CN117690064B

CN117690064B - Transmission line detection method, transmission line detection device, electronic equipment and computer readable medium

Info

Publication number: CN117690064B
Application number: CN202410156975.7A
Authority: CN
Inventors: 宋廷汉; 孔诗琦; 许宇翔; 黄轲; 贲成; 张竞; 李情; 冯玮; 张强; 赵广泉
Original assignee: Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
Current assignee: Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
Priority date: 2024-02-04
Filing date: 2024-02-04
Publication date: 2024-04-16
Anticipated expiration: 2044-02-04
Also published as: CN117690064A

Abstract

The embodiment of the disclosure discloses a transmission line detection method, a transmission line detection device, electronic equipment and a computer readable medium. One embodiment of the method comprises the following steps: acquiring an initial line picture information set shot by each camera to obtain an initial line picture information set; obtaining a line twinning model corresponding to each power transmission line; performing data cleaning processing on the initial line picture information set to generate a line picture information set; mapping the line picture information set and the line twin model to generate a video twin model; transmitting the video twin model to a user terminal to acquire line position information clicked by the user terminal; adjusting angles of cameras corresponding to line position information in the video twin model to obtain a target power transmission line picture set; and sending the obtained target power transmission line picture set to the user terminal so that the user terminal can detect the target power transmission line picture set. This embodiment may reduce the waste of computing resources.

Description

Transmission line detection method, transmission line detection device, electronic equipment and computer readable medium

Technical Field

Embodiments of the present disclosure relate to the field of computer technology, and in particular, to a method, an apparatus, an electronic device, and a computer readable medium for detecting a transmission line.

Background

By detecting the power transmission line, the power transmission line in an abnormal state (for example, the screw is not fastened, the middle joint is loosened, and the like) can be detected, so that the power transmission line in the abnormal state can be adjusted to be in a normal state, and the power transmission line can normally operate. At present, the detection of the transmission line generally adopts the following modes: and identifying the abnormal state in the real-time video of the power transmission line shot by the camera by means of manually identifying the abnormal state so as to detect the power transmission line, or identifying the abnormal state in the line twinning model so as to detect the power transmission line.

However, the following technical problems generally exist in the above manner:

Firstly, the abnormal state is identified only through real-time video, and after the abnormal state is identified each time, time and calculation resources are consumed to calculate the position of the abnormal state, so that the calculation resources are wasted;

secondly, in a mode of identifying an abnormal state through the line twinning model, the abnormal state of the power transmission line at the current moment is difficult to detect because the line twinning model is different from a real scene due to possible delay, and the power transmission line is difficult to normally operate.

The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, may contain information that does not form the prior art that is already known to those of ordinary skill in the art in this country.

Disclosure of Invention

The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose transmission line detection methods, apparatuses, electronic devices, and computer-readable media to solve one or more of the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a power transmission line detection method, including: acquiring an initial line picture information group shot by each camera to obtain an initial line picture information group set, wherein the initial line picture information in the initial line picture information group set comprises: an initial camera identification, initial camera visual field information, an initial power transmission line identification and an initial power transmission line picture; obtaining a line twinning model corresponding to each power transmission line; performing data cleaning processing on the initial line picture information set to generate a line picture information set, wherein the line picture information in the line picture information set comprises: camera identification, camera visual field information, power transmission line identification and power transmission line pictures; mapping the line picture information set and the line twin model to generate a video twin model; transmitting the video twin model to a user terminal to obtain line position information clicked by the user terminal; adjusting angles of cameras corresponding to the line position information in the video twin model to obtain a target power transmission line picture set; and sending the obtained target power transmission line picture set to the user terminal so that the user terminal detects the target power transmission line picture set.

In a second aspect, some embodiments of the present disclosure provide an electric transmission line detection apparatus, the apparatus including: the first obtaining unit is configured to obtain an initial line picture information set shot by each camera, and obtain an initial line picture information set, wherein initial line picture information in the initial line picture information set comprises: an initial camera identification, initial camera visual field information, an initial power transmission line identification and an initial power transmission line picture; the second acquisition unit is configured to acquire a line twinning model corresponding to each power transmission line; a data cleaning unit configured to perform data cleaning processing on the initial line picture information set to generate a line picture information set, where line picture information in the line picture information set includes: camera identification, camera visual field information, power transmission line identification and power transmission line pictures; a mapping unit configured to map the line picture information set and the line twin model to generate a video twin model; the first sending unit is configured to send the video twin model to the user terminal so as to acquire line position information clicked by the user terminal; the adjusting unit is configured to adjust angles of cameras corresponding to the line position information in the video twin model so as to obtain a target power transmission line picture set; and the second sending unit is configured to send the obtained target transmission line picture set to the user terminal so that the user terminal detects the target transmission line picture set.

