CN113096146A - Power transmission line icing monitoring and early warning system, installation equipment and method based on 5G and AI identification technology - Google Patents
Power transmission line icing monitoring and early warning system, installation equipment and method based on 5G and AI identification technology Download PDFInfo
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Abstract
The invention discloses a power transmission line icing monitoring and early warning system and method based on 5G and AI identification technologies, wherein deep research is carried out on power grid icing data by means of deep learning, AI identification and the like, icing spatial-temporal distribution characteristics are deeply excavated, a line icing image identification sample library is constructed, the AI technology is utilized to research icing types and icing thickness image intelligent identification, a power grid equipment icing margin evaluation model based on a multi-physical field simulation technology is constructed, refined icing intelligent prediction is realized based on historical icing rules, basic science of power grid icing safety is broken through, verification demonstration is carried out, and the accuracy and real-time performance of monitoring and early warning are integrally improved.
Description
Technical Field
The invention relates to the technical field of power transmission lines, in particular to a power transmission line icing monitoring and early warning system and method based on 5G and AI identification technologies, and further relates to installation equipment.
Background
The power transmission line icing monitoring model plays a role in calculating the icing thickness of the power transmission line, is a core part of an online power transmission line icing monitoring system and is a prerequisite for determining the icing prediction accuracy, at present, a power grid mainly selects an icing monitoring terminal to distribute points according to faults of the power transmission line caused by icing in the past year or data selection according to an icing result, and spatial distribution correlation analysis is not performed on ice-melting line data and ice-coating monitoring terminal data. The existing ice coating monitoring and early warning system mainly collects tension data of a power transmission line, surrounding meteorological information and video picture information and transmits the data to a rear-end platform through an 2/4G public network of an operator.
The prior art has the defects that:
1. at the present stage, pictures can only be uploaded discontinuously through a public network of an operator, the icing condition cannot be reflected visually, and the icing condition needs to be analyzed by uploading continuous images by utilizing the advantages of a 5G network.
2. In the future, the monitoring and early warning service of the power transmission line develops towards fusion, so that the data types are more, the data volume is larger, and the real-time requirement on data transmission is higher.
Disclosure of Invention
In view of the above, the first aspect of the present invention is to provide a power transmission line icing monitoring and early warning system based on 5G and AI identification technologies. Can overcome the defects in the prior art.
The purpose of the first aspect of the invention is realized by the following technical scheme:
the power transmission line icing monitoring and early warning system based on 5G and AI identification technology comprises
The image monitoring module is used for segmenting the images in the icing state and the images in the non-icing state, extracting icing edge information and analyzing and processing differential information;
the image acquisition module is used for processing and analyzing bare wires in a shooting range to acquire corresponding shooting parameters, wherein the shooting parameters are an image scale coefficient and an image inclination angle;
the edge calculation module is used for receiving the image data transmitted by the image acquisition module, removing redundant information of the image data and analyzing and transferring part or all of the image data to the edge;
the image analysis module receives the preprocessed image data transmitted by the edge calculation module and utilizes the AI model to complete intelligent identification of the icing type and the icing thickness image;
and the intelligent terminal is used for receiving the analysis result sent by the image analysis module.
Further, the edge calculation module removes redundant information of video images by using a video preprocessing module based on a wireless transmission network, so that part or all of video analysis is migrated to the edge;
and the edge preprocessing module is utilized to realize the elastic storage of the video data, and the video data is adjusted in real time according to the behavior characteristic decision function.
Further, the edge calculation module further comprises a model calculation module that integrates a hardware unit with calculation capability into the front end.
Furthermore, the image analysis module is connected with a sample library, and the sample library is used for storing the images and data processed by the image analysis module, so that later calling and comparison are facilitated, and the identification efficiency is improved.
The second aspect of the invention aims to provide a power transmission line icing monitoring and early warning method based on 5G and AI identification technologies, which comprises the following steps:
step S1: determining a shooting position, monitoring the power transmission line in real time through an image monitoring module, then continuously acquiring images of the power transmission line state through an image acquisition module, and transmitting the acquired images and image data processed by the image monitoring module to an edge calculation module through a wireless transmission network;
step S2: preprocessing the transmitted image and data by utilizing an edge calculation module;
step S3: the ice coating type and ice coating thickness images are intelligently identified by utilizing an image analysis module based on an AI technology, a power grid equipment anti-icing margin evaluation model based on a multi-physics simulation technology is constructed, and then an analysis result is transmitted to an intelligent terminal.
