Method and system for identifying hidden danger of power transmission line channel

Abstract

The invention provides a method and system for identifying hidden dangers of a power transmission line channel, and belongs to the technical field of power transmission line detection and artificial intelligence. The method comprises the steps of S100, obtaining a first power transmission line channel image of a current target area through a first resolution; s200, identifying and analyzing the first power transmission line channel image, and judging whether a potential hazard exists or not; when the potential hazard exists, obtaining a second power transmission line channel image of the current target area again through a second resolution ratio, taking the second power transmission line channel image as the input of the potential hazard identification model, and outputting a power transmission line channel potential hazard identification result of the current target area; the second resolution ratio is greater than the first resolution ratio. The system is used for executing the method. The technical scheme of the invention can reduce the data processing amount and improve the hidden danger identification efficiency of the power transmission line channel while ensuring the hidden danger identification accuracy of the power transmission line channel.

Description

Technical Field

[0001] The present invention belongs to the field of power transmission line detection and artificial intelligence technology, and in particular relates to a method and system for identifying hidden dangers in a power transmission line channel, a computer-readable storage medium for implementing the method, a computer program product, and an electronic device. Background Art

[0002] Transmission lines are an important part of the power grid. Affected by human and natural conditions, transmission lines often have various safety hazards. Among them, transmission line channel hazards are one of the most important hazards, which can be divided into external hazards and internal hazards. External hazards mainly include external foreign body hazards, such as bird nests, hanging foreign objects (kites, balloons, plastic bags, etc.), which may cause short circuits and cause abnormal conditions such as fires and thick smoke, leading to power system failures; internal hazards are reflected in internal signal flow failures such as hidden discharge, leakage, high voltage / low voltage instability, etc.

[0003] With the development of image processing technology and the popularization of high-resolution drones, external hidden dangers can be intelligently identified by target recognition technology based on high-resolution images collected by drone inspections, such as a method and system for identifying hidden dangers in transmission line channels based on high-resolution remote sensing images proposed in a Chinese invention patent (CN113033386B); as for internal hidden dangers, along with the transformation of smart grids, they can be predicted and processed by data mining and analysis of internal signal streams collected in real time by a combination of inexpensive multi-IoT sensors.

[0004] In actual applications, transmission lines are widely distributed, and the environments they pass through vary greatly. It takes a long time to complete a complete transmission line channel inspection, and the amount of image data collected to be processed is huge. However, the endurance and data processing capabilities of general drones are limited, resulting in low efficiency in identifying hidden dangers in the transmission line channels. How to reduce the amount of data processing while ensuring the accuracy of identifying hidden dangers in the transmission line channels, and thus improve the efficiency of identifying hidden dangers in the transmission line channels, is a technical problem currently faced by the identification of hidden dangers in the transmission line channels. Summary of the invention

[0005] The present invention proposes a method and system for identifying hidden dangers in a transmission line channel, a computer-readable storage medium, a computer program product and an electronic device for implementing the method, which are proposed to solve the above-mentioned technical problems.

[0006] In a first aspect of the present invention, a method for identifying hidden dangers in a transmission line channel is provided, the method comprising the following steps:

[0007] S100: Acquire a first power transmission line channel image of a current target area at a first resolution;

[0008] S200: Identify and analyze the first transmission line channel image to determine whether there are potential hidden dangers;

[0009] When there is a potential hidden danger, a second transmission line channel image of the current target area is acquired again with a second resolution, the second transmission line channel image is used as an input of the hidden danger identification model, and a transmission line channel hidden danger identification result of the current target area is output;

[0010] The second resolution is greater than the first resolution.

[0011] The step S200 identifies and analyzes the first transmission line channel image to determine whether there are potential hazards, specifically including:

[0012] Get the latest standard channel image corresponding to the current target area;

[0013] Calculating a difference score between the first transmission line channel image and the latest standard channel image;

[0014] When the difference score is greater than a preset difference value, it is determined that there is a potential hidden danger.

[0015] The standard channel image corresponding to each target area includes at least a first standard channel image and a second standard channel image.

[0016] When the result of the identification and analysis of the first transmission line channel image is that there is no potential hidden danger, taking the first transmission line channel image as a candidate standard channel image;

[0017] In practical applications, the method is implemented based on a drone and a ground image processing terminal that wirelessly communicates with the drone.

