Power transmission line defect identification method and system

Abstract

The invention provides a power transmission line defect identification method and system, and the method comprises the steps: receiving a target power transmission line inputted by a user in real time when a preset time is reached, and collecting a detection video corresponding to the target power transmission line in real time through a preset unmanned plane based on a preset rule; performing real-time analysis processing on the detection video to extract a feature region and a line size corresponding to the target power transmission line in real time; and creating a target line three-dimensional model corresponding to the target power transmission line in real time according to the feature region and the line size through a preset three-dimensional program, and performing full scanning on the target line three-dimensional model to judge whether the surface of the target power transmission line has defects or not in real time. According to the method, the process of manual operation can be omitted, meanwhile, whether defects exist or not can be objectively and accurately judged, and the recognition efficiency is greatly improved correspondingly.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission detection, and in particular to a method and system for identifying power transmission line defects. Background Art

[0002] With the advancement of productivity and the rapid development of the times, people's demand for electricity is increasing. Among them, the existing electricity needs to be transmitted through transmission lines before it can be provided to various regions. Therefore, the quality of the transmission lines can directly affect whether the electricity can be transmitted normally.

[0003] Among them, existing transmission lines need to be regularly maintained and inspected during daily use to determine whether there are obvious defects such as damage and cracks on the surface of the transmission lines.

[0004] Furthermore, in the process of maintenance and inspection of transmission lines in the existing technology, most of the corresponding inspections are still carried out by staff. Specifically, the staff will collect images of the transmission lines in real time, and then determine whether defects occur through subjective judgment by the staff. However, this defect identification method is easily affected by human subjective factors, and is prone to missed detections and false detections, which correspondingly reduces the detection efficiency of the transmission lines. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a method and system for identifying defects in power transmission lines, so as to solve the problem that the defect identification method used in the prior art is easily affected by human subjective factors, resulting in missed detection and false detection.

[0006] The first aspect of the embodiment of the present invention proposes:

[0007] A method for identifying defects in a transmission line, wherein the method comprises:

[0008] When the preset time arrives, the target transmission line input by the user is received in real time, and a detection video corresponding to the target transmission line is collected in real time by a preset drone based on preset rules;

[0009] Performing real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time;

[0010] A preset three-dimensional program is used to create a target line three-dimensional model corresponding to the target transmission line in real time according to the characteristic area and the line size, and the target line three-dimensional model is fully scanned to determine in real time whether the surface of the target transmission line has defects.

[0011] The beneficial effect of the present invention is that by determining the target transmission line, the corresponding processing object can be clearly identified. Based on this, in order to improve the efficiency of defect identification, the detection video corresponding to the current target transmission line will be collected in real time according to the pre-set rules and the existing drone. Based on this, the characteristic area and line size corresponding to the current target transmission line can be extracted in real time, and an adapted target line three-dimensional model can be finally created. At the same time, it can objectively and accurately judge whether the surface of the current target transmission line has defects, thereby eliminating the manual operation process and greatly improving the identification efficiency.

[0012] Furthermore, the step of collecting the detection video corresponding to the target transmission line in real time by a preset drone based on a preset rule includes:

[0013] When the target transmission line is detected in real time, a starting point and an ending point corresponding to the target transmission line are determined in real time;

[0014] Determine in real time a target flight path corresponding to the preset UAV within the range between the starting point and the end point;

[0015] The detection video is collected in real time by the preset UAV based on the target flight path, and the target flight path is unique.

[0016] Furthermore, the step of determining in real time the target flight path corresponding to the preset drone includes:

[0017] When the starting point and the ending point are obtained, an initial detection range corresponding to the preset drone is determined in real time, and an effective detection range corresponding to the target power transmission line displayed in the initial detection range is detected in real time;

[0018] Calculating in real time a target ratio between the effective detection range and the initial detection range, and proportionally reducing the initial detection range according to the target ratio to generate in real time a target detection range adapted to the target transmission line;

[0019] The target flight path of the preset UAV is correspondingly determined based on the target detection range.