In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors causes the one or more processors to implement the method described in any of the implementations of the first aspect above.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

The above embodiments of the present disclosure have the following advantageous effects: by the transmission line detection method of some embodiments of the present disclosure, the waste of computing resources can be reduced. Specifically, the reason for wasting computing resources is that: the abnormal state is identified only by real-time video, and after the abnormal state is identified, time and calculation resources are consumed to calculate the position of the abnormal state. Based on this, in the power transmission line detection method according to some embodiments of the present disclosure, first, an initial line picture information set captured by each camera is obtained, and an initial line picture information set is obtained. Therefore, real-time video of the power transmission line shot by each camera can be obtained. And secondly, obtaining a line twinning model corresponding to each power transmission line. Therefore, the line twinning model can be obtained, so that the positions of all parts in the power transmission line can be determined according to the line twinning model. And then, carrying out data cleaning processing on the initial line picture information group set so as to generate the line picture information group set. Therefore, the initial line picture information set can be screened, and the initial power transmission line picture can be preprocessed, so that the line picture information set is obtained. And then, carrying out mapping processing on the line picture information set and the line twin model to generate a video twin model. Therefore, the line pictures included in the line picture information set can be added into the line twin model through mapping processing, and the video twin model is obtained. And then, the video twin model is sent to the user terminal to acquire the line position information clicked by the user terminal. Thus, the position of clicking the video twin model by the user can be obtained. And then, adjusting the angles of all cameras corresponding to the line position information in the video twin model to obtain a target power transmission line picture set. Therefore, the user terminal at the current moment can obtain the power transmission line picture at the appointed position to be checked. And finally, sending the obtained target power transmission line picture set to the user terminal so that the user terminal detects the target power transmission line picture set. Therefore, the target transmission line picture set can be sent to the user terminal so that the user terminal can detect the abnormal state at the designated position. Therefore, the video twin model can be obtained by mapping the real-time video shot by the camera with the line twin model, and the line twin model also comprises the position information of each component in the power transmission line as the line twin model comprises the position information of each component in the power transmission line. Therefore, the position of each part of the transmission line in the real-time video shot by the camera can be obtained by consuming computing resources to perform one-time mapping processing. Thus, the waste of computing resources can be reduced.

Drawings

The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.

Fig. 1 is a flow chart of some embodiments of a transmission line detection method according to the present disclosure;

Fig. 2 is a schematic structural view of some embodiments of a transmission line detection apparatus according to the present disclosure;

fig. 3 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Referring to fig. 1, a flow 100 of some embodiments of a transmission line detection method according to the present disclosure is shown. The transmission line detection method comprises the following steps:

step 101, obtaining an initial line picture information set shot by each camera, and obtaining an initial line picture information set.

In some embodiments, the execution body (for example, a computing device) of the transmission line detection method may acquire, by way of wired connection or wireless connection, an initial line picture information set captured by each camera from the terminal device, to obtain an initial line picture information set. Wherein, the initial line picture information in the initial line picture information group set may include, but is not limited to, at least one of the following: the method comprises the steps of initial camera identification, initial camera visual field information, initial power transmission line identification and initial power transmission line picture. Here, the camera may be a camera for photographing a power transmission line. The transmission line may include, but is not limited to: screws (for fixing wires), wires (for transmitting electric energy), intermediate connectors (for connecting two wires), and the like. The initial camera identification may uniquely identify a camera. The initial camera view information may represent an angle of a camera corresponding to the initial line picture information. The initial transmission line identification may uniquely identify a transmission line. The initial power transmission line picture can represent a picture of the power transmission line shot by the camera under the angle of the camera represented by the initial camera visual field information.

For example, the camera may be, but is not limited to: barrel camera, hemisphere camera.

Step 102, obtaining a line twinning model corresponding to each power transmission line.

In some embodiments, the executing body may acquire a line twinning model corresponding to each power transmission line from the terminal device through a wired connection or a wireless connection. The line twin model may be a three-dimensional digital twin model including each transmission line.

Step 103, performing data cleaning processing on the initial line picture information group set to generate a line picture information group set.

In some embodiments, the executing body may perform data cleaning processing on the initial line picture information set to generate a line picture information set, where line picture information in the line picture information set includes: camera identification, camera visual field information, transmission line identification and transmission line pictures. Here, the camera identification may uniquely identify one camera. The camera view information can represent the angle of the camera corresponding to the line picture information. The transmission line identification may uniquely identify a transmission line. The power transmission line picture can represent the picture of the power transmission line shot by the camera under the angle of the camera represented by the visual field information of the camera.

Continuing, when the transmission line detection method of the present application is used for transmission line detection, the following problems are often associated with the transmission line detection: the conditions of uneven illumination, low contrast and the like of the power transmission line picture shot by the camera possibly exist, so that the power transmission line picture is blurred, the accurate abnormal state is difficult to identify through the power transmission line picture with low definition, and the normal state of the power transmission line is easy to identify as the abnormal state. For these problems, the conventional solutions are: and deleting the power transmission line picture set in the power transmission line picture with lower definition from the power transmission line picture set shot by the camera.

However, the above solution generally has the following technical problem three: by adopting a mode of deleting the power transmission line pictures with lower definition, if the definition of the power transmission line pictures shot by a certain camera is not high, the power transmission lines shot by the camera cannot be used, and the waste of camera resources is caused.

Aiming at the third technical problem, the following solution is adopted.

In practice, the executing body may perform data cleaning processing on the initial line picture information set to generate a line picture information set by:

First, screening the initial line picture information set to generate a line picture screening information set. The line picture screening information in the line picture screening information set may include, but is not limited to, at least one of the following: camera identification, camera visual field information, transmission line identification and transmission line screening pictures. In practice, the executing body may remove each initial line picture information meeting the preset screening condition in the initial line picture information set to obtain a line picture screening information set. Here, the preset screening conditions may be: the initial line picture information comprises an initial camera identification, initial camera view information, an initial power transmission line identification or an initial power transmission line picture which is empty.