[0018] The drone has an image acquisition module and an image analysis module; the ground image processing terminal has the hidden danger identification model;

[0019] The image acquisition module acquires a first power transmission line channel image of the current target area at a first resolution;

[0020] The image analysis module identifies and analyzes the first transmission line channel image to determine whether there are potential hidden dangers;

[0021] When there is a potential hidden danger, the image acquisition module acquires the second power transmission line channel image of the current target area again with a second resolution, and sends the second power transmission line channel image to the ground image processing terminal;

[0022] The ground image processing terminal calls the hidden danger identification model to output the hidden danger identification result of the power transmission line channel in the current target area.

[0023] When the result of the image analysis module's identification and analysis of the first transmission line channel image is that there is no potential hidden danger, the next target area is taken as the current target area, and the process returns to step S100.

[0024] After the step S200 outputs the transmission line channel hidden danger identification result of the current target area, the next target area is taken as the current target area and the process returns to step S100.

[0025] In a second aspect of the present invention, in order to implement all or part of the steps described in the first aspect, a system for identifying hidden dangers in a transmission line channel is proposed, the system comprising an image acquisition module, an image analysis module, and a hidden danger identification model;

[0026] The image acquisition module is used to acquire a first transmission line channel image or a second transmission line channel image of each target area;

[0027] The image analysis module is used to identify and analyze the first power transmission line channel image with the first resolution acquired by the image acquisition module to determine whether there is a potential hidden danger;

[0028] When the image analysis module determines that there is a potential hidden danger, the image acquisition module obtains the second transmission line channel image of the current target area again at the second resolution, uses the second transmission line channel image as the input of the hidden danger identification model, and outputs the transmission line channel hidden danger identification result of the current target area;

[0029] The second resolution is greater than the first resolution.

[0030] Furthermore, the system also includes a standard channel image storage unit;

[0031] The standard channel image storage unit is used to store the standard channel image corresponding to each target area;

[0032] The image analysis module is used to identify and analyze the first power transmission line channel image with the first resolution acquired by the image acquisition module to determine whether there is a potential hidden danger, specifically including:

[0033] Get the latest standard channel image corresponding to the current target area;

[0034] Calculating a difference score between the first transmission line channel image and the latest standard channel image;

[0035] When the difference score is greater than a preset difference value, it is determined that there is a potential hidden danger.

[0036] When the result of the image analysis module's identification and analysis of the first transmission line channel image of the first resolution acquired by the image acquisition module is that there is no potential hidden danger, the first transmission line channel image of the first resolution acquired by the image acquisition module is updated and stored in the standard channel image storage unit as the standard channel image corresponding to the current target area.

[0037] The standard channel image corresponding to each target area includes at least a first standard channel image and a second standard channel image;

[0038] Among them, the first standard channel image is acquired through the image acquisition module, and the second standard channel image is acquired based on a cloud database.

[0039] Part or all of the steps of the method for identifying hidden dangers in a transmission line channel described in the first aspect can be automatically implemented through various forms of electronic devices and computer program instructions; the computer program instructions can be stored in storage media of different forms and loaded into computer electronic devices for execution.

[0040] Therefore, in the third aspect of the present invention, a computer-readable storage medium is also provided for storing computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the method for identifying hidden dangers in a power transmission line channel as described in the first aspect.

[0041] In a fourth aspect of the present invention, an electronic device is further proposed, comprising a processor and a memory, wherein the memory is used to store instructions, and the processor is used to call the instructions in the memory so that the electronic device executes the method for identifying hidden dangers in a transmission line channel as described in the first aspect above.

[0042] In a fifth aspect of the present invention, a computer program product is also proposed, the product comprising a computer program, and when the computer program is executed, the method for identifying hidden dangers in a transmission line channel described in the first aspect is implemented.

[0043] The technical solution of the present invention divides the transmission line channel into multiple target areas (intervals) in advance when identifying hidden dangers in the transmission line channel. For each target area (interval), a first transmission line channel image of the current target area is first obtained with a lower first resolution, and the first transmission line channel image is identified and analyzed to determine whether there are potential hidden dangers. When there are no potential hidden dangers, it directly jumps to the next target area (interval). When there are potential hidden dangers, the second transmission line channel image of the current target area is obtained again with a higher second resolution, and the second transmission line channel image is used as the input of the hidden danger identification model, and the hidden danger identification result of the transmission line channel in the current target area is output. Compared with the prior art that completely relies on the high-resolution image recognition mode throughout the whole process, it reduces the amount of data collection and processing, while not affecting the accuracy of hidden danger identification in the transmission line channel. Furthermore, judging whether there are potential hidden dangers specifically includes: obtaining the latest standard channel image corresponding to the current target area; calculating the difference score between the first transmission line channel image and the latest standard channel image; when the difference score is greater than a preset difference value, judging that there are potential hidden dangers; this process only requires a difference comparison process of low-resolution images, which only requires basic data processing capabilities and can be completed on a general image processing terminal (such as a drone terminal), which greatly improves the efficiency of identifying hidden dangers in the transmission line channel.