[0020] Furthermore, the step of determining the target flight path of the preset UAV based on the target detection range includes:

[0021] When the target detection range is determined, controlling the preset drone to fly a first path corresponding to the target detection range in a direction from the starting point to the end point;

[0022] When the preset drone is detected in real time to have arrived at the end point, the preset drone is controlled to fly a corresponding second path based on the target detection range in a direction from the end point to the start point, where the first path corresponds to the second path;

[0023] The first path and the second path are integrated to generate the target flight path.

[0024] Furthermore, the step of performing real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time includes:

[0025] When the detection video is acquired in real time, a corresponding detection image is randomly generated in the detection video, and a target diameter corresponding to the target transmission line is determined according to the detection image;

[0026] detecting in real time the flight speed and flight time corresponding to the preset UAV, and calculating the target length of the target transmission line according to the flight speed and the flight time;

[0027] The target diameter and the target length are integrated to generate the line size.

[0028] Furthermore, the step of performing real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time also includes:

[0029] When the detection video is acquired in real time, an initial time axis corresponding to the detection video is created in real time, wherein the initial time axis includes a plurality of time nodes;

[0030] Adding a corresponding target identifier to each of the time nodes, and extracting image frames corresponding to each of the time nodes from the detection video according to the target identifier;

[0031] The corresponding feature area appearing in the target power transmission line is extracted in real time according to each image frame, and each target identifier is unique.

[0032] Furthermore, the step of extracting the corresponding feature area appearing in the target power transmission line in real time according to each image frame includes:

[0033] When each image frame is acquired in real time, a number of corresponding pixels contained in the image frame are detected in real time, and it is determined in real time whether there is a pixel value of the pixel point higher than a preset pixel threshold;

[0034] If it is determined in real time that the pixel value of a pixel point is higher than the preset pixel threshold, the pixel point corresponding to the current pixel value higher than the preset pixel threshold is set as the target pixel point, and the target area enclosed by each target pixel point is detected in real time;

[0035] The target area is set to correspond to the characteristic area of ​​the target power transmission line.

[0036] The second aspect of the embodiment of the present invention proposes:

[0037] A transmission line defect identification system, wherein the system comprises:

[0038] The acquisition module is used to receive the target transmission line input by the user in real time when the preset time arrives, and to collect the detection video corresponding to the target transmission line in real time through a preset drone based on preset rules;

[0039] An analysis module is used to perform real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time;

[0040] A judgment module is used to create a target line three-dimensional model corresponding to the target transmission line in real time according to the characteristic area and the line size through a preset three-dimensional program, and to perform a full scan of the target line three-dimensional model to determine in real time whether the surface of the target transmission line has defects.

[0041] Furthermore, the acquisition module is specifically used to:

[0042] When the target transmission line is detected in real time, a starting point and an ending point corresponding to the target transmission line are determined in real time;

[0043] Determine in real time a target flight path corresponding to the preset UAV within the range between the starting point and the end point;

[0044] The detection video is collected in real time by the preset UAV based on the target flight path, and the target flight path is unique.

[0045] Furthermore, the acquisition module is specifically used to:

[0046] When the starting point and the ending point are obtained, an initial detection range corresponding to the preset drone is determined in real time, and an effective detection range corresponding to the target power transmission line displayed in the initial detection range is detected in real time;

[0047] Calculating in real time a target ratio between the effective detection range and the initial detection range, and proportionally reducing the initial detection range according to the target ratio to generate in real time a target detection range adapted to the target transmission line;

[0048] The target flight path of the preset UAV is correspondingly determined based on the target detection range.

[0049] Furthermore, the acquisition module is specifically used to:

[0050] When the target detection range is determined, controlling the preset drone to fly a first path corresponding to the target detection range in a direction from the starting point to the end point;

[0051] When the preset drone is detected in real time to have arrived at the end point, the preset drone is controlled to fly a corresponding second path based on the target detection range in a direction from the end point to the start point, where the first path corresponds to the second path;

[0052] The first path and the second path are integrated to generate the target flight path.

