the cost is high, and the unmanned aerial vehicle cannot work in dense fog, rain and snow weather during routing inspection are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of prediction and management of hidden dangers of trees in overhead power distribution line passages, and in particular relates to a device, method, system and terminal for quickly identifying excessively high tree obstacles near a line. Background Art

[0002] Distribution lines are an important part of the power grid. Their main task is to transmit and distribute electrical energy to the target point. When a distribution line fails, it will have a serious impact on the power supply. In the actual environment, trees on the corridors of distribution lines pose a great safety hazard. High-speed growing branches may touch the high-voltage wires, forming tree barriers, thereby increasing the insulation failure and short circuit risks of the wires, and seriously threatening the safe operation of the power system. If the trees are not pruned and maintained in time, overly tall trees may collapse in bad weather or emergencies, directly affecting the stability and reliability of the distribution lines. In order to ensure the safe operation of the distribution lines, it is particularly important to prune and clean the trees regularly. However, because there are many trees under the lines and their growth rates are different, the current method of relying on patrol personnel to manually discover tree barriers is inefficient. It is difficult for patrol personnel to find all tree barriers in the first place and it is difficult to respond to emergencies in time.

[0003] In order to solve the problem of tree obstacle detection, traditional tree obstacle detection mostly adopts manual inspection. Since tree obstacles are difficult to measure accurately, manual inspection is difficult to find and obtain tree obstacle information, and it is very easy to pose a threat to personal safety. Therefore, there are technical solutions for using drones to inspect distribution lines in the existing technology. For example, drones equipped with laser radars are used to transmit laser signals to distribution lines and the ground to obtain a large amount of laser point cloud data, which is received by photoelectric detectors. After the data is processed, a three-dimensional model of the distribution line, tower pole and surrounding environment can be obtained to assist inspection personnel in making decisions. The disadvantage of laser radar as a data collection sensor is that it is expensive, cannot work all day, and cannot work in dense fog, rain or snow. Summary of the invention

[0004] In view of the problems in the prior art of using drone's laser radar to inspect distribution lines and find tree obstacles, the cost is high, it cannot work all day, and it cannot work in dense fog, rain or snow. The present invention provides a device for quickly identifying tree obstacles that are too high near the line to solve the above technical problems.

[0005] In a first aspect, the present invention provides a device for quickly identifying excessively high tree obstacles near a line, comprising: The single chip microcomputer is connected to the infrared ray transmitting device and is used to control the infrared ray transmitting device to transmit infrared rays to the infrared ray receiving device; The single chip microcomputer is connected to the infrared receiving device signal, and is used to control the camera to shoot when the infrared receiving device cannot receive infrared rays; The single chip microcomputer is connected to the camera signal to control the camera to capture images within a preset area; The microcontroller has a pre-built tree obstacle recognition model built in, which is used to identify whether there are tree obstacles in the image within the preset area captured by the camera.

[0006] Furthermore, the infrared emitting device is arranged at the upper end of the first tension rod, and the infrared receiving device is arranged at the upper end of the second tension rod; The infrared emitting device and the infrared receiving device both include: a bracket, a solar panel and a battery storage unit, wherein the solar panel is arranged on the top of the bracket and connected to the battery storage unit; The infrared emitting device further comprises an infrared transmitter, and the infrared receiving device further comprises an infrared receiver; The height of the infrared transmitter on the first tension rod is consistent with the height of the infrared receiver on the second tension rod, and the emitting surface of the infrared transmitter is opposite to the receiving surface of the infrared receiver.

[0007] Furthermore, it also includes: an audible and visual alarm light; The single chip microcomputer is connected with the sound and light alarm light signal, and is used to give a sound and light alarm when a tree obstacle is identified in a preset area.

