CN116993743A - Method, device, equipment and storage medium for detecting galloping amplitude of power transmission line - Google Patents
Method, device, equipment and storage medium for detecting galloping amplitude of power transmission line Download PDFInfo
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Abstract
The application relates to a method, a device, equipment and a storage medium for detecting the galloping amplitude of a power transmission line. The method comprises the following steps: after a camera continuously shoots a target power transmission line to obtain a plurality of continuous images to be detected, acquiring the continuous images to be detected; extracting a characteristic component area in an image to be detected, and extracting characteristic points in the characteristic component area; determining characteristic distances between each characteristic point and a target power transmission line in a plurality of images to be detected; and determining the waving amplitude of the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected. The method can detect the galloping of the power transmission line in real time based on the image, and has higher timeliness; and the galloping amplitude can be accurately calculated.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a storage medium for detecting a galloping amplitude of a power transmission line.
Background
In the running process of the power transmission line, the power transmission line is influenced by meteorological factors such as wind, ice and the like, and the galloping phenomenon can occur. Too large galloping may cause insufficient gap across the conductors, causing flashover and even tower collapse and other safety accidents.
In the conventional technology, the method for detecting the galloping of the transmission line comprises the following steps: vibration sensor detection, ultrasonic detection, lidar detection, and electromagnetic induction detection.
However, such detection methods have certain drawbacks, such as high deployment cost and limited detection range of the vibration sensor detection method; the ultrasonic detection method is greatly interfered by environmental noise and has limited accuracy; the laser radar detection method has high cost and is easily influenced by weather conditions; the electromagnetic induction detection method is interfered by surrounding electromagnetic environment, and the false alarm rate is high.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method, an apparatus, a device, and a storage medium for detecting a transmission line galloping amplitude that can safely and accurately detect transmission line galloping.
In a first aspect, the application provides a method for detecting the swing amplitude of a power transmission line. The method comprises the following steps:
after a camera continuously shoots a target power transmission line to obtain a plurality of continuous images to be detected, acquiring the continuous images to be detected;
extracting a characteristic component area in an image to be detected, and extracting characteristic points in the characteristic component area;
determining characteristic distances between each characteristic point and a target power transmission line in a plurality of images to be detected;
and determining the waving amplitude of the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected.
In one embodiment, extracting feature regions in an image to be detected includes:
carrying out gray level quantization on pixel values of all pixel points of the image to be detected to obtain gray values of all pixel points;
constructing a network topology diagram of the image to be detected according to the gray value of each pixel point; wherein, each pixel point is used as a network node in the network topology diagram, and the connecting line of each adjacent pixel point is used as an initial network edge in the network topology diagram;
determining the edge weight of each initial network edge according to the gray value of each pixel point;
and removing the initial network edge with the edge weight smaller than the preset weight threshold to obtain a plurality of final network edges, and connecting the adjacent final network edges to obtain the characteristic component area.
In one embodiment, extracting feature points in a feature region includes:
extracting effective pixel points in the feature component area;
and connecting adjacent effective pixel points to form a feature communication area, and extracting each pixel point in the feature communication area as a feature point.
In one embodiment, extracting valid pixel points in a feature region includes:
determining a preset gray threshold value of each pixel point of the characteristic component area;
and carrying out iterative search on the pixel points in the characteristic component area, and taking the pixel points with the gray values larger than a preset gray threshold value as effective pixel points.
In one embodiment, the depth estimation is performed on the images to be detected, so that feature distances between feature points in the images to be detected and the target power transmission line are determined.
In one embodiment, determining the galloping amplitude of the target transmission line according to the difference between the feature distances in the adjacent images to be detected includes:
determining the actual displacement distance of a corresponding line section in the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected, the depth of the camera and the focal length of the camera;
and determining the galloping amplitude of the target power transmission line according to the actual displacement distance.
In one embodiment, determining the galloping amplitude of the target transmission line according to the actual displacement distance includes:
acquiring adjacent image shooting time intervals to be detected;
and determining the waving amplitude of the target transmission line according to the actual displacement distance and the time interval.
In a second aspect, the application further provides a device for detecting the swing amplitude of the power transmission line. The device comprises:
the image acquisition module is used for acquiring continuous images to be detected after the camera continuously shoots the target power transmission line to obtain a plurality of continuous images to be detected;
the feature extraction module is used for extracting feature component areas in the image to be detected and extracting feature points in the feature component areas;
the distance determining module is used for determining characteristic distances between each characteristic point and the target power transmission line in the plurality of images to be detected;
and the galloping amplitude determining module is used for determining the galloping amplitude of the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected.