Second, for each line picture screening information in the line picture screening information group, executing the following processing substeps:

And a first sub-step of performing geometric correction processing on the power transmission line screening pictures included in the line picture screening information to generate line picture correction information. The above circuit picture correction information may include, but is not limited to, at least one of the following: camera identification, camera visual field information, transmission line identification and transmission line correction pictures. In practice, the executing body may perform geometric correction processing on the transmission line screening picture included in the line picture screening information through a preset geometric correction algorithm, so as to generate line picture correction information. For example, the preset geometry correction algorithm may be, but is not limited to: image distortion correction algorithms (e.g., spherical correction algorithm, fisheye correction algorithm, cylindrical correction algorithm), camera calibration, and distortion correction algorithms.

And a second sub-step of performing noise reduction processing on the transmission line correction picture included in the line picture correction information to generate line picture noise reduction information. The above-mentioned line picture noise reduction information may include, but is not limited to, at least one of the following: camera identification, camera visual field information, transmission line identification and transmission line noise reduction pictures. In practice, the executing body may perform noise reduction processing on the transmission line correction picture included in the line picture correction information through a preset noise reduction algorithm, so as to generate line picture noise reduction information. For example, the preset noise reduction algorithm may be, but is not limited to: mean filtering algorithm, median filtering algorithm, gaussian low pass filtering algorithm.

And a third sub-step of performing color adjustment processing on the power transmission line noise reduction picture included in the line picture noise reduction information to generate line picture information. The line picture information may include, but is not limited to, at least one of: camera identification, camera visual field information, transmission line identification and transmission line pictures. In practice, the executing body may perform color adjustment processing on the power transmission line noise reduction picture included in the line picture noise reduction information through a preset color adjustment algorithm, so as to generate line picture information. For example, the preset color adjustment algorithm may be, but is not limited to: polynomial regression, backward propagation network algorithm, support vector regression algorithm.

And a second step of determining each generated line picture information as a line picture information group set.

The optional technical content in step 103 is taken as an invention point of the embodiment of the disclosure, and solves the third technical problem mentioned in the background art, which causes waste of camera resources. Factors causing waste of camera resources are often as follows: by adopting a mode of deleting the power transmission line pictures with lower definition, if the definition of the power transmission line pictures shot by a certain camera is not high, the power transmission lines shot by the camera cannot be used. If the above factors are solved, the effect of reducing the waste of camera resources can be achieved. To achieve this, first, the above-described initial line picture information set is subjected to a screening process to generate a line picture screening information set. Thus, the information that the initial line picture information set shot by the camera is empty can be removed. Next, for each line picture screening information in the line picture screening information group, the following processing steps are performed: firstly, performing geometric correction processing on the power transmission line screening pictures included in the line picture screening information to generate line picture correction information. Therefore, geometric correction processing can be carried out on the transmission line screening pictures so as to reduce deformation caused by factors such as photographic material deformation, objective lens distortion and the like. Secondly, noise reduction processing is carried out on the transmission line correction picture included in the line picture correction information so as to generate line picture noise reduction information. Therefore, the noise reduction processing can be carried out on the transmission line correction picture so as to reduce the influence of noise interference of the imaging equipment and the external environment on the transmission line correction picture. Thirdly, performing color adjustment processing on the power transmission line noise reduction picture included in the line picture noise reduction information to generate line picture information. Therefore, the color adjustment processing can be carried out on the power transmission line noise reduction picture so as to adjust the brightness, contrast, color balance and the like of the power transmission line noise reduction picture to improve the quality of the power transmission line noise reduction picture. And finally, determining the generated line picture information as a line picture information group set. Thus, the improved line picture information set with higher definition can be obtained. Therefore, the geometric correction, noise reduction, color adjustment and other treatments can be carried out on the power transmission line picture shot by the camera, and the power transmission line picture with higher definition is obtained. Thus, each camera can be effectively used. Furthermore, the waste of camera resources can be reduced.

And 104, performing mapping processing on the line picture information set and the line twin model to generate a video twin model.

In some embodiments, the executing body may perform mapping processing on the line picture information set and the line twinning model to generate a video twinning model. The video twin model may include, but is not limited to, at least one power transmission line picture.

In practice, the executing body may perform mapping processing on the line picture information set and the line twin model to generate a video twin model by:

The first step, obtaining the basic information of the camera corresponding to each line picture information group in the line picture information groups, and obtaining the basic information set of the camera. In practice, the executing body may obtain the basic information of the camera corresponding to each line picture information group in the line picture information group in a wired connection or wireless connection manner, so as to obtain a basic information set of the camera. Wherein, the camera basic information in the camera basic information set may include, but is not limited to, at least one of the following: camera position information and camera parameter information. The camera position information may characterize the position of the camera in a map coordinate system. The camera parameter information may include, but is not limited to, at least one of: focal length, pixel.

And secondly, updating the line twin model based on the camera basic information set to generate an initial line picture model. In practice, the executing body may add each camera corresponding to the camera basic information set to the line twinning model according to the camera position information included in the camera basic information set, so as to update the line twinning model to obtain an initial line picture model.