Further, in step S2, the preprocessing includes removing redundant information of the video image by using a video preprocessing technique, so that part or all of the video analysis is migrated to the edge, thereby reducing the calculation, storage and network bandwidth requirements of the data center and improving the efficiency of the video image analysis; and finally, integrating a hardware unit with computing capability to the front end by utilizing a model computing technology, thereby realizing the novel video monitoring system with edge computing capability.
Furthermore, a sample library is further arranged, images and data processed by the image analysis module are stored, calling and comparison in the later period are facilitated, and the identification efficiency is improved.
The third aspect of the invention aims to provide a transmission line icing monitoring and installing device based on 5G and AI identification technologies, which is realized by the following technical scheme:
this transmission line icing control erection equipment based on 5G and AI identification technology, including the base, base top fixedly connected with boss, boss top fixedly connected with function box, the equal fixedly connected with fixed block in function box both sides, the equal fixedly connected with image acquisition module in the fixed block outside, a plurality of first screw holes have been seted up at the base top, the second screw hole has all been seted up at base rear side both ends, be provided with image monitoring module, edge calculation module and image analysis module in the function box.
Further, the outside cover of image acquisition module is equipped with the protective housing, protective housing one side and fixed block fixed connection.
The invention has the beneficial effects that:
1. according to the power transmission line icing monitoring and early warning system and method based on the 5G and AI identification technologies, deep research is carried out on power grid icing data by means of deep learning, AI identification and the like, icing space-time distribution characteristics are deeply excavated, a line icing image identification sample library is constructed, icing types and icing thickness image intelligent identification are researched by means of the AI technology, a power grid equipment icing margin evaluation model based on a multi-physics field simulation technology is constructed, refined icing intelligent prediction is realized based on a historical icing rule, a power grid icing safety basic science is broken through, verification demonstration is carried out, and the accuracy and the real-time performance of monitoring and early warning are integrally improved.
2. This transmission line icing monitoring and early warning system erection equipment based on 5G and AI identification technology can reach the fixed purpose that reaches that can the correspondence according to the angle of installation and position difference through utilizing setting up of first screw hole and second screw hole, improves fixed suitability.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the present invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram of the system of the present invention;
FIG. 2 is a unit diagram of the present invention;
FIG. 3 is a schematic view of the overall structure of the present invention;
fig. 4 is a rear view of the present invention.
In the figure: 1. an image monitoring module; 2. an image acquisition module; 3. an edge calculation module; 4. a sample library; 5. an image analysis module; 6. an APP mobile phone terminal; 7. a video pre-processing module; 8. an edge preprocessing module; 9. a model calculation technique; 10. a camera; 11. a protective shell; 12. a fixed block; 13. a function box; 14. a boss; 15. a first threaded hole; 16. a base; 17. and a second threaded hole.
Detailed Description
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the preferred embodiments are illustrative of the invention only and are not limiting upon the scope of the invention.
As shown in fig. 1 and 2, the power transmission line icing monitoring and early warning system based on the 5G and AI identification technology of the present invention includes an image monitoring module 1, wherein the image monitoring module 1 is configured to perform image processing, segment an image in an icing state and an image in a non-icing state, extract icing edge information, and analyze and process differential information, so as to obtain the current icing thicknesses of a line and an insulator;
image monitoring module 1 with image acquisition module 2 electric connection, image acquisition module 2 adopts the camera as main shooting tool in this embodiment for to the bare wire in the shooting range handles the analysis, acquires corresponding shooting parameter, the shooting parameter is image proportionality coefficient and image inclination.