In a third aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
after a camera continuously shoots a target power transmission line to obtain a plurality of continuous images to be detected, acquiring the continuous images to be detected;
extracting a characteristic component area in an image to be detected, and extracting characteristic points in the characteristic component area;
determining characteristic distances between each characteristic point and a target power transmission line in a plurality of images to be detected;
and determining the waving amplitude of the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected.
In a fourth aspect, the present application also provides a computer-readable storage medium. A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
after a camera continuously shoots a target power transmission line to obtain a plurality of continuous images to be detected, acquiring the continuous images to be detected;
extracting a characteristic component area in an image to be detected, and extracting characteristic points in the characteristic component area;
determining characteristic distances between each characteristic point and a target power transmission line in a plurality of images to be detected;
and determining the waving amplitude of the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected.
In a fifth aspect, the present application also provides a computer program product. Computer program product comprising a computer program which, when executed by a processor, realizes the steps of:
after a camera continuously shoots a target power transmission line to obtain a plurality of continuous images to be detected, acquiring the continuous images to be detected;
extracting a characteristic component area in an image to be detected, and extracting characteristic points in the characteristic component area;
determining characteristic distances between each characteristic point and a target power transmission line in a plurality of images to be detected;
and determining the waving amplitude of the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected.
The method, the device, the equipment and the storage medium for detecting the galloping amplitude of the power transmission line are characterized in that the camera is used for shooting a target power transmission line to obtain a plurality of continuous images to be detected, and the plurality of continuous images to be detected obtained by the camera are obtained. And extracting a characteristic component area in the image to be detected, and extracting characteristic points in the characteristic component area, wherein the characteristic points correspond to a certain line section of the target power transmission line. In determining the characteristic distance between the characteristic points in each image to be detected and the target power transmission line, the characteristic points correspond to the actual target power transmission line, so that the actual galloping amplitude of the target power transmission line can be determined according to the difference value of the characteristic distances of the characteristic points in different images to be detected. Compared with the traditional vibration sensor detection method, the detection method provided by the application has the advantages that the camera deployment cost is lower, and the monitoring range is wide. The detection method provided by the application can detect the galloping of the power transmission line in real time based on the image, and has higher timeliness; and the galloping amplitude of the line characteristic points can be accurately calculated.
Drawings
Fig. 1 is an application environment diagram of a method for detecting a galloping amplitude of a power transmission line according to an embodiment;
fig. 2 is a flow chart of a method for detecting a galloping amplitude of a power transmission line according to an embodiment;
FIG. 3 is a flowchart illustrating a step of extracting feature areas of an image to be detected according to an embodiment;
FIG. 4 is a flowchart illustrating a step of extracting feature points in a feature region according to another embodiment;
FIG. 5 is a flowchart illustrating steps for determining a galloping amplitude of a target transmission line according to one embodiment;
fig. 6 is a flow chart of a method for detecting a swing amplitude of a transmission line according to another embodiment;
fig. 7 is a block diagram of a transmission line galloping amplitude detection device according to an embodiment;
fig. 8 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The method for detecting the galloping amplitude of the power transmission line, provided by the embodiment of the application, can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The terminal 102 is a camera and may be an electronic device with a camera function, such as a monitoring or intelligent terminal with a camera, etc. The terminal 102 is configured to capture an image of the target transmission line, and may transmit the image to the server 104 for processing. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.
In one embodiment, as shown in fig. 2, a method for detecting a galloping amplitude of a power transmission line is provided, and the method is applied to the server in fig. 1 for illustration, and includes the following steps S202 to S208:
s202, after a camera continuously shoots a target power transmission line to obtain a plurality of continuous images to be detected, the continuous images to be detected are obtained.
The camera is used for continuously shooting the target power transmission line to obtain a plurality of continuous images to be detected, which are ordered according to the time sequence. The video camera can shoot video, and split the video into a plurality of continuous images to be detected according to the number of frames; the camera can also take pictures, and take pictures at certain time intervals, so that continuous images to be detected are obtained. Schematically, a high-definition camera can be used for carrying out real-time video shooting on a target power transmission line to obtain an image to be detected.
In one possible implementation, to ensure image quality, the exposure parameters of the camera may be automatically adjusted according to light conditions, and anti-shake techniques may be used to reduce image blur.