[0044] Further advantages of the present invention will be further reflected in detail in the specific embodiments section in conjunction with the drawings of the specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] 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 will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 This is a schematic diagram of the main flow of a method for identifying hidden dangers in a transmission line channel according to an embodiment of the present invention.

[0047] Figure 2 yes Figure 1 Schematic diagram of a first preferred embodiment of the method for identifying hidden dangers in a transmission line channel

[0048] Figure 3 yes Figure 1 Schematic diagram of a second preferred embodiment of the method for identifying hidden dangers in a transmission line channel

[0049] Figure 4This is a schematic diagram of the functional modules of a system for identifying hidden dangers in a transmission line channel according to an embodiment of the present invention.

[0050] Figure 5 A schematic diagram of a computer-readable storage medium and an electronic device for implementing a method for identifying hidden dangers in a transmission line channel according to the present invention DETAILED DESCRIPTION

[0051] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments that are the same as the present application. Instead, they are only examples of devices and methods that are the same as some aspects of the present application as detailed in the attached claims.

[0052] In the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program with a predetermined function, and works together with other related parts to achieve a predetermined goal, and can be implemented in whole or in part by using software, hardware (such as processing circuits or memories) or a combination thereof. Similarly, a processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be part of an overall module or unit that includes the function of the module or unit.

[0053] At the same time, in the specific implementation of this application, if user-related data is involved, when the embodiment of this application is applied to a specific product or technology, the user's permission or consent must be obtained, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0054] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0055] See also Figure 1 , Figure 1 The present invention is a schematic diagram of the main flow of a method for identifying hidden dangers in a transmission line channel according to an embodiment of the present invention.

[0056] Figure 1 The main steps of the method are divided into two major steps S100-S200:

[0057] S100: Acquire a first power transmission line channel image of a current target area at a first resolution;

[0058] S200: Identify and analyze the first transmission line channel image to determine whether there are potential hidden dangers;

[0059] When there is a potential hidden danger, a second transmission line channel image of the current target area is acquired again with a second resolution, the second transmission line channel image is used as an input of the hidden danger identification model, and a transmission line channel hidden danger identification result of the current target area is output.

[0060] The second resolution is greater than the first resolution.

[0061] Next, combine Figure 2 and Figure 3 , further introduces the specific implementation principles of each step of the method embodiment of the present application and the corresponding multiple preferred embodiments.

[0062] First, before implementing the technical solution of the present invention, it is necessary to determine the starting point-end point of the transmission line to be inspected or the specific inspection channel range, and then divide the transmission line channel to be inspected into multiple target areas (also called target sections), and for each target section, the channel hidden danger identification is performed by the method of the present invention. Referring to the above background technology introduction, the channel hidden danger identification targeted by the present invention is mainly external hidden danger identification.

[0063] From the review of the prior art, it can be seen that there are already a variety of mature transmission line external hidden danger identification models in the field, which mainly collect high-resolution images of the target section and use image recognition methods to identify whether there are hidden dangers in the current target section.

[0064] In addition to the patent documents mentioned in the background technology, similar related documents can also be found in:

[0065] [1] Tian Ersheng, Li Chunlei, Zhu Guodong, et al. Transmission line external damage risk identification algorithm based on YOLOv4[J]. Computer Systems and Applications, 2021, 30(07): 190-196.

[0066] [2] Ni Wei. Research on panoramic monitoring technology of transmission lines based on convolutional neural network[D]. North China Electric Power University (Beijing), 2023.

[0067] That is to say, on the basis of obtaining high-definition (high-resolution) video (image) data of each section, the corresponding hidden danger identification model (such as the aforementioned YOLOv4, convolutional neural network, etc.) can be used to identify the corresponding transmission line channel hidden dangers.