[0008] In a second aspect, the present invention provides a method for quickly identifying excessively high tree obstacles near a line, comprising: The infrared transmitter transmits an infrared signal to the infrared receiver; When the single chip microcomputer detects that the infrared signal is interrupted, the camera takes a picture of the preset area to obtain an image of the preset area; The tree obstacle recognition model pre-built in the single chip microcomputer recognizes the preset area image. If a tree obstacle is recognized in the preset area image, an audible and visual alarm is issued.

[0009] Furthermore, the method of constructing a tree obstacle recognition model includes: Obtain historical tree obstacle images in fog, rain, snow, clear weather, and spring, summer, autumn, and winter environments; Based on historical tree barrier images, tree barrier features are selected and labeled to obtain a sample set; Use the sample set to train YOLOv5 and obtain the tree obstacle recognition model.

[0010] Furthermore, based on the historical tree barrier images, tree barrier features are selected and labeled to obtain a sample set, including: Select the morphological features, color features, position features, texture features, environmental features and weather features of the tree barriers, wherein the morphological features include the morphology of the trunk and the crown, the color features include the green, yellow, brown and red of the leaves and the brown, gray and black of the trunk, the position features include the relative position of the tree barriers relative to the background, the texture features include the surface texture of the leaves and the trunk, the environmental features include the shadow and reflection of the tree barriers, the weather features include the clear outline of the tree barriers in sunny weather, the outline of the tree barriers covered by rain in rainy weather, the outline and color of the tree barriers covered by snow in snowy weather, and the outline of the tree barriers covered by fog in foggy weather; The morphological features, color features, position features, texture features, environmental features and weather features of the tree barriers are annotated to obtain a sample set.

[0011] In a third aspect, the present invention provides a system for quickly identifying excessively high tree obstacles near a line, comprising: An infrared signal transmitting module transmits an infrared signal to an infrared receiver via an infrared transmitter; Preset area image shooting module, when the single chip microcomputer detects that the infrared signal is interrupted, the camera takes a picture of the preset area to obtain the preset area image; The tree obstacle recognition module recognizes the preset area image through the tree obstacle recognition model pre-built in the single-chip microcomputer. If a tree obstacle is recognized in the preset area image, an audible and visual alarm will be issued.

[0012] Furthermore, it also includes: a model building module, including: Image acquisition unit, which acquires historical tree barrier images under dense fog, rain, snow, clear weather, and spring, summer, autumn, and winter conditions; The sample set construction unit selects tree barrier features by using historical tree barrier pictures and labels the tree barrier features to obtain a sample set; The model training unit is used to train YOLOv5 using the sample set to obtain a tree obstacle recognition model.

[0013] Furthermore, the sample set construction unit includes: A feature selection module selects the morphological features, color features, position features, texture features, environmental features and weather features of the tree barrier, wherein the morphological features include the morphology of the trunk and the crown, the color features include the green, yellow, brown and red of the leaves and the brown, gray and black of the trunk, the position features include the relative position of the tree barrier with respect to the background, the texture features include the surface texture of the leaves and the trunk, the environmental features include the shadow and reflection of the tree barrier, the weather features include the clear outline of the tree barrier in sunny weather, the outline of the tree barrier covered by rain in rainy weather, the outline and color of the tree barrier covered by snow in snowy weather, and the outline of the tree barrier covered by fog in foggy weather; The feature annotation module obtains a sample set by annotating the morphological features, color features, position features, texture features, environmental features and weather features of the tree barriers.

[0014] In a fourth aspect, a terminal is provided, including: processor, memory, wherein: The memory is used to store computer programs. The processor is used to call and run the computer program from the memory, so that the terminal executes the above-mentioned terminal method.

[0015] In a fifth aspect, a computer storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the computer-readable storage medium is run on a computer, the computer executes the methods described in the above aspects.

[0016] The beneficial effect of the present invention is that the device for quickly identifying over-high tree obstacles near the line provided by the present invention determines whether there are tree obstacles in the image of the preset area taken by the camera when the infrared signal between the infrared transmitting device and the infrared receiving device is disconnected, which greatly improves the real-time performance, can work all day, and is not affected by dense fog, rain and snow. Not only does it reduce the inspection cost, but it also reduces the manual workload, realizes fully automatic identification of tree obstacles, and solves the problems of poor timeliness, high cost and inability to work in dense fog, rain and snow during drone inspection.