After the camera captures an image to be detected, the server 104 communicates with the camera to obtain the captured image to be detected.
S204, extracting a feature part area in the image to be detected, and extracting feature points in the feature part area.
The image to be detected obtained by the camera comprises the target transmission line, however, it is unavoidable that a background outside the target transmission line is shot in the shooting process, and the background needs to be removed at this time.
The characteristic component area is the area where the lead of the target transmission line is located, and the lead area can be extracted through the difference between the lead and the background in the image to be detected.
As shown in fig. 3, in one embodiment, extracting feature component areas of an image to be detected may be achieved by the following steps S302 to S308.
S302, carrying out gray level quantization on pixel values of all pixel points of the image to be detected to obtain gray values of all the pixel points.
The image to be detected consists of densely distributed pixel points. A pixel is a point in an image that has a particular location and value. Each pixel may represent a small region in the image and record the color of that region.
In digital images, pixels are typically represented by numbers, i.e., pixel values in this embodiment. For color images, each pixel is composed of three components of red, green and blue, and represents color information of the pixel point, for example, the sizes of the components of red, green and blue can be represented by 0-255.
Gray level quantization is used to map the pixel value of each pixel of the original image onto a set of discrete gray levels, for example 256 or 16 gray levels, so that different pixels are converted into gray values, each pixel having only one value, each pixel being capable of representing the brightness level by the gray value.
S304, constructing a network topological graph of the image to be detected according to the gray value of each pixel point; wherein each pixel point is used as a network node in the network topology diagram, and the connecting line of each adjacent pixel point is used as an initial network edge in the network topology diagram.
The network topology comprises a plurality of network nodes, and adjacent network nodes are connected through network edges to form a mesh structure.
In this embodiment, the pixel points are used as network nodes, and the connection lines of the pixel points are used as initial network edges, so as to form a network topology diagram of the image to be detected.
S306, determining the edge weight of each initial network edge according to the gray value of each pixel point.
The edge weights of the network edges essentially show the variability of the connected network nodes, the larger the edge weights, the larger the gray value difference of the two network nodes, the greater the likelihood of being a feature area boundary line.
Optionally, taking the average value of gray values between any two adjacent pixel points as the edge weight of the network edge corresponding to any two adjacent pixel points.
And S308, removing the initial network edge with the edge weight smaller than the preset weight threshold to obtain a plurality of final network edges, and connecting the adjacent final network edges to obtain the characteristic component area.
Setting a preset weight threshold of the edge weight, removing the initial network edge with the edge weight smaller than the preset weight threshold, reserving the initial network edge larger than or equal to the preset weight threshold, wherein the reserved initial network edge is the final network edge, and connecting all the final network edges to obtain a surrounding area, namely the characteristic component area.
For example, in the image to be monitored, if two adjacent pixel points are all parts on the conducting wire, the gray value difference is smaller, and if the two adjacent pixel points are all parts on the background, the gray value difference is also smaller. Only one pixel is located on the wire and the other pixel is located on the background, there is a significant gray value difference. Based on this principle, the feature recognition region can be accurately recognized.
In this embodiment, the gray level of the image to be detected is processed to obtain a gray level image, and each pixel point has a gray level value after gray level, and the feature component area is determined according to the gray level value. By the method, the boundary line of the characteristic part can be accurately screened, the characteristic part area is determined by the boundary line, and the judgment speed and the judgment accuracy are high.
The feature points are portions having special features in the feature component region, and may be, for example, different colors, different shapes, or have particles, and the feature points can be specifically extracted by recognizing the colors, shapes, or the particles.
As shown in fig. 4, in one embodiment, extracting feature points in a feature region may be achieved by the following steps S402 to S404.
S402, extracting effective pixel points in the feature component area.
The effective pixel points are the pixel points of the lead of the target transmission line and can reflect the area of the galloping condition of the target transmission line.
In a possible implementation manner, a preset gray threshold value of each pixel point in the feature part area can be determined by using a maximum inter-class variance method, and then iterative search is performed on the pixel points in the feature part area, and the pixel points with gray values larger than the preset gray threshold value are used as effective pixel points.
The maximum inter-class variance method can effectively partition images into different classes and is more effective for objects or backgrounds with significantly different features.
In this way, the effective pixel points in the feature component region can be quickly and accurately determined.
S404, connecting adjacent effective pixel points to form a feature communication area, and extracting each pixel point in the feature communication area as a feature point.