[0068] However, in actual application, the inventors found that the above prior art has at least the following problems when implemented:

[0069] (1) Although the recognition accuracy for a single sample image is high, the actual transmission line channels are widely distributed, which will generate a large number of multiple section images. If a large number of multiple section images are used as sample images to be processed, the above method uses the same processing method for each sample image, which will obviously greatly reduce the processing speed;

[0070] (2) The actual transmission line channel is a protective device, and there are daily intelligent inspection and manual inspection systems. The transmission line sections with hidden dangers are rare, and most transmission line sections are normal most of the time (no external hidden dangers). If the same image processing process is used for each section (each sample image), a large amount of unnecessary invalid data processing will be generated, which will waste data resources and extend the inspection time of the transmission line channel.

[0071] (3) Actual transmission line channel inspections are usually carried out using drones, but drones have limitations in terms of endurance and data processing capabilities (if a drone with high endurance and high processing capabilities is to be configured, the cost will increase).

[0072] Based on this, the inventor of the present application has improved the prior art and proposed the technical solution of the present application. The technical solution of the present application can be executed automatically in the form of computer program instructions without manual intervention.

[0073] Therefore, the following is an introduction in the form of a process language for computer program instructions.

[0074] Step 0: Determine the inspection channel range of the transmission line to be inspected and identified;

[0075] Step 1: Divide the transmission line channel to be inspected into N target areas as follows: 1 , Area 2 ,…Area N ; N ≥ 2;

[0076] Let i = 1;

[0077] step2: through the first resolution P L Get the target area i Image of the first transmission line channel Li ;

[0078] Step 3: Image the first transmission line channel image Li Conduct identification analysis to determine whether there are potential hidden dangers;

[0079] If there is a potential risk, the second resolution P HGet the second transmission line channel image Image of the current target area again Hi , the second transmission line channel image is used as the input of the hidden danger identification model, and the target area Area is output i The second resolution P H Greater than the first resolution P L ;

[0080] If there is no potential hidden danger, the first transmission line channel image Image Li As a candidate standard channel image;

[0081] i=i+1;

[0082] When i≤N, return to step 2; otherwise, end the process.

[0083] Figure 2 The preferred embodiment of the present invention generally describes the above computer process. Figure 2 Based on the above process, a first preferred embodiment of a method for identifying hidden dangers in a power transmission line channel of the present application is as follows:

[0084] S10: Determine the inspection channel range of the transmission line to be inspected and identified;

[0085] S20: Divide the transmission line channel to be inspected into multiple target areas;

[0086] S30: Acquire a first power transmission line channel image of the current target area at a first resolution;

[0087] S40: Determine whether there is a potential hidden danger in the first power transmission line channel image;

[0088] If yes, go to step S50; otherwise, go to step S80;

[0089] S50: acquiring a second transmission line channel image of the current target area again with a second resolution; S60: using the second transmission line channel image as an input of a hidden danger identification model;

[0090] S70: Outputting the transmission line channel hidden danger identification result of the current target area;

[0091] S80: taking the first power transmission line channel image as a candidate standard channel image;

[0092] S90: Taking the next target area as the current target area, and returning to step S30.

[0093] exist Figure 2In the figure, the process of identifying "potential hidden dangers" for a "current target area" is shown. Therefore, after the transmission line channel hidden danger identification result of the current target area is output in step S7, the identification process for the current "current target area" is ended.

[0094] However, in actual applications, it is necessary to identify all potential hazards for all “target processes”. Figure 2 Based on this, see Figure 3 The second preferred embodiment is as follows (for ease of comparison, Figure 2 and Figure 3 Step numbers are omitted):

[0095] S11: Determine the inspection channel range of the transmission line to be inspected and identified;

[0096] S21: Divide the transmission line channel to be inspected into multiple target areas;

[0097] S31: Acquire a first power transmission line channel image of a current target area at a first resolution;

[0098] S41: Determine whether there is a potential hidden danger in the first transmission line channel image;

[0099] If no, proceed to step S51; if yes, proceed to step S71;

[0100] S51: taking the first power transmission line channel image as a candidate standard channel image;

[0101] S61: Take the next target area as the current target area and return to step S31.

[0102] S71: acquiring a second transmission line channel image of the current target area again with a second resolution; S81: using the second transmission line channel image as an input of a hidden danger identification model;

[0103] S91: Output the transmission line channel hidden danger identification result of the current target area, and return to step S61.

