Intelligent operation and maintenance system for power transmission line
By constructing an intelligent operation and maintenance system for power transmission lines, and utilizing image acquisition and simulation modules for real-time status mapping and anomaly detection, the problems of manpower shortage and data dispersion in the traditional operation and maintenance model have been solved, achieving efficient and accurate operation and maintenance results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-20
- Publication Date
- 2026-04-03
AI Technical Summary
The existing operation and maintenance model for transmission lines requires a large amount of human resources, and the online monitoring system suffers from problems such as messy and scattered data and a lack of unified analysis and processing, resulting in poor operation and maintenance effectiveness.
By employing image acquisition equipment, image preprocessing module, image fusion module, 3D simulation module, intelligent analysis module, and processing module, combined with wireless transmission, virtual reality, 3D maps, digital twin semantic maps, and cloud computing technologies, a simulation model of the transmission line is constructed to perform real-time status mapping and anomaly detection, and automatically generate maintenance plans.
It has achieved precise and efficient operation and maintenance of transmission lines. By combining intelligent analysis with manual re-inspection, it has improved the accuracy of anomaly identification and the rationality of maintenance plans, while reducing the demand for human resources and operation and maintenance time.
Smart Images
Figure CN121788884A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of power transmission line operation and maintenance management technology, and specifically relates to an intelligent operation and maintenance system for power transmission lines. Background Technology
[0002] Power line inspection is a fundamental task for ensuring the safety of transmission lines and equipment. The process involves workers using their eyes, telescopes, and other tools and instruments to observe, inspect, and measure various components of the transmission lines. The aim is to understand the line's operational status, promptly identify equipment defects, and identify potential threats to line safety. Currently, traditional operation and maintenance (O&M) models often require a large investment of human resources to concentrate on O&M, repair, and power supply maintenance. With the rapid development of the power grid, the shortage of professional human resources, and the increasingly harsh external O&M environment, the contradiction between the original O&M model and the rapidly growing power grid scale is becoming increasingly prominent, and the effectiveness of O&M urgently needs to be significantly improved. Even though the State Grid has now widely introduced online monitoring systems that can replace manual on-site inspections, the problems of scattered and disorganized data collection and a lack of unified analysis and processing still exist. Therefore, to solve these problems, it is necessary to develop a precise, efficient, time-saving, and convenient intelligent O&M system for transmission lines. Summary of the Invention
[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a precise, efficient, time-saving and convenient intelligent operation and maintenance system for power transmission lines.
[0004] The objective of this invention is achieved as follows: an intelligent operation and maintenance system for power transmission lines, comprising an image acquisition device, an image preprocessing module, an image fusion module, a three-dimensional simulation module, an intelligent analysis module, a processing module, and a work order generation module. The image acquisition device is used to capture and collect the operating status information of the power transmission lines. It is equipped with a wireless transmission unit, which can be used to transmit the captured images and video information in real time. The image preprocessing module is used to preprocess the received images and video data to form the original image data. The image fusion module fuses images based on comprehensive background and detailed features to form a preliminary fused image. Then, wavelet downsampling and wavelet upsampling are performed on the preliminary fused image in sequence to obtain the final fused image. The 3D simulation module sets a safety distance based on the field strength distribution pattern of the transmission line. Then, based on the safety distance and the final fused image, it uses virtual reality, 3D map technology, digital twin semantic map, and cloud computing edge computing technology to construct a simulation model of the transmission line and map the state of the transmission line in real time. The intelligent analysis module obtains the corresponding attention weight matrix from the final fused image and performs weighted calculations using the attention weight matrix to obtain visual feature data. Then, based on the simulation model, it backtracks historical data and compares and analyzes data from multiple time periods to detect the operating status and appearance information of the transmission line. When an anomaly is detected in the transmission line, the anomaly point of the transmission line is marked in the simulation model through the marking unit. After the marking is completed, the fused image and original image data corresponding to the anomaly point are extracted. The processing module, based on the anomaly points marked on the simulation model, as well as the fused images and original image data corresponding to the anomaly points, performs fault identification and analysis, finds the fault source, the cause of the fault, and the fault propagation path, and matches the historical maintenance database to automatically generate maintenance and treatment plans. Then, while triggering the warning module to issue a warning signal, the maintenance and treatment plan is integrated with the fused images and original image data and transmitted to the control terminal for manual re-inspection. The work order generation module can generate a final maintenance work order based on the maintenance solution after manual re-inspection is completed, and then dispatch the final maintenance work order to the mobile terminal of the operation and maintenance personnel.
[0005] Furthermore, the image acquisition device includes any one or more combinations of a fixed-position camera, a drone, and a handheld mobile camera.
[0006] Furthermore, the preprocessing operation of the images and video data specifically involves performing multi-dimensional attribute processing on each image according to pre-set standards, wherein the multi-dimensional attributes include image sharpness, image contrast, image noise variance, image distortion coefficient, image color uniformity, and image size ratio.
[0007] Furthermore, the image acquisition device is equipped with a marking unit, which can be used to mark the time and location information of the images and videos captured by the image acquisition device.