Third, for the line picture information group set, the following update sub-steps are performed:

and a first sub-step of selecting the line picture information from the line picture information set as the target line picture information. In practice, the executing body may randomly select the line picture information from the line picture information group set as the target line picture information.

And a second sub-step of determining the line picture information group set from which the target line picture information is removed as the line picture removal information group set.

And a third sub-step, selecting characteristic points from the power transmission line picture included in the target line picture information as line characteristic points. In practice, the executing body may randomly select the feature points from the power transmission line picture included in the target line picture information as the line feature points. Here, the characteristic point may be any point in the power transmission line picture, which characterizes a screw, an intermediate joint, and the like included in the power transmission line.

And a fourth sub-step of determining the characteristic point positions of the line characteristic points in the initial line picture model based on the target line picture information and the basic information of the camera corresponding to the target line picture information. In practice, the executing body can determine the position of the characteristic point of the line characteristic point in the initial line picture model through a preset calibration algorithm based on the target line picture information and the basic information of the camera corresponding to the target line picture information. For example, the preset calibration algorithm may be: zhang Zhengyou black and white checkerboard calibration method.

And a fifth substep, based on the feature point positions, adding the power transmission line picture included in the target line picture information into the initial line picture model to obtain a line picture updating model. In practice, the executing body may add the power transmission line picture included in the target line picture information to the position of the corresponding feature point in the initial line picture model, so as to update the initial line picture model, and obtain a line picture update model.

And a sixth substep of determining the line picture update model as a video twinning model in response to determining that the line picture removal information set is empty.

Optionally, in response to determining that the line picture removal information set is not empty, determining the line picture update model as an initial line picture model and determining the line picture removal information set as a line picture information set for performing the updating step again.

In some embodiments, the executing body may determine the line picture update model as the initial line picture model and the line picture removal information set as the line picture information set for executing the updating step again in response to determining that the line picture removal information set is not empty.

The optional technical content in step 104 is taken as an invention point of the embodiment of the disclosure, and solves the second technical problem mentioned in the background art, namely that the power transmission line is difficult to normally operate. Factors that cause the difficulty in normal operation of the transmission line are often as follows: by means of the line twinning model, the abnormal state of the power transmission line at the current moment is difficult to detect because the line twinning model possibly has delay and is different from a real scene. If the above factors are solved, the effect that the transmission line can normally run can be achieved. To achieve this effect, first, the camera basic information corresponding to each of the above-mentioned line picture information groups is acquired, and a camera basic information set is obtained. Therefore, the internal parameter information of the camera can be obtained so as to determine the position of the power transmission line picture in the line twinning model later. And secondly, based on the camera basic information set, updating the line twin model to generate an initial line picture model. Thus, the camera may be added to the line twinning model for subsequent addition of the transmission line picture to the line twinning model. Next, for the line picture information group set, the following updating steps are performed: first, line picture information is selected from the line picture information set as target line picture information. And secondly, determining the line picture information group set from which the target line picture information is removed as the line picture removal information group set. Thirdly, selecting characteristic points from the power transmission line picture included in the target line picture information as line characteristic points. Therefore, the line characteristic points can be selected from the power transmission line picture, so that the position of the power transmission line picture in the initial line picture model can be determined according to the line characteristic points. Fourth, based on the target line picture information and the basic information of the camera corresponding to the target line picture information, the position of the characteristic point of the line characteristic point in the initial line picture model is determined. Therefore, the position of the characteristic point can be determined according to a preset calibration algorithm. Fifthly, based on the feature point positions, adding the power transmission line picture included in the target line picture information into the initial line picture model to obtain a line picture updating model. Thus, the transmission line picture can be added to the initial line picture model. Sixth, in response to determining that the line picture removal information set is empty, determining the line picture update model as a video twinning model. Thus, a video twin model comprising all the transmission line pictures can be obtained. Finally, in response to determining that the line picture removal information set is not empty, determining the line picture update model as an initial line picture model and determining the line picture removal information set as a line picture information set for performing the updating step again. Thus, when there is a transmission line picture that is not added to the initial line picture model, the updating step is repeated so as to add all the transmission line pictures to the initial line picture model. Therefore, the real-time video shot by the camera can be added into the line twin model to obtain the video twin model. Furthermore, the abnormal state of the transmission line can be detected through a video twin model comprising real-time video. Therefore, the abnormal state of the power transmission line at the current moment can be detected. Therefore, the user terminal can adjust the abnormal state of the power transmission line to be a normal state, so that the power transmission line can normally operate.

Step 105, the video twin model is sent to the user terminal to obtain the line position information clicked by the user terminal.

In some embodiments, the executing entity may send the video twin model to the user terminal to obtain line location information clicked by the user terminal. The line position information may characterize a position where the user terminal clicks the video twin model.

And 106, adjusting the angles of the cameras corresponding to the line position information in the video twin model to obtain a target power transmission line picture set.

