Transmission line construction progress monitoring is critical for grid security control. This study proposed a method of using satellite remote sensing and UAV technology for transmission line construction progress detection and unplanned operation troubleshooting in response to the challenge of controlling unplanned operation problems in transmission line construction operations. The study utilized satellite remote sensing technology to obtain high-resolution images of the transmission line construction operation site, and combined with intelligent recognition algorithms, it realized the automatic identification and status monitoring of typical phases such as foundation construction, tower formation construction and wire erection construction. By intelligently comparing with the progress of the operation plan, the method in this paper can realize the accurate investigation and early warning of unplanned operation, which improves the lean management level of construction safety. In addition, this study also designed the core functions of the transmission line progress management system, including data acquisition, processing, analysis, display and early warning, etc., which provided strong support for the monitoring of on-site operations of transmission and substation projects. This study not only solved the limitations of traditional control means in transmission line construction operations, but also provided an important guarantee for the safe and stable supply of electricity.
The Green Plastic Cover (GPC) around power transmission towers is one of the main external hazards to power transmission lines, and conducting remote sensing identification of GPC is of great significance for the management of external hazards to power transmission lines. Existing remote sensing identification studies mainly focus on plastic greenhouses and plastic mulches, with relatively few studies on GPC, especially in areas around power transmission towers. Consequently, this research selected four areas along transmission corridors in Jiangsu Province as a case study to boost GPC mapping performance through integrating the focal loss function into the TransUNet model using Sentinel-1 and Sentinel-2 data, and subsequently conducting with the U-Net model and Deeplabv3+ model for comparative experiment to validate the superiority of the model selected in this study. The experimental results demonstrated that the TransUNet model performs well in extracting GPC, with Precision, Recall, IoU and F1 values reaching 82.24%, 92.38%, 77.01% and 0.87, respectively. It is feasible and effective to utilize the model in this paper to identify GPC along transmission corridors, which can provide a decision-making basis for the comprehensive management of the risk of external damage.
With the development of smart grid, the requirements for real-time monitoring of transmission line operation status are increasing. However, the on-line energy supply for monitoring equipment has always been a problem for high-voltage transmission lines. This paper analyzes the physical and circuit models of various energy extraction methods in typical high-voltage transmission lines, such as electrostatic field energy harvesting, vortex electric field energy harvesting and magnetic field energy harvesting. Maximum energy harvesting power is also calculated. The results show that CT energy harvesting of wire and electrostatic induction energy harvesting of sectionalized ground wire has the highest energy harvesting power. Meanwhile, the energy harvesting power, operation reliability and engineering implementation of different energy harvesting methods are also compared. The results show that the energy extraction method with lower power level has better performance in the aspects of operation reliability and engineering implementation, and vice versa.
Guizhou Province, situated in the southwest of China, boasts diverse and complex geographical environments and abundant forest resources. However, it faces threats from natural disasters like forest fires. Accurate estimation of combustible fuel load in Guizhou is crucial for assessing fire risks and implementing effective fire management strategies. This paper employs remote sensing technology, utilizing various remote sensing datasets including satellite imagery and ground observation data, combined with geostatistical methods to retrieve combustible fuel load in Guizhou. Furthermore, the application value of the retrieval results in fire prevention management and forest resource protection is discussed.
KEYWORDS: Point clouds, LIDAR, Data transmission, Inspection, 3D modeling, Remote sensing, Data modeling, Optical transmission, 3D image processing, Laser scanners
Facing the extraction of hidden danger information of external breakage to transmission lines, we first introduce lidar and optical remote sensing image data acquisition, processing, and information extraction technologies, then analyze the characteristics of transmission corridors obtained by these two sensing methods, and summarize their respective advantages and disadvantages. On this basis, we propose a method for external breakage hidden danger information of transmission lines by combining remote sensing images and LiDAR point clouds. This method can simultaneously acquire the texture and spatial three-dimensional data of the external breakage target in the transmission corridor, and form high-quality spatial three-dimensional model data, which is conducive to the effective identification and accurate extraction of external breakage hidden danger.
Wind-induced deflection of overhead transmission line is a phenomenon of conductor non-synchronous swing caused by strong wind. Serious wind deflection will cause flashover and lead to line trip. It is of great significance to strengthen the monitoring of wind deflection of transmission line insulator. For transmission lines located in cold and strong wind areas, due to the need for on-site power supply, the long-term operation reliability of monitoring devices in low temperature environment is difficult to ensure. The monitoring scheme based on Fiber Bragg grating technology has the advantages of no on-site power supply, anti-electromagnetic interference and good insulation performance. It has a good application prospect in wind deflection monitoring of transmission lines in cold areas. This paper analyzes the characteristics of wind load, the causes of wind deflection of transmission line, and introduces the basic principle of measuring insulator inclination when using fiber Bragg grating sensor, which provides technical support for wind deflection monitoring of transmission line in cold areas and ensures the structural safety, safe and stable operation of transmission line.
KEYWORDS: Video, Data modeling, Performance modeling, Image enhancement, Video processing, Safety, Feature extraction, Inspection, Control systems, Algorithm development
A method for predicting abnormal behaviors of substation workers based on video scenes and using generative confrontation networks to integrate global and local information is proposed. In the substation, this method can be used to issue timely warnings to the transportation and inspection personnel that may trigger dangerous actions during the operation, so as to provide an important guarantee for the life and safety of the transportation and inspection personnel. The human behavior prediction task aims to predict future behavior video frames based on a given behavior video frame. Considering that the human behavior video contains not only relatively stable scene information, but also time-varying and complex human behavior information, this method first uses a global generation confrontation network to generate video scenes and rough human contours; then uses local generation confrontation Network to further optimize the details of human behavior in the video. Experiments show that, compared with the existing methods that only use a single model to achieve pixel-level behavior prediction, the method of combining global and local generation proposed in this paper can better capture the spatial appearance and the timing dynamics of humans in the video.
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