[0104] As described above, the hidden danger identification model used in the embodiments of the present invention can be the hidden danger identification model disclosed in the prior art mentioned above, such as the YOLOv4, convolutional neural network and other models mentioned in the aforementioned documents. Of course, it can also be other known image recognition models. The present invention does not impose specific restrictions on this, because the improvement point of the present invention does not lie in the existing model, and no specific expansion is made on this.

[0105] It can be seen that compared with the prior art, the embodiment of the present application does not need to use a large number of multiple section images as sample images to be processed for the hidden danger identification model. Instead, for each target area (interval), a first transmission line channel image of the current target area is first obtained with a lower first resolution, and the first transmission line channel image is identified and analyzed to determine whether there are potential hidden dangers; when there are no potential hidden dangers, it directly jumps to the next target area (interval), and when there are potential hidden dangers, the second transmission line channel image of the current target area is obtained again with a higher second resolution, and the second transmission line channel image is used as the input of the hidden danger identification model, and the hidden danger identification result of the transmission line channel of the current target area is output. Compared with the prior art that completely relies on the high-resolution image recognition mode throughout the whole process, it reduces the amount of data collection and processing, while not affecting the accuracy of transmission line channel hidden danger identification.

[0106] Furthermore, in order to quickly identify whether there are potential hidden dangers, in the above embodiment, the first transmission line channel image is identified and analyzed to determine whether there are potential hidden dangers, specifically including:

[0107] Get the latest standard channel image corresponding to the current target area;

[0108] Calculating a difference score between the first transmission line channel image and the latest standard channel image;

[0109] When the difference score is greater than a preset difference value, it is determined that there is a potential hidden danger.

[0110] The standard channel image can be used to understand the channel image of the transmission line channel in the target area when everything is normal. In the standard channel image, there are no external hidden dangers in the transmission line channel (such as bird nests, hanging foreign objects, kites, balloons, plastic bags, etc.).

[0111] In the initial state, the standard channel image corresponding to each target area can be captured in advance. For example, after the manual inspection is completed, the standard channel image corresponding to each target area can be captured and stored in the corresponding standard channel image database.

[0112] Preferably, the standard channel image is not static but dynamically updated. When the result of the identification and analysis of the first transmission line channel image is that there is no potential hidden danger, the first transmission line channel image is updated as a candidate standard channel image to the standard channel image database.

[0113] In order to further improve the recognition accuracy, the standard channel image corresponding to each target area includes at least a first standard channel image and a second standard channel image;

[0114] The first standard channel image may be a standard channel image corresponding to each target area captured after the manual inspection is completed;

[0115] The second standard channel image may be the first transmission line channel image obtained when the result of identification and analysis of the first transmission line channel image is that there is no potential hidden danger.

[0116] On this basis, in order to ensure the possible errors in the potential hidden danger identification results and further ensure the integrity of the subsequent identification results, the first transmission line channel image is identified and analyzed to determine whether there are potential hidden dangers, specifically including:

[0117] Obtain the first standard channel image and the second standard channel image corresponding to the current target area;

[0118] Calculating a first difference score between the first power transmission line channel image and the first standard channel image, and a second difference score between the first power transmission line channel image and the second standard channel image;

[0119] When any of the following conditions is met, it is determined that there is a potential risk:

[0120] (1) The first difference score is higher than the preset difference value;

[0121] (2) the second difference score is higher than the preset difference value;

[0122] (3) The absolute value of the difference between the first difference score and the second difference score is greater than a preset threshold.

[0123] It can be seen that the above process of determining whether there are potential hidden dangers only requires basic image frame comparison, which does not require strong computing power and requires fewer computing resources. It can be implemented on a general image processing terminal (such as an ordinary drone terminal), consumes less energy, and reduces data energy consumption. At the same time, the judgment and comparison process fully considers possible misjudgments and errors, and ensures the accuracy of data judgment through a multi-angle and multi-benchmark approach.

[0124] In summary, the above process determines whether there are potential hidden dangers. It only requires a difference comparison process of low-resolution images, which only requires basic data processing capabilities. It can be completed on a general image processing terminal (such as a drone), which greatly improves the efficiency of identifying hidden dangers in the transmission line channel.

[0125] As a practical application, the above method of the present invention can be implemented based on a drone and a ground image processing terminal that wirelessly communicates with the drone.