[0017] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 is a schematic block diagram of an apparatus according to an embodiment of the present invention.

[0020] Figure 2 is a schematic flow chart of a method according to an embodiment of the present invention.

[0021] Figure 3 The figure is a schematic flow chart of a method for constructing a tree obstacle recognition model according to an embodiment of the present invention.

[0022] Figure 4 is a schematic block diagram of a system according to an embodiment of the present invention.

[0023] Figure 5A schematic diagram of the structure of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0026] The technical solution of the present invention is a device for quickly identifying tree obstacles that are too high near the line, such as Figure 1 As shown, it includes: an infrared transmitting device, an infrared receiving device, a camera and a single chip microcomputer. The single chip microcomputer is connected to the infrared transmitting device to control the infrared transmitting device to transmit infrared rays to the infrared receiving device; the single chip microcomputer is connected to the infrared receiving device signal to control the camera to shoot when the infrared receiving device cannot receive infrared rays; the single chip microcomputer is connected to the camera signal to control the camera to shoot images in a preset area; the single chip microcomputer has a pre-built tree obstacle recognition model built in, which is used to identify whether there are tree obstacles in the images in the preset area shot by the camera.

[0027] Optionally, as an embodiment of the present invention, the infrared emitting device is arranged at the upper end of the first tension rod, and the infrared receiving device is arranged at the upper end of the second tension rod; the infrared emitting device and the infrared receiving device both include: a bracket, a solar panel and a battery storage unit, the solar panel is arranged on the top of the bracket and connected to the battery storage unit; the infrared emitting device also includes an infrared transmitter, and the infrared receiving device also includes an infrared receiver; the height of the infrared transmitter on the first tension rod is consistent with the height of the infrared receiver on the second tension rod, and the emitting surface of the infrared transmitter is placed opposite to the receiving surface of the infrared receiver.

[0028] Optionally, as an embodiment of the present invention, it further comprises: an audible and visual alarm lamp. The single chip microcomputer is connected to the audible and visual alarm lamp signal, and is used to generate an audible and visual alarm when a tree obstacle is identified in a preset area.

[0029] The method for quickly identifying excessively high tree obstacles near a line provided by the embodiment of the present invention is executed by a computer device, and correspondingly, the system for quickly identifying excessively high tree obstacles near a line runs in the computer device.

[0030] To facilitate understanding of the present invention, the following is a further description of the method for quickly identifying excessively high tree barriers near a line provided by the present invention based on the principle of the method for quickly identifying excessively high tree barriers near a line in the present invention and the process of identifying excessively high tree barriers near a line in an embodiment.

[0031] Specifically, Figure 2 As shown, the method for quickly identifying excessively high tree obstacles near a line includes: S1. The infrared transmitter transmits an infrared signal to the infrared receiver.

[0032] S2. When the single chip microcomputer detects that the infrared signal is interrupted, the camera takes a picture of the preset area to obtain an image of the preset area.

[0033] In some embodiments, Figure 3 As shown, it also includes a method for constructing a tree obstacle recognition model, which specifically includes steps Q1-Q3.

[0034] Q1. Obtain historical tree barrier images in fog, rain, snow, clear weather, and spring, summer, autumn, and winter.

[0035] Specifically, these pictures can be taken on-site or obtained from an existing database.

[0036] Q2. Based on historical tree barrier images, select tree barrier features and label them to obtain a sample set.