In some embodiments, the executing body may adjust angles of respective cameras corresponding to the line position information in the video twin model to obtain a target power transmission line picture set. In practice, first, the executing body may determine, as the target feature point, a feature point corresponding to the line position information in the video twin model. And secondly, the execution main body can select each power transmission line picture comprising the target characteristic points from the video twin model to be used as a power transmission line selection picture set. Then, the executing body may perform grouping processing on the power transmission line selection pictures to generate a power transmission line selection picture group set. The power transmission line selection picture group in the power transmission line selection picture group set can correspond to one camera. Then, for each power transmission line selection picture group in the power transmission line selection picture group set, the executing body may determine a power transmission line selection picture satisfying a preset selection condition in the power transmission line selection picture group as a target power transmission line selection picture. And then, the executing body can determine the selected target power transmission line selection pictures as target power transmission line selection picture sets. Then, for each target transmission line selection picture in the target transmission line selection picture set, the executing body may adjust an angle of a camera corresponding to the target transmission line selection picture, so that the picture shot by the camera is the target transmission line selection picture. Finally, the executing body may determine the target transmission line selection picture set as a target transmission line picture set.

Here, the preset selection condition may be: the target transmission line selection picture is a transmission line selection picture of which the characteristic points included in each transmission line selection picture in the transmission line selection picture group are closest to the middle position.

Step 107, the obtained target transmission line picture set is sent to a user terminal, so that the user terminal detects the target transmission line picture set.

In some embodiments, the executing entity may send the obtained target transmission line picture set to the user terminal, so that the user terminal detects the target transmission line picture set. Here, in response to receiving the above-described target transmission line picture set, the user terminal may perform the following adjustment steps: firstly, detecting an abnormal state existing in a target power transmission line picture set in a manual detection mode. Then, the abnormal state existing in the target power transmission line picture set is adjusted to be a normal state in a manual adjustment mode, so that the power transmission line can normally operate.

Optionally, the above execution body may further execute the following steps:

First, receiving target characteristic information input by a user terminal. Wherein, the target characteristic information may include, but is not limited to, at least one of the following: target region, target feature point. Here, the target area may be an area that the user terminal wants to find. The target feature points may be feature points that the user accents want to view. For example, the target area may be an area on a map coordinate system. The target feature points may be, but are not limited to: screw, intermediate head.

Secondly, for each transmission line picture included in the video twin model, executing the following matching substeps:

And a first sub-step of performing matching processing on the power transmission line picture and target feature points included in the target feature information to generate a matching result. In practice, the execution subject may perform matching processing on the power transmission line picture and the target feature point included in the target feature information through a preset matching algorithm, so as to generate a matching result. The matching result may be a first preset matching result or a second preset matching result. The first preset matching result may represent that the power transmission line picture includes a target feature point. The second preset matching result may represent that the power transmission line picture does not include the target feature point. For example, the preset matching algorithm may be, but is not limited to: gray level matching algorithm, feature matching algorithm, decision tree model.

And a second sub-step of determining the power transmission line picture as a power transmission line matching picture in response to determining that the matching result meets a preset matching condition. The preset matching condition may be: the matching result is a first preset matching result.

And thirdly, determining each determined transmission line matching picture as a transmission line matching picture set.

Fourth, the matching picture sets of the power transmission lines are subjected to grouping processing to generate grouping picture sets of the power transmission lines. In practice, the executing body may perform grouping processing on the transmission line matching picture set through a preset grouping algorithm, so as to generate a transmission line grouping picture set. The preset grouping algorithm may be: and dividing each transmission line matching picture corresponding to the same camera in the transmission line matching picture set into a group.

And fifthly, determining the transmission line grouping pictures meeting the preset grouping selection conditions in the transmission line grouping picture groups as transmission line grouping selection pictures for each transmission line grouping picture group in the transmission line grouping picture group. The preset packet selection conditions may be: the transmission line grouping selection picture is a transmission line grouping picture of which the target feature points included in each transmission line grouping picture in the transmission line grouping picture group are closest to the middle position.

And sixthly, determining the determined power transmission line group selection pictures as a power transmission line group selection picture set.

And seventh, transmitting the transmission line grouping selection picture set to the user terminal.

Optionally, the above execution body may further execute the following steps:

In the first step, a camera corresponding to camera adjustment information is determined as a target camera in response to receiving the camera adjustment information sent by the user terminal. Wherein, the camera adjustment angle may include, but is not limited to, at least one of: camera identification, camera angle. The camera identification may uniquely identify a camera. The camera angle may characterize the user terminal's desire to adjust the camera to a specified angle.

And secondly, adjusting the camera angle of the target camera based on the camera adjustment information. In practice, the executing body may adjust the target camera to a camera angle included in the camera adjustment information.

And thirdly, acquiring the real-time line picture shot by the adjusted target camera. In practice, the executing body may acquire the real-time line picture taken by the target camera from the target camera through wired connection or wireless connection. The line real-time picture may be a picture taken by the target camera at the current moment.

And step four, transmitting the line real-time picture to the user terminal.

Continuing, when the transmission line detection method of the present application is used for transmission line detection, the following problems are often associated with the transmission line detection: when the video twin model is clicked manually to view the pictures of the transmission lines at different positions, the transmission lines at partial positions may not be detected. For these problems, the conventional solutions are: and aiming at each camera, sequentially adjusting the angles of the cameras to check the power transmission line pictures at different positions, and then detecting the abnormal state in the power transmission line in a manual detection mode.

However, the above solution generally has the following technical problem four: for each angle of each camera, manual detection is needed, and excessive pictures of the power transmission line to be detected can cause that part of abnormal states in the power transmission line are not detected, so that alarm on part of abnormal power transmission line is difficult.

For the fourth technical problem, the following solution is adopted.