After the effective pixel points are determined, the effective pixel points are connected to form a characteristic communication area. Illustratively, feature points in the feature communication region may be extracted using a boundary feature method.
In this embodiment, after extracting the effective pixel points in the feature component region, the region formed around the effective pixel points is used as the feature point. Characteristic points which can represent the galloping condition in the image to be detected are accurately screened.
S206, determining characteristic distances between the characteristic points and the target transmission line in the plurality of images to be detected.
The characteristic distance is the distance between the characteristic point and the target transmission line. Illustratively, depth estimation may be performed on the image using a deep learning technique, such as CNN (Convolutional Neural Networks, convolutional neural network), to calculate the distance from the feature point in the image to the target transmission line.
Alternatively, the CNN is based on a coding-decoding structure, such as a U-Net (U-shaped Network) structure. The encoding part is used for extracting advanced features of the image to be detected, and the decoding part is used for recovering the original size of the image to be detected, and meanwhile, the depth information is reserved.
In order to improve the accuracy of depth estimation, attention mechanisms can be introduced into a network structure, so that importance of a network to a key part is increased, and meanwhile, attention to unimportant areas is reduced. Alternatively, the key portion may be the feature point position.
And S208, determining the waving amplitude of the target transmission line according to the difference value of the characteristic distances in the adjacent images to be detected.
After the feature distance in each image to be detected is determined, the feature displacement distance of the pixels can be converted into the actual distance according to the moving pixels and depth information of the feature points in the images to be detected in the continuous frames, so that the galloping amplitude of the line feature points is obtained.
As shown in fig. 5, in one embodiment, the galloping amplitude of the target transmission line is determined through the following S502 and S504.
S502, determining the actual displacement distance of the corresponding line section in the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected, the depth of the camera and the focal length of the camera.
The characteristic point corresponds to a line segment of the target power transmission line and may be a point or an area, so that movement of the characteristic point can reflect movement of the line segment. The characteristic distance of the displacement of the characteristic points in the two adjacent images to be detected can be converted into the actual displacement distance of the line section.
The calculation of the actual displacement distance can adopt the projection geometric principle, and the formula is as follows: actual displacement distance = difference in feature distance × depth/focal length, where depth and focal length can be obtained from internal parameters of the camera.
S504, determining the waving amplitude of the target transmission line according to the actual displacement distance.
After the actual displacement distance is determined, the galloping amplitude of the target power transmission line can be determined according to the interval between the shooting time of two adjacent images to be detected.
In one possible implementation, the determination of the amplitude of the dance includes: acquiring adjacent image shooting time intervals to be detected; and determining the waving amplitude of the target transmission line according to the actual displacement distance and the time interval.
The formula is: the galloping amplitude=actual displacement distance/time interval, so that the displacement of the transmission line wire in unit time, namely the galloping amplitude, can be obtained; the time interval is the time interval when the camera collects two adjacent images to be detected of the target transmission line.
In addition, the galloping amplitude of the whole target power transmission line can be obtained by calculating the galloping amplitudes of the characteristic points of the plurality of different positions of the target power transmission line and carrying out weighted average.
In the transmission line galloping amplitude detection method, the camera is used for shooting the target transmission line to obtain a plurality of continuous images to be detected, and the plurality of continuous images to be detected obtained by the camera are obtained. And extracting a characteristic component area in the image to be detected, and extracting characteristic points in the characteristic component area, wherein the characteristic points correspond to a certain line section of the target power transmission line. In determining the characteristic distance between the characteristic points in each image to be detected and the target power transmission line, the characteristic points correspond to the actual target power transmission line, so that the actual galloping amplitude of the target power transmission line can be determined according to the difference value of the characteristic distances of the characteristic points in different images to be detected. Compared with the traditional vibration sensor detection method, the detection method provided by the application has the advantages that the camera deployment cost is lower, and the monitoring range is wide. The detection method provided by the application can detect the galloping of the power transmission line in real time based on the image, and has higher timeliness; and the galloping amplitude of the line characteristic points can be accurately calculated.
As shown in fig. 6, in one embodiment, a method for detecting a swing amplitude of a power transmission line includes the steps of:
s602, after a camera continuously shoots a target power transmission line to obtain a plurality of continuous images to be detected, the continuous images to be detected are obtained.
S604, carrying out gray level quantization on the pixel value of each pixel point of the image to be detected to obtain the gray value of each pixel point.