[0037] The morphological features, color features, position features, texture features, environmental features and weather features of tree barriers are selected. The morphological features include the morphology of the trunk and crown, the color features include the green, yellow, brown and red of the leaves and the brown, gray and black of the trunk, the position features include the relative position of the tree barrier relative to the background, the texture features include the surface texture of the leaves and trunk, the environmental features include the shadow and reflection of the tree barrier, and the weather features include the clear outline of the tree barrier in sunny weather, the outline of the tree barrier covered by rain in rainy weather, the outline and color of the tree barrier covered by snow in snowy weather, and the outline of the tree barrier covered by fog in foggy weather. The morphological features, color features, position features, texture features, environmental features and weather features of the tree barrier are annotated to obtain a sample set.

[0038] Specifically, you can use a labeling tool (such as LabelImg) to label the tree obstacles in the image.

[0039] Q3. Use the sample set to train YOLOv5 to obtain a tree obstacle recognition model.

[0040] Specifically, select the YOLOv5 model as the target detection model and configure it. First, install the dependencies required by the YOLOv5 model. Make sure Python and related deep learning frameworks (such as PyTorch) are installed.

[0041] Configuring the model parameters of YOLOv5 mainly includes the following aspects: Model architecture: Select the appropriate YOLOv5 version (such as YOLOv5s). Dataset path: Set the path of the training set and validation set. Category name: Specify the category name for tree obstacle recognition, such as tree_obstruction.

[0042] Then divide the labeled sample set into training set and validation set, and perform necessary data preprocessing, such as adjusting image size and normalization. Then use the training script of YOLOv5 to train the model. The training process uses the data of the training set for learning, and uses the data of the validation set for model performance evaluation. The best weight file of the model is saved during the training process. After the training is completed, the model is evaluated using the validation set. The evaluation indicators include mean average precision (mAP), precision, recall, etc. These indicators can be used to understand the performance of the model under different conditions. Optimize the model based on the evaluation results. For example, you can adjust the model's hyperparameters (such as learning rate, batch size, etc.), increase training data, or perform transfer learning to improve the model's recognition accuracy and generalization ability. Export the trained model to a format suitable for deployment, such as ONNX or TensorRT format. These formats are suitable for model deployment on embedded devices or mobile devices. Integrate the exported model into the actual tree obstacle detection system.

[0043] S3. The tree obstacle recognition model pre-built in the single chip recognizes the preset area image. If a tree obstacle is recognized in the preset area image, an audible and visual alarm is issued.

[0044] In some embodiments, the system for quickly identifying over-high tree obstacles near a route may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the system for quickly identifying over-high tree obstacles near a route may be stored in a memory of a computer device and executed by at least one processor to perform (see Figure 2 Description) A function that allows you to quickly identify tree obstacles that are too high near the line.

[0045] In this embodiment, the system for quickly identifying high tree obstacles near a line can be divided into multiple functional modules according to the functions it performs, such as Figure 3As shown. The functional modules of the system 300 may include: a basic construction module 310, an attribute definition module 320, a data sharing module 330 and an order processing module 340. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0046] An infrared signal transmitting module transmits an infrared signal to an infrared receiver via an infrared transmitter; Preset area image shooting module, when the single chip microcomputer detects that the infrared signal is interrupted, the camera takes a picture of the preset area to obtain the preset area image; The tree obstacle recognition module recognizes the preset area image through the tree obstacle recognition model pre-built in the single-chip microcomputer. If a tree obstacle is recognized in the preset area image, an audible and visual alarm will be issued.

[0047] Optionally, as an embodiment of the present invention, it further includes: a model building module, including: Image acquisition unit, which acquires historical tree barrier images under dense fog, rain, snow, clear weather, and spring, summer, autumn, and winter conditions; The sample set construction unit selects tree barrier features by using historical tree barrier pictures and labels the tree barrier features to obtain a sample set; The model training unit is used to train YOLOv5 using the sample set to obtain a tree obstacle recognition model.