Alternatively, the above-described execution body may execute the steps of:

First, a normal line picture is obtained. In practice, the executing body may acquire the normal line picture from the terminal device through a wired connection or a wireless connection. Here, the normal line picture may represent a picture of the power transmission line in a normal state. For example, a normal line picture is a picture that characterizes a screw as fastened and an intermediate joint as fastened.

And secondly, inputting the video twin model and the normal line picture into a pre-trained abnormal line identification model to obtain an abnormal line information set. The abnormal line identification model may be a neural network model with video twin model and normal line information as input and an abnormal line information set as output. The abnormal line information in the abnormal line information set may be information characterizing an abnormal state in which the power transmission line exists. For example, the exception state may be, but is not limited to: the screw is not fastened and the middle joint is loosened.

And thirdly, carrying out alarm processing on the user terminal based on the abnormal line information set. In practice, the executing body may send the abnormal line information set to the user terminal to alert the user terminal. The alarm processing may be to display warning text or control the speaker to give out prompt sound.

Alternatively, the pre-trained abnormal line identification model may be trained by:

First, a training sample set is obtained.

In some embodiments, the executing entity may obtain the training sample set from the terminal device through a wired connection or a wireless connection. Wherein, the training samples in the training sample set may include: a sample video twin model, sample normal line information and a sample abnormal line information set.

And secondly, determining an initial abnormal line identification model.

In some embodiments, the execution body may determine an initial abnormal line identification model. Wherein, the abnormal line identification model can include, but is not limited to, at least one of the following: an initial picture segmentation model, an initial picture identification model, an initial line comparison model and an initial abnormal information output model.

The initial image segmentation model may be a model with a video twin model as input and an initial line image set as output. Here, the initial line picture in the initial line picture set may be a picture characterizing a screw, an intermediate joint, or the like. The initial picture segmentation model described above may be used to: and carrying out segmentation processing on each power transmission line picture included in the video twin model through a preset picture segmentation algorithm so as to generate each initial line picture and obtain an initial line picture set. For example, the preset picture segmentation algorithm may be, but is not limited to: canny (edge detection) algorithm, sobel (Sobel) algorithm, adaptive threshold segmentation algorithm, watershed segmentation algorithm.

The initial picture recognition model may be a neural network model with the line picture as input and the line information as output. Here, the line information may include, but is not limited to, at least one of: the distance between the screw and the nut, and the middle joint state. The intermediate joint state may be a first preset state and a second preset state. The first preset state may be indicative of the intermediate joint being fastened. The second preset state may be indicative of intermediate joint loosening. For example, the distance between the screw and the nut is 2 mm. Here, the initial picture recognition model is used to: first, a recognition process is performed on a line picture by an image recognition technique to generate a recognition result. The recognition result can represent the screw and the nut. The recognition result may also characterize the intermediate joint and intermediate joint state. Secondly, in response to determining that the identification result characterizes the screw and the nut, a distance between the screw and the nut is determined as line information. Then, responsive to determining that the identification characterizes the intermediate joint and the intermediate joint state, the intermediate joint state is determined as line information.

The initial line comparison model may be a model in which initial line information and initial normal line information are input and a comparison result is output. The initial line contrast model is used to: and comparing the initial line information with the initial normal line information to generate a comparison result. Here, the comparison result may be the first comparison result or the second comparison result. The first comparison result may be indicative of the line identification information being different from the normal line information of the sample. The second comparison result may characterize that the line identification information is the same as the normal line information of the sample.

The initial abnormal information output model may be a model in which a comparison result set and an initial line picture set are taken as inputs and an initial abnormal line information set is taken as an output. The initial anomaly information output model is used for: first, each comparison result of the comparison result set representing the first comparison result is determined as a target comparison result set. And secondly, for each target comparison result in the target comparison result set, determining the target comparison result and an initial line picture corresponding to the initial line picture in the initial line picture set as initial abnormal line information. Then, the determined initial abnormal line information is determined as an initial abnormal line information set.

And thirdly, selecting training samples from the training sample set.

In some embodiments, the executing entity may select a training sample from the training sample set. In practice, the executing entity may randomly select training samples from the training sample set.

And fourthly, inputting the video twin model included in the selected training sample into an initial picture segmentation model to obtain an initial line picture set.

In some embodiments, the executing body may input a video twin model included in the selected training sample into the initial image segmentation model to obtain an initial line image set.

And fifthly, inputting each initial line picture in the initial line picture set into an initial picture identification model to generate initial line information, and obtaining an initial line information set.

In some embodiments, the executing body may input each initial line picture in the initial line picture set into an initial picture identification model to generate initial line information, so as to obtain an initial line information set.

And sixthly, inputting the sample normal line picture included in the selected training sample into an initial picture identification model to obtain initial normal line information.

In some embodiments, the executing body may input a sample normal line picture included in the selected training sample into the initial picture identification model to obtain initial normal line information. Here, the initial normal line information may include, but is not limited to, at least one of: the distance between the screw and the nut, and the middle joint state. For example, the initial normal line information includes a distance between the screw and the nut of 2 mm or less. The state of the intermediate connector included in the initial normal line information is a first preset state.

And seventhly, inputting each initial line information and the initial normal line information in the initial line information set into an initial line comparison model to generate a comparison result, and obtaining a comparison result set.

