Search Results (49)

With the expansion of the scale of ultra-high-voltage transmission lines and the complexity of the corridor environment, the traditional manual inspection method faces serious challenges in terms of efficiency, cost, and safety. In this study, based on power laser inspection technology with a high-precision servo control system, a complete set of laser point cloud processing technology is proposed, covering three core aspects: transmission line extraction, scene recovery, and operation status monitoring. In transmission line extraction, combining the traditional clustering algorithm with the improved PointNet++ deep learning model, a classification accuracy of 92.3% is achieved in complex scenes; in scene recovery, 95.9% and 94.4% of the internal point retention rate of transmission lines and towers, respectively, and a vegetation denoising rate of 7.27% are achieved by RANSAC linear fitting and density filtering algorithms; in the condition monitoring segment, the risk detection of tree obstacles based on KD-Tree acceleration and the arc sag calculation of the hanging chain line model realize centimetre-level accuracy of hidden danger localisation and keep the arc sag error within 5%. Experiments show that this technology significantly improves the automation level and decision-making accuracy of transmission line inspection and provides effective support for intelligent operation and maintenance of the power grid. Full article

A damping spacer rod is a key protective device in ultrahigh voltage transmission lines, which not only keeps the distance of split wires and limits the whipping and collision caused by the relative motion between sub-wires, but also inhibits the vibration of wires. This study aims to solve the problem of typical faults, such as loose wire clamps, that are prone to occur in damping isolation rods during long-term operation in ultra-high voltage transmission lines. Taking the spacer rod FGZ-450/34B as the object, a new high-pressure casting process for spacer rod frames is explored. The spacer rods were simulated by using the ABAQUS finite element software to predict the stress distribution and identify the dangerous sections. Based on this, the mold process was optimized to avoid die-casting defects. Meanwhile, mechanical property tests were carried out on the products produced by the two types of molds. The research finds that by optimizing the mold process, the die-casting quality of the dangerous section of the spacer rod can be effectively improved, and the best high-pressure die-casting scheme has been obtained through comparison. This research achievement provides technical support for enhancing the anti-vibration performance, anti-loosening reliability, short-circuit current thermal shock resistance, and anti-ultraviolet aging performance of damping isolation rods. It is of great significance for ensuring the stable operation of ultra-high voltage transmission lines and improving the production process level of damping isolation rods. Full article

Against the background of the “dual carbon” goal and the construction of a new power system, the intelligent operation and maintenance of insulators for ultra-high voltage transmission lines face challenges such as difficulty in detecting small-scale defects and strong interference from complex backgrounds. This paper proposes an improved network IDD-DETR to address the problems of inefficient one-way feature fusion and low-contrast defects that are easily overwhelmed in existing RT-DETR models. The enhanced network IDD-DETR replaces PAFPN with a Feature-Focused Diffusion Network (FFDN) and improves multi-scale fusion efficiency through bidirectional cross-scale interaction and designs Dynamic-Range Histogram Self-Attention (DHSA) to enhance defect response in low brightness areas. The experiment showed that its mAP⁵⁰ reached 81.7% (an increase of 3.8% percentage points compared to RT-DETR), the flashover defect AP⁵⁰ reached 74.6% (+6.1% percentage points), and it maintained 76 FPS on NVIDIA RTX3060, with an average decrease of 1.65% in mAP⁵⁰ under complex environments. This model reduces the comprehensive missed detection rate from 26.7% to 23.3%, reduces 45.6 GWh of power loss annually (corresponding to 283,000 tons of CO₂ emission reductions, with 64.3% of the reduction contributed by flashover defect detection), improves inspection efficiency by 60%, reduces manual pole climbing frequency by 37%, and reduces 28 high-altitude risk events annually, providing support for low-carbon operation and maintenance of transmission lines. Full article

Ultra-high-voltage (UHV) transmission lines are prone to galloping and oscillations under ice and wind loads, posing risks to system reliability and safety. Accurate aerodynamic coefficients are essential for evaluating these effects, but conventional wind tunnel and CFD methods are costly and inefficient for practical applications. To address these challenges, this study develops a surrogate model for rapid and accurate prediction of aerodynamic coefficients for six-bundle conductors. Initially, a CFD model to calculate the aerodynamic coefficients of six-bundle conductors was proposed and validated against wind tunnel experimental results. Subsequently, Latin hypercube sampling (LHS) was employed to generate datasets covering wind speed, icing shape, icing thickness, and wind attack angle. High-throughput numerical simulations established a comprehensive aerodynamic database used to train and validate multiple tree-based surrogate models, including decision tree (DT), random forest (RF), extremely randomized trees (ERTs), gradient boosted decision tree (GBDT), and extreme gradient boosting (XGBoost). Comparative analysis revealed that the XGBoost-based model achieved the highest prediction accuracy, with an R² of 0.855 and superior generalization performance. Feature importance analysis further highlighted wind speed and icing shape as the dominant influencing factors. The results confirmed the XGBoost surrogate as the most effective among the tested models, providing a fast and reliable tool for aerodynamic prediction, vibration risk assessment, and structural optimization in UHV transmission systems. Full article