[0053] Furthermore, the parsing module is specifically used to:

[0054] When the detection video is acquired in real time, a corresponding detection image is randomly generated in the detection video, and a target diameter corresponding to the target transmission line is determined according to the detection image;

[0055] detecting in real time the flight speed and flight time corresponding to the preset UAV, and calculating the target length of the target transmission line according to the flight speed and the flight time;

[0056] The target diameter and the target length are integrated to generate the line size.

[0057] Furthermore, the parsing module is specifically used to:

[0058] When the detection video is acquired in real time, an initial time axis corresponding to the detection video is created in real time, wherein the initial time axis includes a plurality of time nodes;

[0059] Adding a corresponding target identifier to each of the time nodes, and extracting image frames corresponding to each of the time nodes from the detection video according to the target identifier;

[0060] The corresponding feature area appearing in the target power transmission line is extracted in real time according to each image frame, and each target identifier is unique.

[0061] Furthermore, the parsing module is specifically used to:

[0062] When each image frame is acquired in real time, a number of corresponding pixels contained in the image frame are detected in real time, and it is determined in real time whether there is a pixel value of the pixel point higher than a preset pixel threshold;

[0063] If it is determined in real time that the pixel value of a pixel point is higher than the preset pixel threshold, the pixel point corresponding to the current pixel value higher than the preset pixel threshold is set as the target pixel point, and the target area enclosed by each target pixel point is detected in real time;

[0064] The target area is set to correspond to the characteristic area of ​​the target power transmission line.

[0065] The third aspect of the embodiment of the present invention proposes:

[0066] A computer comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for identifying power transmission line defects when executing the computer program.

[0067] The fourth aspect of the embodiments of the present invention proposes:

[0068] A readable storage medium stores a computer program thereon, wherein when the program is executed by a processor, the method for identifying defects in a power transmission line as described above is implemented.

[0069] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A flow chart of a method for identifying defects in a transmission line provided by a first embodiment of the present invention;

[0071] Figure 2 This is a structural block diagram of a transmission line defect identification system provided by the third embodiment of the present invention.

[0072] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0073] To facilitate understanding of the present invention, the present invention will be described more fully below with reference to the accompanying drawings. The drawings illustrate several embodiments of the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the present invention.

[0074] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be an intermediate element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only.

[0075] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0076] See also Figure 1 , shown is a transmission line defect identification method provided by the first embodiment of the present invention. The transmission line defect identification method provided by this embodiment can save the manual operation process, and can objectively and accurately determine whether there are defects on the surface of the transmission line, thereby correspondingly improving the identification efficiency.

[0077] Specifically, this embodiment provides:

[0078] A method for identifying defects in a transmission line comprises the following steps:

[0079] Step S10: When the preset time arrives, the target transmission line input by the user is received in real time, and a detection video corresponding to the target transmission line is collected in real time by a preset drone based on a preset rule;

[0080] Step S20: performing real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time;

[0081] In step S30, a preset three-dimensional program is used to create a target line three-dimensional model corresponding to the target transmission line in real time according to the characteristic area and the line size, and the target line three-dimensional model is fully scanned to determine in real time whether the surface of the target transmission line has defects.

[0082] Specifically, in this embodiment, it should be noted that in order to objectively and accurately determine whether the surface of the transmission line has defects, it is necessary to collect information related to the current transmission line in real time. In particular, for ease of implementation, the present invention uses existing drone technology to collect information related to the transmission line in real time, thereby eliminating the manual collection process. Specifically, in actual application, in order to ensure that the transmission line can continue to operate normally and effectively, it is necessary to regularly inspect the transmission line to eliminate safety hazards of the transmission line. Based on this, for example, the existing transmission line is identified for defects every three months or one month. That is, after reaching the specified time, the present invention will receive the target transmission line sent by the user through the existing user terminal in real time, that is, it is necessary to clearly identify a corresponding processing object. Based on this, after the required target transmission line is determined in real time, the existing drone can immediately collect the inspection video corresponding to the current target transmission line in real time according to the pre-set rules. That is, the drone is used to inspect the target transmission line and collect the video. It should be noted that the inspection video contains information related to the current target transmission line, so that subsequent analysis can be performed to facilitate subsequent processing.