In some embodiments, the executing body may input each of the initial line information and the initial normal line information in the initial line information set into an initial line comparison model to generate a comparison result, so as to obtain a comparison result set.

And eighth step, inputting the comparison result set and the initial line picture set into the initial abnormal information output model to obtain an initial abnormal line information set.

In some embodiments, the execution body may input the comparison result set and the initial line image set into the initial abnormal information output model to obtain an initial abnormal line information set.

And ninth, determining a difference value between the initial abnormal line information set and a sample abnormal line information set included in the selected training sample based on a preset loss function.

In some embodiments, the executing body may determine a difference value between the initial abnormal line information set and a sample abnormal line information set included in the selected training sample based on a preset loss function. The preset loss function may be, but is not limited to: mean square error loss function (MSE), hinge loss function, cross entropy loss function (CrossEntropy), 0-1 loss function, absolute loss function, log loss function, square loss function, exponential loss function, and the like.

And tenth, in response to determining that the difference value is greater than or equal to a preset difference value, adjusting network parameters of the initial abnormal line identification model.

In some embodiments, the execution body may adjust the network parameters of the initial abnormal line identification model in response to determining that the difference value is equal to or greater than a preset difference value. For example, the above-described difference value and the preset difference value may be differentiated. On this basis, the error value is transmitted forward from the last layer of the model by using back propagation, random gradient descent and the like to adjust the parameters of each layer. Of course, a network freezing (dropout) method may be used as needed, and network parameters of some layers therein may be kept unchanged and not adjusted, which is not limited in any way. The setting of the preset difference value is not limited, and for example, the preset difference value may be 0.1.

The optional technical content in step 107 is taken as an invention point of the embodiment of the present disclosure, and solves the fourth technical problem mentioned in the background art, which results in that it is difficult to alarm a part of abnormal transmission lines. Factors that cause difficulty in alarming a part of abnormal transmission lines are often as follows: for each angle of each camera, manual detection is needed, and excessive pictures of the power transmission line to be detected can cause that part of abnormal states in the power transmission line are not detected. If the above factors are solved, the effect of detecting the abnormal state of the transmission line can be achieved. In order to achieve the effect, firstly, the transmission line picture in the video twin model can be segmented through an initial picture segmentation model so as to segment different parts in the transmission line picture. Then, the initial line information and the initial normal line information characterized by the initial line picture and the sample normal line picture can be identified through the initial picture identification model. And then, comparing the initial line information with the initial normal line information through an initial line comparison model so as to detect whether the initial line information is identical with the initial normal line information. Finally, abnormal line information representing the abnormal state can be output through the initial abnormal information output model. Therefore, the relatively accurate abnormal line identification model can be trained by training the initial abnormal line identification model comprising the initial picture segmentation model, the initial picture identification model, the initial line comparison model and the initial abnormal information output model, so that relatively accurate abnormal line information can be identified through the relatively accurate abnormal line identification model. Therefore, the video twin model can be input into the abnormal line identification model, and accurate abnormal line information in the video twin model can be obtained through only one input. Thus, an abnormal state of the transmission line can be detected. Furthermore, an alarm can be given to a part of abnormal transmission lines.

Optionally, in response to determining that the difference value is smaller than the preset difference value, the initial abnormal line identification model is determined as a trained abnormal line identification model.

In some embodiments, the executing body may determine the initial abnormal line recognition model as the trained abnormal line recognition model in response to determining that the difference value is smaller than the preset difference value.

With further reference to fig. 2, as an implementation of the method shown in the above figures, the present disclosure provides embodiments of a transmission line detection apparatus, which correspond to those method embodiments shown in fig. 1, and which are particularly applicable to various electronic devices.

As shown in fig. 2, the transmission line detection apparatus 200 of some embodiments includes: a first acquisition unit 201, a second acquisition unit 202, a data cleansing unit 203, a mapping unit 204, a first transmission unit 205, an adjustment unit 206, and a second transmission unit 207. The first obtaining unit 201 is configured to obtain an initial line picture information set captured by each camera, and obtain an initial line picture information set, where initial line picture information in the initial line picture information set includes: an initial camera identification, initial camera visual field information, an initial power transmission line identification and an initial power transmission line picture; a second obtaining unit 202 configured to obtain a line twinning model corresponding to each transmission line; a data cleansing unit 203 configured to perform data cleansing processing on the initial line picture information group set to generate a line picture information group set, where line picture information in the line picture information group set includes: camera identification, camera visual field information, power transmission line identification and power transmission line pictures; a mapping unit 204 configured to map the line picture information set and the line twinning model to generate a video twinning model; a first sending unit 205 configured to send the video twin model to a user terminal, so as to obtain line position information clicked by the user terminal; an adjustment unit 206 configured to adjust angles of respective cameras corresponding to the line position information in the video twin model to obtain a target power transmission line picture set; a second transmitting unit 207 configured to transmit the obtained target transmission line picture set to the user terminal, so that the user terminal detects the target transmission line picture set.

It will be appreciated that the elements described in the transmission line detection apparatus 200 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations, features and beneficial effects described above with respect to the method are equally applicable to the transmission line detection apparatus 200 and the units contained therein, and are not described herein.