[0126] At this time, the drone has an image acquisition module and an image analysis module; the ground image processing terminal has the hidden danger identification model;

[0127] The image acquisition module acquires a first power transmission line channel image of the current target area at a first resolution;

[0128] The image analysis module identifies and analyzes the first transmission line channel image to determine whether there are potential hidden dangers;

[0129] When there is a potential hidden danger, the image acquisition module acquires the second power transmission line channel image of the current target area again with a second resolution, and sends the second power transmission line channel image to the ground image processing terminal;

[0130] The ground image processing terminal calls the hidden danger identification model to output the hidden danger identification result of the power transmission line channel in the current target area.

[0131] The ground image processing terminal has a higher processing capability than the drone and can communicate with a cloud model library, which includes a variety of hidden danger identification models;

[0132] The ground image processing terminal calls at least two hidden danger identification models to output hidden danger identification results of the power transmission line channel in the current target area.

[0133] When the result of the image analysis module's identification and analysis of the first transmission line channel image is that there is no potential hidden danger, the next target area is taken as the current target area, and the method returns to step S100 to continue to execute all the steps of the method.

[0134] It can be seen that in the above embodiment, the drone can be regarded as a local edge model unit, which performs the basic potential hidden danger identification process locally without strong computing power support. When it is identified that there are no potential hidden dangers, there is no need to transmit the data back to the ground for further processing. It can go directly to the next target section for processing, which reduces the amount of data transmission and improves the autonomous processing capability. When the potential hidden danger is identified, it is sent to the ground terminal for further processing with the help of the cloud model, which reflects the advantages of cloud-edge combination.

[0135] Based on the above method embodiment, Figure 4 A schematic diagram of the functional modules of a system for identifying hidden dangers in a transmission line channel according to an embodiment of the present invention is provided.

[0136] exist Figure 4 In the figure, a system for identifying hidden dangers in a transmission line channel is shown, and the system includes an image acquisition module, an image analysis module, and a hidden danger identification model.

[0137] The image acquisition module is used to acquire a first transmission line channel image or a second transmission line channel image of each target area;

[0138] The image analysis module is used to identify and analyze the first power transmission line channel image with the first resolution acquired by the image acquisition module to determine whether there is a potential hidden danger;

[0139] When the image analysis module determines that there is a potential hidden danger, the image acquisition module obtains the second transmission line channel image of the current target area again at the second resolution, uses the second transmission line channel image as the input of the hidden danger identification model, and outputs the transmission line channel hidden danger identification result of the current target area;

[0140] The second resolution is greater than the first resolution.

[0141] The standard channel image storage unit is used to store the standard channel image corresponding to each target area;

[0142] The image analysis module is used to identify and analyze the first power transmission line channel image with the first resolution acquired by the image acquisition module to determine whether there is a potential hidden danger, specifically including:

[0143] Get the latest standard channel image corresponding to the current target area;

[0144] Calculating a difference score between the first transmission line channel image and the latest standard channel image;

[0145] When the difference score is greater than a preset difference value, it is determined that there is a potential hidden danger.

[0146] When the result of the image analysis module's identification and analysis of the first transmission line channel image of the first resolution acquired by the image acquisition module is that there is no potential hidden danger, the first transmission line channel image of the first resolution acquired by the image acquisition module is updated and stored in the standard channel image storage unit as the standard channel image corresponding to the current target area.

[0147] The standard channel image corresponding to each target area includes at least a first standard channel image and a second standard channel image;

[0148] Among them, the first standard channel image is acquired through the image acquisition module, and the second standard channel image is acquired based on a cloud database.

[0149] It is understandable that the relevant principles and advantages of the system embodiment are the same as the relevant principles and advantages of the method embodiment described in detail above, so they are not repeated here.

[0150] Although multiple embodiments are given above, each embodiment can constitute an independent technical solution and may contribute to the prior art and solve corresponding technical problems. However, it should be pointed out that different embodiments can be combined with each other without violating logic; at the same time, each embodiment can solve at least one technical problem, but it is not required that each individual embodiment solves multiple or all technical problems.

[0151] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. Figure 5 It is a schematic diagram of a computer-readable storage medium and an electronic device for implementing a method for identifying hidden dangers in a power transmission line channel described in the present invention.

[0152] Figure 5 The embodiment also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by an electronic device including a processor, the steps of a method for identifying hidden dangers in a power transmission line channel as described in the above embodiment are implemented.

[0153] For other technologies, principles, algorithms or models not elaborated in detail in this application, please refer to the prior art.