[0083] Furthermore, after the required inspection video is obtained in real time through the above steps, the corresponding analysis processing can be immediately performed. Specifically, the present invention can extract the required feature areas and line dimensions from the inside of the target transmission line in real time, and can create a proportional three-dimensional model of the target line in real time based on the current two types of information and existing three-dimensional programs such as UG or SolidWorks. On this basis, the current target line three-dimensional model is immediately fully scanned, so that it can be objectively and accurately determined whether the surface of the current target transmission line has defects, thereby eliminating the process of manual inspection and shortening the time for defect identification, which can not only improve the accuracy of defect identification, but also improve the efficiency of defect identification.

[0084] Second embodiment

[0085] Furthermore, the step of collecting the detection video corresponding to the target transmission line in real time by a preset drone based on a preset rule includes:

[0086] When the target transmission line is detected in real time, a starting point and an ending point corresponding to the target transmission line are determined in real time;

[0087] Determine in real time a target flight path corresponding to the preset UAV within the range between the starting point and the end point;

[0088] The detection video is collected in real time by the preset UAV based on the target flight path, and the target flight path is unique.

[0089] Furthermore, the step of determining in real time the target flight path corresponding to the preset drone includes:

[0090] When the starting point and the ending point are obtained, an initial detection range corresponding to the preset drone is determined in real time, and an effective detection range corresponding to the target power transmission line displayed in the initial detection range is detected in real time;

[0091] Calculating in real time a target ratio between the effective detection range and the initial detection range, and proportionally reducing the initial detection range according to the target ratio to generate in real time a target detection range adapted to the target transmission line;

[0092] The target flight path of the preset UAV is correspondingly determined based on the target detection range.

[0093] Furthermore, the step of determining the target flight path of the preset UAV based on the target detection range includes:

[0094] When the target detection range is determined, controlling the preset drone to fly a first path corresponding to the target detection range in a direction from the starting point to the end point;

[0095] When the preset drone is detected in real time to have arrived at the end point, the preset drone is controlled to fly a corresponding second path based on the target detection range in a direction from the end point to the start point, where the first path corresponds to the second path;

[0096] The first path and the second path are integrated to generate the target flight path.

[0097] Furthermore, the step of performing real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time includes:

[0098] When the detection video is acquired in real time, a corresponding detection image is randomly generated in the detection video, and a target diameter corresponding to the target transmission line is determined according to the detection image;

[0099] detecting in real time the flight speed and flight time corresponding to the preset UAV, and calculating the target length of the target transmission line according to the flight speed and the flight time;

[0100] The target diameter and the target length are integrated to generate the line size.

[0101] Furthermore, the step of performing real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time also includes:

[0102] When the detection video is acquired in real time, an initial time axis corresponding to the detection video is created in real time, wherein the initial time axis includes a plurality of time nodes;

[0103] Adding a corresponding target identifier to each of the time nodes, and extracting image frames corresponding to each of the time nodes from the detection video according to the target identifier;

[0104] The corresponding feature area appearing in the target power transmission line is extracted in real time according to each image frame, and each target identifier is unique.

[0105] Furthermore, the step of extracting the corresponding feature area appearing in the target power transmission line in real time according to each image frame includes:

[0106] When each image frame is acquired in real time, a number of corresponding pixels contained in the image frame are detected in real time, and it is determined in real time whether there is a pixel value of the pixel point higher than a preset pixel threshold;

[0107] If it is determined in real time that the pixel value of a pixel point is higher than the preset pixel threshold, the pixel point corresponding to the current pixel value higher than the preset pixel threshold is set as the target pixel point, and the target area enclosed by each target pixel point is detected in real time;

[0108] The target area is set to correspond to the characteristic area of ​​the target power transmission line.