[0008] Furthermore, the aforementioned 3D simulation module employs a stream computing framework to process real-time video streams and synchronously analyze video sources.
[0009] The beneficial effects of this invention are as follows: By setting up an image acquisition device, this invention can capture and transmit real-time information on the operating status of power transmission lines; by setting up an image preprocessing module and an image fusion module, the acquired images and video data can be preprocessed and fused to obtain the final fused image; by setting up a 3D simulation module, based on the safety distance and the final fused image, a simulation model of the power transmission line can be constructed using virtual reality, 3D map technology, digital twin semantic maps, and cloud computing edge computing technology to map the status of the power transmission line in real time; this invention, with its structure, has the advantages of safety, convenience, time-saving, and high efficiency compared to the traditional manual operation and maintenance mode. This invention, through the establishment of an intelligent analysis module, can detect the operating status and appearance information of transmission lines by retrospectively analyzing historical data and comparing multiple time periods based on a simulation model. When an anomaly is detected in the transmission line, the anomaly point is marked in the simulation model by a marking unit, and the corresponding fused image and original image data are extracted. Through the establishment of a processing module, based on the anomaly points marked on the simulation model, and the corresponding fused image and original image data, fault identification analysis is performed to find the fault source, cause of the fault, and fault propagation path. Simultaneously, it matches the historical maintenance database to automatically generate a maintenance plan. Subsequently, while triggering the warning module to issue a warning signal, the maintenance plan is integrated with the fused image and original image data and transmitted to the control terminal for manual re-inspection. This invention, by combining intelligent analysis and processing with manual re-inspection, increases the accuracy of anomaly point identification and the rationality of maintenance plans. In summary, this invention has the advantages of accuracy, efficiency, time-saving, and convenience. Attached Figure Description
[0010] Figure 1 This is a flowchart illustrating the structure of the present invention. Detailed Implementation
[0011] The present invention will now be further described with reference to the accompanying drawings.
[0012] Example: Figure 1As shown, an intelligent operation and maintenance system for power transmission lines includes an image acquisition device, an image preprocessing module, an image fusion module, a 3D simulation module, an intelligent analysis module, a processing module, and a work order generation module. The image acquisition device is used to capture and collect operational status information of the power transmission lines. It is equipped with a wireless transmission unit, which allows for real-time transmission of the acquired images and videos. The image acquisition device can include any one or more combinations of fixed-position cameras, drones, and handheld mobile cameras. Furthermore, the image acquisition device is equipped with a marking unit, which can be used to mark the images and videos captured by the device with time and location information. The image preprocessing module is used to preprocess the received image and video data to form the original image data. In this process, the preprocessing operation of the image and video data is as follows: each image is processed for multi-dimensional attributes according to the preset standards. The multi-dimensional attributes include image sharpness, image contrast, image noise variance, image distortion coefficient, image color uniformity and image size ratio. The image fusion module fuses images based on comprehensive background and detailed features to form a preliminary fused image. Then, wavelet downsampling and wavelet upsampling are performed on the preliminary fused image in sequence to obtain the final fused image. The 3D simulation module sets a safe distance based on the field strength distribution pattern of the transmission line. Then, based on the safe distance and the final fused image, it constructs a simulation model of the transmission line using virtual reality, 3D mapping technology, digital twin semantic maps, and cloud computing edge computing technology, which maps the state of the transmission line in real time. During this process, the 3D simulation module uses a stream computing framework to process real-time video streams and analyzes the video source synchronously. The intelligent analysis module obtains the corresponding attention weight matrix from the final fused image and performs weighted calculations using the attention weight matrix to obtain visual feature data. Then, based on the simulation model, it backtracks historical data and compares and analyzes data from multiple time periods to detect the operating status and appearance information of the transmission line. When an anomaly is detected in the transmission line, the anomaly point of the transmission line is marked in the simulation model through the marking unit. After the marking is completed, the fused image and original image data corresponding to the anomaly point are extracted. The processing module, based on the anomaly points marked on the simulation model, as well as the fused images and original image data corresponding to the anomaly points, performs fault identification and analysis, finds the fault source, the cause of the fault, and the fault propagation path, and matches the historical maintenance database to automatically generate maintenance and treatment plans. Then, while triggering the warning module to issue a warning signal, the maintenance and treatment plan is integrated with the fused images and original image data and transmitted to the control terminal for manual re-inspection. The work order generation module can generate a final maintenance work order based on the maintenance solution after manual re-inspection is completed, and then dispatch the final maintenance work order to the mobile terminal of the operation and maintenance personnel.