S606, constructing a network topological graph of the image to be detected according to the gray value of each pixel point; wherein each pixel point is used as a network node in the network topology diagram, and the connecting line of each adjacent pixel point is used as an initial network edge in the network topology diagram.
S608, determining the edge weight of each initial network edge according to the gray value of each pixel point.
And S610, removing the initial network edge with the edge weight smaller than the preset weight threshold to obtain a plurality of final network edges, and connecting the adjacent final network edges to obtain the characteristic component area.
S612, determining a preset gray threshold value of each pixel point of the characteristic component area.
S614, carrying out iterative search on the pixel points in the characteristic component area, and taking the pixel points with the gray values larger than a preset gray threshold value as effective pixel points.
S616, connecting adjacent effective pixel points to form a feature communication area, and extracting each pixel point in the feature communication area as a feature point.
And S618, determining the characteristic distance between each characteristic point and the target transmission line in the plurality of images to be detected.
S620, determining the actual displacement distance of the corresponding line section in the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected, the depth of the camera and the focal length of the camera.
S622, acquiring adjacent image shooting time intervals to be detected.
S624, determining the galloping amplitude of the target power transmission line according to the actual displacement distance and the time interval.
In this embodiment, a plurality of continuous images to be detected are obtained by capturing a target power transmission line with a camera, and gray scales of the images to be detected are quantized, so that pixel values of all pixel points are converted into gray values. And constructing a network topological graph according to the gray value of each pixel point, and determining a characteristic component area by setting a preset weight threshold value of a network side. And extracting effective pixel points in the feature component area, so that feature points are determined according to feature communication areas formed by the effective pixel points. And then, according to the characteristic distances between the characteristic points and the target power transmission line in the images to be detected, determining the waving amplitude of the target power transmission line. The method for detecting the galloping of the power transmission line in the embodiment has higher timeliness and can accurately calculate the galloping amplitude of the characteristic points of the line.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a power transmission line galloping amplitude detection device for realizing the power transmission line galloping amplitude detection method. The implementation scheme of the device for solving the problem is similar to the implementation scheme described in the method, so the specific limitation of the embodiment of the device for detecting the galloping amplitude of the power transmission line provided below can be referred to the limitation of the method for detecting the galloping amplitude of the power transmission line hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 7, there is provided a transmission line galloping amplitude detection apparatus 700, including: an image acquisition module 702, a feature extraction module 704, a distance determination module 706, and a waving amplitude determination module 708, wherein:
the image acquisition module 702 is configured to acquire a plurality of continuous images to be detected after the camera continuously shoots the target transmission line to obtain the continuous images to be detected.
The feature extraction module 704 is configured to extract a feature component area in the image to be detected, and extract feature points in the feature component area.
The distance determining module 706 is configured to determine feature distances between each feature point and the target transmission line in the multiple images to be detected.
And the galloping amplitude determining module 708 is configured to determine the galloping amplitude of the target power transmission line according to the difference value of the feature distances in the adjacent images to be detected.
In one embodiment, the feature extraction module 704 is further configured to: carrying out gray level quantization on pixel values of all pixel points of the image to be detected to obtain gray values of all pixel points; constructing a network topology diagram of the image to be detected according to the gray value of each pixel point; wherein, each pixel point is used as a network node in the network topology diagram, and the connecting line of each adjacent pixel point is used as an initial network edge in the network topology diagram; determining the edge weight of each initial network edge according to the gray value of each pixel point; and removing the initial network edge with the edge weight smaller than the preset weight threshold to obtain a plurality of final network edges, and connecting the adjacent final network edges to obtain the characteristic component area.
In one embodiment, the feature extraction module 704 is further configured to: extracting effective pixel points in the feature component area; and connecting adjacent effective pixel points to form a feature communication area, and extracting each pixel point in the feature communication area as a feature point.
In one embodiment, the feature extraction module 704 is further configured to: determining a preset gray threshold value of each pixel point of the characteristic component area; and carrying out iterative search on the pixel points in the characteristic component area, and taking the pixel points with the gray values larger than a preset gray threshold value as effective pixel points.
In one embodiment, the distance determining module 706 determines the feature distances between each feature point in the plurality of images to be detected and the target transmission line by performing depth estimation on the images to be detected.
In one embodiment, the dance amplitude determination module 708 is further to: determining the actual displacement distance of a corresponding line section in the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected, the depth of the camera and the focal length of the camera; and determining the galloping amplitude of the target power transmission line according to the actual displacement distance.