[0109] In addition, in this embodiment, it should be noted that after the required target transmission line is determined in real time through the above steps, it is necessary to immediately collect information related to the current target transmission line. Specifically, the present invention will collect video information corresponding to the current target transmission line in real time, and again objectively and accurately determine whether the surface of the current target transmission line has defects based on the video information. It should be noted that the present invention will detect the starting point and the ending point corresponding to the current target transmission line in real time. At the same time, the target flight path of the current UAV is immediately determined in real time based on the starting point and the ending point, that is, the current UAV is controlled to collect the highest accuracy detection video in real time according to the optimal flight path. Specifically, it is necessary to determine in real time the initial detection range corresponding to the current UAV when it is not in use. Based on this, in order to enable the detection range of the current UAV to adapt to the current target transmission line, it is necessary to adaptively adjust the initial detection range of the current UAV. Specifically, the present invention will again determine the effective detection range corresponding to the current target transmission line in the current initial detection range, that is, the current target transmission line in the current The corresponding occupied area in the initial detection range. Based on this, in order to facilitate subsequent adjustments, the present invention will calculate in real time the target ratio between the current effective detection range and the current initial detection range. Specifically, based on the target ratio, the current initial detection range can be directly proportionally reduced, so that the current drone can generate a target detection range that is compatible with the current target transmission line in real time. Based on this, subsequent path planning can be carried out. Specifically, the present invention will first control the current drone to fly within the target detection range in the direction from the starting point to the ending point, and generate a corresponding first path. It should be noted that since existing power lines are all cylindrical, that is, the detection of one surface cannot cover the surface of the power line. Based on this, it is necessary to detect the other surface of the current power line. Similarly, the present invention will again control the current drone to fly within the target detection range in the direction from the ending point to the starting point, and generate a corresponding second path. Based on this, it is only necessary to integrate the current first path and the second path in real time to generate the target flight path for subsequent processing.

[0110] Furthermore, after obtaining the required target flight path in real time through the above steps, the current UAV can be controlled to immediately collect the detection video corresponding to the current target transmission line in real time according to the current target flight path. In order to facilitate the extraction of the required feature areas and line dimensions, corresponding analysis processing is required at this time. Specifically, the present invention will randomly generate a detection image in the current detection video, wherein the target diameter corresponding to the current target transmission line can be directly determined based on the detection image. In addition, since the current UAV is flying at a constant speed, based on this, the target length of the current target transmission line can be calculated according to the flight speed and flight time of the current UAV. Based on this, corresponding integration can be performed to generate the above-mentioned line dimensions. In addition, after the required inspection video is obtained in real time through the above steps, in order to objectively and accurately extract the corresponding feature areas appearing in the above inspection video, that is, to extract the areas where defects may occur on the surface of the above target transmission line in real time, based on this, the present invention will create an initial time axis with the current inspection video in real time. At the same time, it will synchronously detect several time nodes contained in the current initial time axis. In order to facilitate subsequent identification, a corresponding target identifier will be added to each current time node, so that the image frames corresponding to each time node can be extracted in the above inspection video based on the current target identifier. Specifically, each current time node will also be detected in real time. Each image frame contains several pixel values ​​respectively. At the same time, it will judge in real time whether the size of each current pixel value is greater than the preset pixel threshold. Specifically, if it is judged in real time that the size of a pixel value is greater than the preset pixel threshold, the target pixel value corresponding to the current pixel value being greater than the preset pixel threshold will be detected in real time, and the target area enclosed by each current target pixel value will be detected in real time. Specifically, defects may appear inside the target area, that is, the target area is the feature area that needs to be extracted in real time. In the subsequent recognition process, it is only necessary to detect each feature area to determine whether a defect occurs, thereby greatly improving the efficiency of defect recognition.

[0111] See also Figure 2 , the third embodiment of the present invention provides:

[0112] A transmission line defect identification system, wherein the system comprises:

[0113] The acquisition module is used to receive the target transmission line input by the user in real time when the preset time arrives, and to collect the detection video corresponding to the target transmission line in real time through a preset drone based on preset rules;

[0114] An analysis module is used to perform real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time;

[0115] A judgment module is used to create a target line three-dimensional model corresponding to the target transmission line in real time according to the characteristic area and the line size through a preset three-dimensional program, and to perform a full scan of the target line three-dimensional model to determine in real time whether the surface of the target transmission line has defects.