The output end of the image acquisition module 2 is fixedly provided with an edge calculation module 3, the edge calculation module 3 removes redundant information of video images by using a video preprocessing module 7 based on a 5G transmission network, so that part or all of video analysis is migrated to the edge, the requirements on calculation, storage and network bandwidth of a data center are reduced, the efficiency of video image analysis is improved, and the edge preprocessing module 8 is used for realizing elastic storage of video data. According to the behavior characteristic decision function, video data are adjusted in real time, so that the storage of invalid videos is reduced, the storage space is reduced, the 'in-the-fact' evidence video data are stored to the maximum extent, and the utilization rate of the storage space of the video data is improved; in this embodiment, the edge calculation module 3 includes a video preprocessing module 7, an edge preprocessing module 8, and a model calculation module 9, where the model calculation module 9 integrates a hardware unit with calculation capability into a front end based on an advanced wireless transmission technology (such as 5G transmission technology) by using a model calculation cardinal number, so as to implement a novel video monitoring system with edge calculation capability. In edge calculation models, the calculation typically occurs near the data source, i.e., at the edge of the video data acquisition where the video data is processed. On one hand, the preprocessing function module based on the intelligent algorithm executes fuzzy calculation and executes partial or all calculation tasks on the video data acquired in real time, so that timely response service can be provided for application requests with higher real-time requirements; on the other hand, a telescopic elastic storage function module is designed, and the intelligent algorithm is utilized to sense the image change in the monitoring scene, so that higher space storage efficiency is realized.
Further, an image analysis module 5 is fixedly arranged at the output end of the edge calculation module 3, the image analysis module 5 utilizes an AI model to research the ice coating type and ice coating thickness image intelligent identification, a power grid equipment ice-protection margin evaluation model based on a multi-physics simulation technology is constructed, the refined ice coating intelligent prediction is realized based on the historical ice coating rule, the power grid ice coating safety basic science is broken through, and verification demonstration is carried out;
Further, a sample library 4 is fixedly arranged at the connecting end of the image analysis module 5, and the sample library 4 is used for storing images and data processed by the image analysis module 5, so that later-stage calling and comparison are facilitated, and the identification efficiency is improved.
According to the invention, as shown in fig. 3 and 4, the ice coating monitoring and early warning installation equipment for the power transmission line based on the 5G and AI identification technology comprises a base 16, wherein a boss 14 is fixedly connected to the top of the base 16, a function box 13 is fixedly connected to the top of the boss 14, fixed blocks 12 are fixedly connected to two sides of the function box 13, cameras 10 are fixedly connected to the outer sides of the two fixed blocks 12, a protective shell 11 is sleeved on the outer side of each camera 10, one side of each protective shell 11 is fixedly connected with the corresponding fixed block 12, a plurality of first threaded holes 15 are formed in the top of the base 16, and second threaded holes 17 are formed in two. The function box is provided with an image monitoring module, an edge calculating module and an image analyzing module.
The working principle is as follows: in the use of the invention, the main components in the system can be fixed at a reasonable shooting position by the first threaded hole 15, the base 16 and the second threaded hole 17, then, images of the power transmission line state are continuously acquired by the aid of the camera 10, the transmitted images and data are preprocessed by the aid of the edge computing module 3, the images are elastically stored by the edge preprocessing module 8 to improve the utilization rate of a video data storage space, finally, a hardware unit with computing capacity is integrated to the front end by the aid of the model computing module 9, a novel video monitoring system with edge computing capacity is achieved, ice coating types and ice coating thickness images are intelligently identified by the aid of the image analysis module 5 based on AI technology, a power grid equipment ice prevention margin evaluation model based on multi-physics field simulation technology is built, and analysis results are transmitted to the intelligent terminal 6.
Based on the system, the invention discloses a power transmission line icing monitoring and early warning method based on 5G and AI identification technologies, which comprises the following steps:
step S1: determining a shooting position, monitoring the power transmission line in real time through an image monitoring module, then continuously acquiring images of the power transmission line state through an image acquisition module, and transmitting the acquired images and image data processed by the image monitoring module to an edge calculation module through a wireless transmission network;
step S2: preprocessing the transmitted image by utilizing an edge calculation module; the preprocessing comprises the steps of removing redundant information of video images by utilizing a video preprocessing technology, so that part or all of video analysis is migrated to the edge, thereby reducing the requirements on calculation, storage and network bandwidth of a data center and improving the efficiency of video image analysis; utilizing an edge preprocessing technology to perform elastic storage on the image so as to improve the utilization rate of a video data storage space, and finally utilizing a model calculation technology to integrate a hardware unit with calculation capability into a front end;
step S3: the ice coating type and ice coating thickness images are intelligently identified by utilizing an image analysis module based on an AI technology, a power grid equipment anti-icing margin evaluation model based on a multi-physics simulation technology is constructed, and then an analysis result is transmitted to an intelligent terminal.