In one embodiment, the dance amplitude determination module 708 is further to: acquiring adjacent image shooting time intervals to be detected; and determining the waving amplitude of the target transmission line according to the actual displacement distance and the time interval.
All or part of each module in the power transmission line galloping amplitude detection device can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 8. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer equipment is used for storing the image to be detected of the target transmission line, which is obtained by shooting by the camera. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor is to implement a method of transmission line galloping amplitude detection.
It will be appreciated by those skilled in the art that the structure shown in FIG. 8 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A method for detecting the amplitude of a galloping of a power transmission line, the method comprising:
after a camera continuously shoots a target power transmission line to obtain a plurality of continuous images to be detected, acquiring the continuous images to be detected;
extracting a characteristic part area in the image to be detected, and extracting characteristic points in the characteristic part area;
determining characteristic distances between the characteristic points and the target power transmission line in the plurality of images to be detected;
determining the galloping amplitude of the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected;
wherein the extracting the feature component area in the image to be detected includes:
carrying out gray level quantization on pixel values of all pixel points of the image to be detected to obtain gray values of all pixel points;
constructing a network topology graph of the image to be detected according to the gray value of each pixel point; wherein each pixel point is used as a network node in the network topology graph, and a connecting line of each adjacent pixel point is used as an initial network edge in the network topology graph;
determining the edge weight of each initial network edge according to the gray value of each pixel point;
and removing the initial network edge with the edge weight smaller than a preset weight threshold to obtain a plurality of final network edges, and connecting the adjacent final network edges to obtain the characteristic component area.
2. The method of claim 1, wherein the extracting feature points in the feature region comprises:
extracting effective pixel points in the characteristic component area;
and connecting adjacent effective pixel points to form a feature communication area, and extracting each pixel point in the feature communication area as the feature point.
3. The method of claim 2, wherein the extracting valid pixel points in the feature area comprises:
determining a preset gray threshold value of each pixel point of the characteristic component area;
and carrying out iterative search on the pixel points in the characteristic component area, and taking the pixel points with the gray values larger than the preset gray threshold value as effective pixel points.
4. The method of claim 1, wherein the step of determining the position of the substrate comprises,
and determining the characteristic distance between each characteristic point in the plurality of images to be detected and the target power transmission line by carrying out depth estimation on the images to be detected.
5. The method according to claim 1, wherein the determining the galloping amplitude of the target transmission line according to the difference in the characteristic distances in the adjacent images to be detected includes:
determining the actual displacement distance of a corresponding line section in the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected, the depth of the camera and the focal length of the camera;
and determining the galloping amplitude of the target power transmission line according to the actual displacement distance.
6. The method of claim 5, wherein said determining the galloping amplitude of the target transmission line from the actual displacement distance comprises:
acquiring adjacent image shooting time intervals to be detected;
and determining the galloping amplitude of the target power transmission line according to the actual displacement distance and the time interval.
7. A transmission line galloping amplitude detection device, the device comprising:
the image acquisition module is used for acquiring continuous images to be detected after the camera continuously shoots the target power transmission line to obtain a plurality of continuous images to be detected;
the feature extraction module is used for extracting feature component areas in the image to be detected and extracting feature points in the feature component areas;
the distance determining module is used for determining characteristic distances between the characteristic points and the target power transmission line in the plurality of images to be detected;
the galloping amplitude determining module is used for determining the galloping amplitude of the target power transmission line according to the difference value of the characteristic distances in the adjacent images to be detected;
the feature extraction module is further configured to perform gray level quantization on pixel values of each pixel point of the image to be detected, so as to obtain a gray value of each pixel point; constructing a network topology graph of the image to be detected according to the gray value of each pixel point; wherein each pixel point is used as a network node in the network topology graph, and a connecting line of each adjacent pixel point is used as an initial network edge in the network topology graph; determining the edge weight of each initial network edge according to the gray value of each pixel point; and removing the initial network edge with the edge weight smaller than a preset weight threshold to obtain a plurality of final network edges, and connecting the adjacent final network edges to obtain the characteristic component area.
8. The transmission line galloping amplitude detection device of claim 7, wherein the feature extraction module is further configured to extract valid pixel points in the feature area; and connecting adjacent effective pixel points to form a feature communication area, and extracting each pixel point in the feature communication area as the feature point.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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