[0116] Furthermore, the acquisition module is specifically used to:

[0117] When the target transmission line is detected in real time, a starting point and an ending point corresponding to the target transmission line are determined in real time;

[0118] Determine in real time a target flight path corresponding to the preset UAV within the range between the starting point and the end point;

[0119] The detection video is collected in real time by the preset UAV based on the target flight path, and the target flight path is unique.

[0120] Furthermore, the acquisition module is specifically used to:

[0121] When the starting point and the ending point are obtained, an initial detection range corresponding to the preset drone is determined in real time, and an effective detection range corresponding to the target power transmission line displayed in the initial detection range is detected in real time;

[0122] Calculating in real time a target ratio between the effective detection range and the initial detection range, and proportionally reducing the initial detection range according to the target ratio to generate in real time a target detection range adapted to the target transmission line;

[0123] The target flight path of the preset UAV is correspondingly determined based on the target detection range.

[0124] Furthermore, the acquisition module is specifically used to:

[0125] When the target detection range is determined, controlling the preset drone to fly a first path corresponding to the target detection range in a direction from the starting point to the end point;

[0126] When the preset drone is detected in real time to have arrived at the end point, the preset drone is controlled to fly a corresponding second path based on the target detection range in a direction from the end point to the start point, where the first path corresponds to the second path;

[0127] The first path and the second path are integrated to generate the target flight path.

[0128] Furthermore, the parsing module is specifically used to:

[0129] When the detection video is acquired in real time, a corresponding detection image is randomly generated in the detection video, and a target diameter corresponding to the target transmission line is determined according to the detection image;

[0130] detecting in real time the flight speed and flight time corresponding to the preset UAV, and calculating the target length of the target transmission line according to the flight speed and the flight time;

[0131] The target diameter and the target length are integrated to generate the line size.

[0132] Furthermore, the parsing module is specifically used to:

[0133] When the detection video is acquired in real time, an initial time axis corresponding to the detection video is created in real time, wherein the initial time axis includes a plurality of time nodes;

[0134] Adding a corresponding target identifier to each of the time nodes, and extracting image frames corresponding to each of the time nodes from the detection video according to the target identifier;

[0135] The corresponding feature area appearing in the target power transmission line is extracted in real time according to each image frame, and each target identifier is unique.

[0136] Furthermore, the parsing module is specifically used to:

[0137] When each image frame is acquired in real time, a number of corresponding pixels contained in the image frame are detected in real time, and it is determined in real time whether there is a pixel value of the pixel point higher than a preset pixel threshold;

[0138] If it is determined in real time that the pixel value of a pixel point is higher than the preset pixel threshold, the pixel point corresponding to the current pixel value higher than the preset pixel threshold is set as the target pixel point, and the target area enclosed by each target pixel point is detected in real time;

[0139] The target area is set to correspond to the characteristic area of ​​the target power transmission line.

[0140] A fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-described method for identifying power transmission line defects when executing the computer program.

[0141] A fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the power transmission line defect identification method as described above.

[0142] In summary, the power transmission line defect identification method and system provided by the above embodiments of the present invention can eliminate the manual operation process and objectively and accurately determine whether the surface of the transmission line has defects, thereby correspondingly improving the identification efficiency.

[0143] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0144] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0145] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0146] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0147] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0148] The above-described embodiments merely illustrate several embodiments of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A method for identifying defects in a transmission line, characterized in that: The method comprises: When the preset time arrives, the target transmission line input by the user is received in real time, and a detection video corresponding to the target transmission line is collected in real time by a preset drone based on preset rules; Performing real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time; A preset three-dimensional program is used to create a target line three-dimensional model corresponding to the target transmission line in real time according to the characteristic area and the line size, and the target line three-dimensional model is fully scanned to determine in real time whether the surface of the target transmission line has defects.