[0048] Optionally, as an embodiment of the present invention, the sample set construction unit includes: A feature selection module selects the morphological features, color features, position features, texture features, environmental features and weather features of the tree barrier, wherein the morphological features include the morphology of the trunk and the crown, the color features include the green, yellow, brown and red of the leaves and the brown, gray and black of the trunk, the position features include the relative position of the tree barrier with respect to the background, the texture features include the surface texture of the leaves and the trunk, the environmental features include the shadow and reflection of the tree barrier, the weather features include the clear outline of the tree barrier in sunny weather, the outline of the tree barrier covered by rain in rainy weather, the outline and color of the tree barrier covered by snow in snowy weather, and the outline of the tree barrier covered by fog in foggy weather; The feature annotation module obtains a sample set by annotating the morphological features, color features, position features, texture features, environmental features and weather features of the tree barriers.

[0049] Figure 4 The present invention is a schematic diagram of the structure of a terminal 400 provided in an embodiment of the present invention. The terminal 400 can be used to execute the method for quickly identifying excessively high tree obstacles near a line provided in an embodiment of the present invention.

[0050] The terminal 400 may include: a processor 410, a memory 420 and a communication unit 430. These components communicate via one or more buses. Those skilled in the art will appreciate that the server structure shown in the figure does not limit the present invention, and it may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0051] The memory 420 can be used to store the execution instructions of the processor 410, and the memory 420 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. When the execution instructions in the memory 420 are executed by the processor 410, the terminal 400 can perform some or all of the steps in the following method embodiments.

[0052] The processor 410 is the control center of the storage terminal, and uses various interfaces and lines to connect various parts of the entire electronic terminal. It runs or executes software programs and / or modules stored in the memory 420, and calls data stored in the memory to perform various functions of the electronic terminal and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 410 can include only a central processing unit (CPU). In the embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0053] The communication unit 430 is used to establish a communication channel so that the storage terminal can communicate with other terminals, receive user data sent by other terminals or send user data to other terminals.

[0054] Therefore, the present invention determines whether there is a tree obstacle in the image of the preset area captured by the camera when the infrared signal between the infrared transmitting device and the infrared receiving device is disconnected, which greatly improves the real-time performance, can work all day, and is not affected by dense fog, rain and snow. Not only does it reduce the inspection cost, but it also reduces the manual workload, realizes the full-automatic identification of tree obstacles, solves the problems of poor timeliness, high cost and inability to work in dense fog, rain and snow during drone inspection, and the technical effects that can be achieved by this embodiment can be found in the above description, which will not be repeated here.

[0055] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present invention, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes, including several instructions for enabling a computer terminal (which can be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0056] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

[0057] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, which can be electrical, mechanical or other forms.

[0058] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0059] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0060] Although the present invention has been described in detail by referring to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, and all of these shall be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A device for quickly identifying tree obstacles that are too high near a line, characterized in that: include: Infrared transmitting device, infrared receiving device, camera and single chip microcomputer; The single chip microcomputer is connected to the infrared ray transmitting device and is used to control the infrared ray transmitting device to transmit infrared rays to the infrared ray receiving device; The single chip microcomputer is connected to the infrared receiving device signal, and is used to control the camera to shoot when the infrared receiving device cannot receive infrared rays; The single chip microcomputer is connected to the camera signal to control the camera to capture images within a preset area; The microcontroller has a pre-built tree obstacle recognition model built in, which is used to identify whether there are tree obstacles in the image within the preset area captured by the camera.

2. The device according to claim 1, characterized in that The infrared emitting device is arranged at the upper end of the first tension rod, and the infrared receiving device is arranged at the upper end of the second tension rod; The infrared transmitting device and the infrared receiving device both include: a bracket, a solar panel and a battery storage unit, wherein the solar panel is arranged on the top of the bracket and connected to the battery storage unit; The infrared emitting device further comprises an infrared transmitter, and the infrared receiving device further comprises an infrared receiver; The height of the infrared transmitter on the first tension rod is consistent with the height of the infrared receiver on the second tension rod, and the emitting surface of the infrared transmitter is opposite to the receiving surface of the infrared receiver.