[0154] The foregoing has shown and described the method embodiments and system of the present invention, but it is understandable to those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for identifying hidden dangers in a transmission line channel, characterized in that: The method comprises the following steps: S100: Acquire a first power transmission line channel image of a current target area at a first resolution; S200: Identify and analyze the first transmission line channel image to determine whether there are potential hidden dangers; When there is a potential hidden danger, a second transmission line channel image of the current target area is acquired again with a second resolution, the second transmission line channel image is used as an input of the hidden danger identification model, and a transmission line channel hidden danger identification result of the current target area is output; The second resolution is greater than the first resolution.

2. A method for identifying hidden dangers in a power transmission line channel according to claim 1, characterized in that: Identify and analyze the first transmission line channel image to determine whether there are potential hidden dangers, specifically including: Get the latest standard channel image corresponding to the current target area; Calculating a difference score between the first transmission line channel image and the latest standard channel image; When the difference score is greater than a preset difference value, it is determined that there is a potential hidden danger.

3. A method for identifying hidden dangers in a power transmission line channel according to claim 1, characterized in that: When the result of the identification and analysis of the first power transmission line channel image is that there is no potential hidden danger, the first power transmission line channel image is used as a candidate standard channel image.

4. A method for identifying hidden dangers in a power transmission line channel according to claim 1, characterized in that: The method is implemented based on a UAV and a ground image processing terminal that wirelessly communicates with the UAV, wherein the UAV has an image acquisition module and an image analysis module; the ground image processing terminal has the hidden danger identification model; The image acquisition module acquires a first power transmission line channel image of the current target area at a first resolution; The image analysis module identifies and analyzes the first transmission line channel image to determine whether there are potential hidden dangers; When there is a potential hidden danger, the image acquisition module acquires the second power transmission line channel image of the current target area again with a second resolution, and sends the second power transmission line channel image to the ground image processing terminal; The ground image processing terminal calls the hidden danger identification model to output the hidden danger identification result of the power transmission line channel in the current target area.

5. A method for identifying hidden dangers in a power transmission line channel according to claim 4, characterized in that: When the result of the image analysis module's identification and analysis of the first transmission line channel image is that there is no potential hidden danger, the next target area is taken as the current target area, and the process returns to step S100.

6. A method for identifying hidden dangers in a power transmission line channel according to claim 4, characterized in that: After the step S200 outputs the transmission line channel hidden danger identification result of the current target area, the next target area is taken as the current target area and the process returns to step S100.

7. A system for identifying hidden dangers in power transmission line channels, the system comprising an image acquisition module, an image analysis module, and a hidden danger identification model, characterized in that: The image acquisition module is used to acquire a first transmission line channel image or a second transmission line channel image of each target area; The image analysis module is used to identify and analyze the first power transmission line channel image with the first resolution acquired by the image acquisition module to determine whether there is a potential hidden danger; When the image analysis module determines that there is a potential hidden danger, the image acquisition module obtains a second transmission line channel image of the current target area again at a second resolution, uses the second transmission line channel image as an input of the hidden danger identification model, and outputs a transmission line channel hidden danger identification result of the current target area; The second resolution is greater than the first resolution.

8. A system for identifying hidden dangers in power transmission line channels as claimed in claim 7, characterized in that: The system also includes a standard channel image storage unit; The standard channel image storage unit is used to store the standard channel image corresponding to each target area; The image analysis module is used to identify and analyze the first power transmission line channel image with the first resolution acquired by the image acquisition module to determine whether there is a potential hidden danger, specifically including: Get the latest standard channel image corresponding to the current target area; Calculating a difference score between the first transmission line channel image and the latest standard channel image; When the difference score is greater than a preset difference value, it is determined that there is a potential hidden danger.

9. A system for identifying hidden dangers in power transmission line channels as claimed in claim 8, characterized in that: When the result of the image analysis module's identification and analysis of the first transmission line channel image of the first resolution acquired by the image acquisition module is that there is no potential hidden danger, the first transmission line channel image of the first resolution acquired by the image acquisition module is updated and stored in the standard channel image storage unit as the standard channel image corresponding to the current target area.

10. A system for identifying hidden dangers in power transmission line channels as claimed in claim 8, characterized in that: The standard channel image corresponding to each target area includes at least a first standard channel image and a second standard channel image; Among them, the first standard channel image is acquired through the image acquisition module, and the second standard channel image is acquired based on a cloud database.

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