2. The method for identifying transmission line defects according to claim 1, wherein: The step of collecting the detection video corresponding to the target transmission line in real time by using a preset drone based on a preset rule includes: When the target transmission line is detected in real time, a starting point and an ending point corresponding to the target transmission line are determined in real time; Determine in real time a target flight path corresponding to the preset UAV within the range between the starting point and the end point; The detection video is collected in real time by the preset UAV based on the target flight path, and the target flight path is unique.

3. The method for identifying power transmission line defects according to claim 2, wherein: The step of determining the target flight path corresponding to the preset UAV in real time includes: When the starting point and the ending point are obtained, an initial detection range corresponding to the preset drone is determined in real time, and an effective detection range corresponding to the target power transmission line displayed in the initial detection range is detected in real time; Calculating in real time a target ratio between the effective detection range and the initial detection range, and proportionally reducing the initial detection range according to the target ratio to generate in real time a target detection range adapted to the target transmission line; The target flight path of the preset UAV is correspondingly determined based on the target detection range.

4. The method for identifying transmission line defects according to claim 3, wherein: The step of determining the target flight path of the preset UAV based on the target detection range includes: When the target detection range is determined, controlling the preset drone to fly a first path corresponding to the target detection range in a direction from the starting point to the end point; When the preset drone is detected in real time to have arrived at the end point, the preset drone is controlled to fly a corresponding second path based on the target detection range in a direction from the end point to the start point, where the first path corresponds to the second path; The first path and the second path are integrated to generate the target flight path.

5. The method for identifying power transmission line defects according to claim 1, wherein: The step of analyzing the detection video in real time to extract the characteristic area and line size corresponding to the target transmission line in real time includes: When the detection video is acquired in real time, a corresponding detection image is randomly generated in the detection video, and a target diameter corresponding to the target transmission line is determined according to the detection image; detecting in real time the flight speed and flight time corresponding to the preset UAV, and calculating the target length of the target transmission line according to the flight speed and the flight time; The target diameter and the target length are integrated to generate the line size.

6. The method for identifying power transmission line defects according to claim 5, characterized in that: The step of performing real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time also includes: When the detection video is acquired in real time, an initial time axis corresponding to the detection video is created in real time, wherein the initial time axis includes a plurality of time nodes; Adding a corresponding target identifier to each of the time nodes, and extracting image frames corresponding to each of the time nodes from the detection video according to the target identifier; The corresponding feature area appearing in the target power transmission line is extracted in real time according to each image frame, and each target identifier is unique.

7. The method for identifying power transmission line defects according to claim 6, wherein: The step of extracting the corresponding feature area appearing in the target power transmission line in real time according to each image frame includes: When each image frame is acquired in real time, a number of corresponding pixels contained in the image frame are detected in real time, and it is determined in real time whether there is a pixel value of the pixel point higher than a preset pixel threshold; If it is determined in real time that the pixel value of a pixel point is higher than the preset pixel threshold, the pixel point corresponding to the current pixel value higher than the preset pixel threshold is set as the target pixel point, and the target area enclosed by each target pixel point is detected in real time; The target area is set to correspond to the characteristic area of ​​the target power transmission line.

8. A transmission line defect identification system, characterized in that: The system comprises: The acquisition module is used to receive the target transmission line input by the user in real time when the preset time arrives, and to collect the detection video corresponding to the target transmission line in real time through a preset drone based on preset rules; An analysis module is used to perform real-time analysis on the detection video to extract the characteristic area and line size corresponding to the target transmission line in real time; A judgment module is used to create a target line three-dimensional model corresponding to the target transmission line in real time according to the characteristic area and the line size through a preset three-dimensional program, and to perform a full scan of the target line three-dimensional model to determine in real time whether the surface of the target transmission line has defects.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for identifying defects in a power transmission line according to any one of claims 1 to 7 is implemented.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for identifying defects in a power transmission line according to any one of claims 1 to 7 is implemented.

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