In the description of the present invention, it is to be understood that the terms "longitudinal," "length," "circumferential," "front," "rear," "left," "right," "top," "bottom," "inner," "outer," and the like are used in the orientations and positional relationships indicated in the drawings for the convenience of description and simplicity of description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed in a particular orientation, and be operated, and thus are not to be construed as limiting the present invention.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically connected, electrically connected or can communicate with each other; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Finally, the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all of them should be covered by the claims of the present invention.
Claims (9)
1. The utility model provides a transmission line icing monitoring and early warning system based on 5G and AI identification technology which characterized in that: comprises that
The image monitoring module (1) is used for segmenting an image in an icing state and an image in a non-icing state, extracting icing edge information and analyzing and processing differential information;
the image acquisition module (2) is used for processing and analyzing bare wires in a shooting range to obtain corresponding shooting parameters, wherein the shooting parameters are an image scale coefficient and an image inclination angle;
the edge calculation module (3) is used for receiving the image data transmitted by the image acquisition module and removing redundant information of the image data so that part or all of the image data is analyzed and transferred to the edge;
the image analysis module (5) receives the preprocessed image data transmitted by the edge calculation module and utilizes the AI model to complete intelligent identification of the icing type and the icing thickness image;
and the intelligent terminal (6) is used for receiving the analysis result sent by the image analysis module.
2. The power transmission line icing monitoring and early warning system and method based on 5G and AI identification technology according to claim 1, characterized in that: the edge calculation module removes redundant information of video images by using a video preprocessing module (7) based on a wireless transmission network, so that part or all of video analysis is migrated to the edge;
and the elastic storage of the video data is realized by utilizing an edge preprocessing module (8), and the video data is adjusted in real time according to a behavior characteristic decision function.
3. The power transmission line icing monitoring and early warning method based on 5G and AI identification technology according to claim 2, characterized in that: the edge calculation module (3) further comprises a model calculation module integrating a hardware unit with computing power into the front end.
4. The power transmission line icing monitoring and early warning method based on 5G and AI identification technology according to claim 1, characterized in that: the image analysis module is connected with a sample library (4), and the sample library is used for storing pictures and data processed by the image analysis module, so that later-stage calling and comparison are facilitated, and the identification efficiency is improved.
5. A power transmission line icing monitoring and early warning method based on 5G and AI identification technology is characterized in that: the method comprises the following steps:
step S1: determining a shooting position, monitoring the power transmission line in real time through an image monitoring module, then continuously acquiring images of the power transmission line state through an image acquisition module, and transmitting the acquired images and the images processed by the image monitoring module to an edge calculation module through a wireless transmission network;
step S2: preprocessing the transmitted image and data by utilizing an edge calculation module;
step S3: the ice coating type and ice coating thickness images are intelligently identified by utilizing an image analysis module based on an AI technology, a power grid equipment anti-icing margin evaluation model based on a multi-physics simulation technology is constructed, and then an analysis result is transmitted to an intelligent terminal.
6. The power transmission line icing monitoring and early warning method based on 5G and AI identification technology according to claim 5, characterized in that: in step S2, the preprocessing includes removing redundant information of the video image by using a video preprocessing technique, so that part or all of the video analysis is migrated to the edge, thereby reducing the calculation, storage and network bandwidth requirements of the data center and improving the efficiency of the video image analysis; and finally, integrating a hardware unit with computing capability to the front end by utilizing a model computing technology, thereby realizing the novel video monitoring system with edge computing capability.
7. The power transmission line icing monitoring and early warning method based on 5G and AI identification technology according to claim 5, characterized in that: the image analysis module is used for processing the images and the data, and storing the images and the data.
8. The utility model provides a transmission line icing monitoring erection equipment based on 5G and AI identification technique which characterized in that: including base (16), base top fixedly connected with boss (14), boss top fixedly connected with function box (13), the equal fixedly connected with fixed block (12) in function box both sides, the equal fixedly connected with image acquisition module (10) in the fixed block outside, a plurality of first screw holes (15) have been seted up at the base top, second screw hole (17) have all been seted up at base rear side both ends, be provided with image monitoring module (1), edge calculation module (3) and image analysis module (5) in the function box.
9. The transmission line icing monitoring and installing equipment based on 5G and AI identification technology of claim 8, wherein: the outside cover of image acquisition module is equipped with protective housing (11), protective housing (11) one side and fixed block (12) fixed connection.
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