3. The device according to claim 1, characterized in that Also includes: Sound and light warning lights; The single chip microcomputer is connected with the sound and light alarm light signal, and is used to issue a sound and light alarm when a tree obstacle is identified in a preset area.

4. A method for quickly identifying tree obstacles that are too high near a line, characterized in that: include: The infrared transmitter transmits an infrared signal to the infrared receiver; When the single chip microcomputer detects that the infrared signal is interrupted, the camera takes a picture of the preset area to obtain an image of the preset area; The tree obstacle recognition model pre-built in the single chip recognizes the preset area image. If a tree obstacle is recognized in the preset area image, an audible and visual alarm is issued.

5. The method according to claim 4, characterized in that Methods for building a tree obstacle recognition model include: Obtain historical tree obstacle images in fog, rain, snow, clear weather, and spring, summer, autumn, and winter environments; Based on historical tree barrier images, tree barrier features are selected and labeled to obtain a sample set; Use the sample set to train YOLOv5 and obtain the tree obstacle recognition model.

6. The method according to claim 5, characterized in that Based on historical tree barrier images, tree barrier features are selected and labeled to obtain a sample set, including: Select the morphological features, color features, position features, texture features, environmental features and weather features of the tree barriers, wherein the morphological features include the morphology of the trunk and the crown, the color features include the green, yellow, brown and red of the leaves and the brown, gray and black of the trunk, the position features include the relative position of the tree barriers relative to the background, the texture features include the surface texture of the leaves and the trunk, the environmental features include the shadow and reflection of the tree barriers, the weather features include the clear outline of the tree barriers in sunny weather, the outline of the tree barriers covered by rain in rainy weather, the outline and color of the tree barriers covered by snow in snowy weather, and the outline of the tree barriers covered by fog in foggy weather; The morphological features, color features, position features, texture features, environmental features and weather features of the tree barriers are annotated to obtain a sample set.

7. A system for quickly identifying high tree obstacles near a line, characterized in that: include: An infrared signal transmitting module transmits an infrared signal to an infrared receiver via an infrared transmitter; Preset area image shooting module, when the single chip microcomputer detects that the infrared signal is interrupted, the camera takes a picture of the preset area to obtain the preset area image; The tree obstacle recognition module recognizes the preset area image through the tree obstacle recognition model pre-built in the single-chip microcomputer. If a tree obstacle is recognized in the preset area image, an audible and visual alarm will be issued.

8. The system according to claim 7, characterized in that Also includes: Model building modules, including: Image acquisition unit, which acquires historical tree barrier images under dense fog, rain, snow, clear weather, and spring, summer, autumn, and winter conditions; The sample set construction unit selects tree barrier features by using historical tree barrier pictures and labels the tree barrier features to obtain a sample set; The model training unit is used to train YOLOv5 using the sample set to obtain a tree obstacle recognition model.

9. The system according to claim 8, characterized in that The sample set building blocks include: A feature selection module selects the morphological features, color features, position features, texture features, environmental features and weather features of the tree barrier, wherein the morphological features include the morphology of the trunk and the crown, the color features include the green, yellow, brown and red of the leaves and the brown, gray and black of the trunk, the position features include the relative position of the tree barrier with respect to the background, the texture features include the surface texture of the leaves and the trunk, the environmental features include the shadow and reflection of the tree barrier, the weather features include the clear outline of the tree barrier in sunny weather, the outline of the tree barrier covered by rain in rainy weather, the outline and color of the tree barrier covered by snow in snowy weather, and the outline of the tree barrier covered by fog in foggy weather; The feature annotation module obtains a sample set by annotating the morphological features, color features, position features, texture features, environmental features and weather features of the tree barriers.

10. A terminal, characterized in that: include: A memory for storing a program for quickly identifying high tree obstacles near a line; A processor is used to implement the steps of the method for quickly identifying too high tree obstacles near a line as described in any one of claims 4 to 6 when executing the program for quickly identifying too high tree obstacles near a line.

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