Referring now to FIG. 3, a schematic diagram of an electronic device (e.g., computing device) 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic devices in some embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), car terminals (e.g., car navigation terminals), and the like, as well as stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is merely an example and should not impose any limitations on the functionality and scope of use of embodiments of the present disclosure.

As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM303, various programs and data required for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM302, and the RAM303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.

In general, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 308 including, for example, magnetic tape, hard disk, etc.; and communication means 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 3 may represent one device or a plurality of devices as needed.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 309, or from storage device 308, or from ROM 302. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing means 301.

It should be noted that, the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some embodiments, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring an initial line picture information group shot by each camera to obtain an initial line picture information group set, wherein the initial line picture information in the initial line picture information group set comprises: an initial camera identification, initial camera visual field information, an initial power transmission line identification and an initial power transmission line picture; obtaining a line twinning model corresponding to each power transmission line; performing data cleaning processing on the initial line picture information set to generate a line picture information set, wherein the line picture information in the line picture information set comprises: camera identification, camera visual field information, power transmission line identification and power transmission line pictures; mapping the line picture information set and the line twin model to generate a video twin model; transmitting the video twin model to a user terminal to obtain line position information clicked by the user terminal; adjusting angles of cameras corresponding to the line position information in the video twin model to obtain a target power transmission line picture set; and sending the obtained target power transmission line picture set to the user terminal so that the user terminal detects the target power transmission line picture set.

Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor includes a first acquisition unit, a second acquisition unit, a data cleansing unit, a mapping unit, a first transmission unit, an adjustment unit, and a second transmission unit. The names of these units do not limit the unit itself in some cases, and for example, the acquisition unit may also be described as "a unit that acquires an initial line picture information group captured by each camera, and obtains an initial line picture information group set".

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A transmission line detection method, comprising:

Acquiring an initial line picture information group shot by each camera to obtain an initial line picture information group set, wherein the initial line picture information in the initial line picture information group set comprises: an initial camera identification, initial camera visual field information, an initial power transmission line identification and an initial power transmission line picture;

Obtaining a line twinning model corresponding to each power transmission line;

Performing data cleaning processing on the initial line picture information group set to generate a line picture information group set, wherein the line picture information in the line picture information group set comprises: camera identification, camera visual field information, power transmission line identification and power transmission line pictures;

Mapping the line picture information set and the line twin model to generate a video twin model, wherein the video twin model comprises a power transmission line picture;

Transmitting the video twin model to a user terminal to acquire line position information clicked by the user terminal;

adjusting angles of cameras corresponding to the line position information in the video twin model to obtain a target power transmission line picture set;

The obtained target power transmission line picture set is sent to the user terminal so that the user terminal can detect the target power transmission line picture set;

receiving target feature information input by a user terminal, wherein the target feature information comprises: a target region, target feature points;

For each power transmission line picture included in the video twin model, executing the following matching steps:

matching the power transmission line picture with target feature points included in the target feature information to generate a matching result;

Determining the power transmission line picture as a power transmission line matching picture in response to determining that the matching result meets a preset matching condition;

determining each determined transmission line matching picture as a transmission line matching picture set;

Grouping the transmission line matching picture sets to generate transmission line grouping picture set;

For each power transmission line grouping picture group in the power transmission line grouping picture group, determining power transmission line grouping pictures meeting preset grouping selection conditions in the power transmission line grouping picture group as power transmission line grouping selection pictures;

Determining each determined power transmission line group selection picture as a power transmission line group selection picture set;

And sending the power transmission line grouping selection picture set to the user terminal.

2. The method of claim 1, wherein the method further comprises:

responding to receiving camera adjustment information sent by a user terminal, and determining a camera corresponding to the camera adjustment information as a target camera;

adjusting the camera angle of the target camera based on the camera adjustment information;

acquiring a real-time line picture shot by the adjusted target camera;

and sending the line real-time picture to the user terminal.

3. The method of claim 1, wherein the method further comprises:

obtaining a normal line picture;

inputting the video twin model and the normal line picture into a pre-trained abnormal line identification model to obtain an abnormal line information set;

and carrying out alarm processing on the user terminal based on the abnormal line information set.

4. A transmission line detection apparatus, comprising:

the first acquisition unit is configured to acquire an initial line picture information group shot by each camera to obtain an initial line picture information group set, wherein initial line picture information in the initial line picture information group set comprises: an initial camera identification, initial camera visual field information, an initial power transmission line identification and an initial power transmission line picture;

The second acquisition unit is configured to acquire a line twinning model corresponding to each power transmission line;

a data cleaning unit configured to perform data cleaning processing on the initial line picture information group set to generate a line picture information group set, wherein line picture information in the line picture information group set includes: camera identification, camera visual field information, power transmission line identification and power transmission line pictures;

The mapping unit is configured to perform mapping processing on the line picture information set and the line twin model to generate a video twin model, wherein the video twin model comprises a power transmission line picture;

The first sending unit is configured to send the video twin model to the user terminal so as to acquire line position information clicked by the user terminal;

the adjusting unit is configured to adjust angles of cameras corresponding to the line position information in the video twin model so as to obtain a target power transmission line picture set;

A second sending unit configured to send the obtained target transmission line picture set to the user terminal, so that the user terminal detects the target transmission line picture set;

wherein the transmission line detection apparatus is further configured to:

5. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon;

When executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-3.

6. A computer readable medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method of any of claims 1-3.