[0013] In use, this invention first captures and collects information on the operational status of power transmission lines using an image acquisition device comprised of one or more combinations of a fixed-position camera, a drone, or a handheld mobile camera. During the acquisition process, a marking unit marks the captured images and videos with time and location information. After acquisition, the captured images and videos are transmitted in real time via a wireless transmission unit. Then, an image preprocessing module processes the captured images and videos according to pre-set standards to perform multi-dimensional attribute processing, thereby forming the original image data. These multi-dimensional attributes include image clarity, image quality, and other properties. The system considers factors such as contrast, image noise variance, image distortion coefficients, image color uniformity, and image size ratio. Then, based on the comprehensive background and detail features of the image, an image fusion module fuses the images to form a preliminary fused image. Subsequently, wavelet downsampling and wavelet upsampling are performed on the preliminary fused image to obtain the final fused image. Finally, a safety distance is set based on the field strength distribution of the transmission line. Based on this safety distance, a 3D simulation module uses the final fused image and employs virtual reality, 3D mapping technology, digital twin semantic maps, and cloud computing edge computing technologies to construct a simulation model of the transmission line, mapping the transmission line in real time. Status; After completing the above operations, the intelligent analysis module, based on the simulation model, backtracks historical data and compares and analyzes multiple time periods to detect the operating status and appearance information of the transmission line. When an anomaly is detected in the transmission line, the marking unit is used to mark the abnormal points of the transmission line in the simulation model. After the marking is completed, the fused image and original image data corresponding to the abnormal point are extracted. Finally, based on the anomaly points marked on the simulation model, as well as the fused image and original image data corresponding to the anomaly points, the processing module performs fault identification analysis to find the fault source, the cause of the fault, and the fault propagation path. At the same time, it matches the historical maintenance database and automatically generates inspection reports. The invention employs a repair and processing plan. Subsequently, while triggering an alarm module to issue a warning signal, the repair and processing plan is integrated with the fused image and original video data, and transmitted to the control terminal for manual re-inspection. After the manual re-inspection is passed, a final maintenance work order is generated based on the repair and processing plan using the work order generation module, and then dispatched to the mobile terminal of the maintenance personnel. This structure, compared to the traditional manual operation and maintenance mode, offers advantages such as safety, convenience, time-saving, and high efficiency. Furthermore, by combining intelligent analysis and processing with manual re-inspection, this invention increases the accuracy of anomaly identification and the rationality of the repair and processing plan. In summary, this invention offers the advantages of accuracy, efficiency, time-saving, and convenience.
[0014] The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.
Claims
1. A smart operation and maintenance system for transmission lines, comprising an image acquisition device, an image preprocessing module, an image fusion module, a 3D simulation module, an intelligent analysis module, a processing module, and a work order generation module, characterized in that: The image acquisition device is used to capture and collect information on the operating status of power transmission lines. It is equipped with a wireless transmission unit, which can be used to transmit the captured images and videos in real time. The image preprocessing module is used to preprocess the received images and video data to form the original image data. The image fusion module fuses images based on comprehensive background and detailed features to form a preliminary fused image. Then, wavelet downsampling and wavelet upsampling are performed on the preliminary fused image in sequence to obtain the final fused image. The 3D simulation module sets a safety distance based on the field strength distribution pattern of the transmission line. Then, based on the safety distance and the final fused image, it uses virtual reality, 3D map technology, digital twin semantic map, and cloud computing edge computing technology to construct a simulation model of the transmission line and map the state of the transmission line in real time. The intelligent analysis module obtains the corresponding attention weight matrix from the final fused image and performs weighted calculations using the attention weight matrix to obtain visual feature data. Then, based on the simulation model, it backtracks historical data and compares and analyzes data from multiple time periods to detect the operating status and appearance information of the transmission line. When an anomaly is detected in the transmission line, the anomaly point of the transmission line is marked in the simulation model through the marking unit. After the marking is completed, the fused image and original image data corresponding to the anomaly point are extracted. The processing module, based on the anomaly points marked on the simulation model, as well as the fused images and original image data corresponding to the anomaly points, performs fault identification and analysis, finds the fault source, the cause of the fault, and the fault propagation path, and matches the historical maintenance database to automatically generate maintenance and treatment plans. Then, while triggering the warning module to issue a warning signal, the maintenance and treatment plan is integrated with the fused images and original image data and transmitted to the control terminal for manual re-inspection. The work order generation module can generate a final maintenance work order based on the maintenance solution after manual re-inspection is completed, and then dispatch the final maintenance work order to the mobile terminal of the operation and maintenance personnel.
2. The intelligent operation and maintenance system for transmission lines as described in claim 1, characterized in that: The image acquisition device includes any one or more combinations of fixed-position cameras, drones, and handheld mobile cameras.
3. The intelligent operation and maintenance system for transmission lines as described in claim 1, characterized in that: The preprocessing of the images and video data specifically involves performing multi-dimensional attribute processing on each image according to pre-set standards. These multi-dimensional attributes include image sharpness, image contrast, image noise variance, image distortion coefficient, image color uniformity, and image size ratio.
4. The intelligent operation and maintenance system for transmission lines as described in claim 1, characterized in that: The image acquisition device is equipped with a marking unit, which can be used to mark the time and location information of the images and videos captured by the image acquisition device.
5. The intelligent operation and maintenance system for transmission lines as described in claim 1, characterized in that: The 3D simulation module uses a stream computing framework to process real-time video streams and simultaneously analyze the video source.