With the continuous expansion of power grids and the advancement of ultra-high voltage (UHV) projects, transmission lines are increasingly traversing areas characterized by micro-terrain. These localized topographic features can intensify meteorological effects, thereby increasing the risks of hazards such as conductor icing and galloping, directly threatening operational stability. Enhancing the disaster resilience of transmission lines in such environments requires accurate and efficient terrain identification. However, conventional recognition methods often neglect the spatial alignment of the transmission lines, limiting their effectiveness. This paper proposes a deep learning-based recognition framework that incorporates a dual-branch network architecture and a cross-branch spatial attention mechanism to address this limitation. The model explicitly captures the spatial correlation between transmission lines and surrounding terrain by utilizing line alignment information to guide attention along the line corridor. A semi-synthetic dataset, comprising 6495 simulated samples and 130 real-world samples, was constructed to facilitate model training and evaluation. Experimental results show that the proposed model achieves classification accuracies of 94.6% on the validation set and 92.8% on real-world test cases, significantly outperforming conventional baseline methods. These findings demonstrate that explicitly modeling the spatial relationship between transmission lines and terrain features substantially improves recognition accuracy, offering important support for hazard prevention and resilience enhancement in UHV transmission systems. Full article

FeAl intermetallic compounds exhibit high application potential in high-voltage transmission lines to withstand external forces such as powerlines’ own gravity and wind force. The ordered crystal structure in FeAl intermetallic compounds endows materials with high strength, but the remarkable brittleness at room temperature restricts engineering applications. This contradiction is essentially closely related to the deformation mechanism at the nanoscale. Here, we performed molecular dynamics simulations to reveal anomalous grain size effects and deformation mechanisms in nanocrystalline FeAl intermetallic material. Models with grain sizes ranging from 6.2 to 17.4 nm were systematically investigated under uniaxial tensile stress. The study uncovers a distinctive inverse Hall-Petch relationship governing flow stress within the nanoscale regime. This behavior stems from high-density grain boundaries promoting dislocation annihilation over pile-up. Crucially, the material exhibits anomalous ductility at ultra-high strain rates due to stress-induced phase transformation dominating the plastic deformation. The nascent FCC phase accommodates strain through enhanced slip systems and inherent low stacking fault energy with the increasing phase fraction paralleling the stress plateau. Nanoconfinement suppresses the propagation of macroscopic defects while simultaneously suppressing room-temperature brittle fracture and inhibiting the rapid phase transformation pathways at extreme strain rates. These findings provide new theoretical foundations for designing high-strength and high-toughness intermetallic nanocompounds. Full article

High-voltage direct-current (HVdc) transmission lines are gaining more attention as an integral part of modern power system networks. Monitoring the dc current is important for metering and the development of dynamic line rating control schemes. However, this has been a challenging task, and there is a need for wireless sensing methods with high accuracy and a dynamic range. Conventional methods require direct contact with the high-voltage conductors and utilize bulky and complex equipment. In this paper, an ultra-high-frequency (UHF) radio frequency identification (RFID)-based sensor is introduced for the monitoring of the dc current of an HVdc transmission line. The sensor is composed of a passive RFID tag with a custom-designed antenna, integrated with a Hall effect magnetic field device and an RF power harvesting unit. The dc current is measured by monitoring the dc magnetic field around the conductor using the Hall effect device. The internal memory of the RFID tag is encoded with the magnetic field data. The entire RFID sensor can be wirelessly powered and interrogated using a conventional RFID reader. The advantage of this approach is that the sensor does not require batteries and does not need additional maintenance during its lifetime. This is an important feature in a high-voltage environment where any maintenance requires either an outage or special equipment. In this paper, the detailed design of the RFID sensor is presented, including the antenna design and measurements for both the RFID tag and the RF harvesting section, the microcontroller interfacing design and testing, the magnetic field sensor calibration, and the RF power harvesting section. The UHF RFID-based magnetic field sensor was fabricated and tested using a laboratory experimental setup. In the experiment, a 40 mm-diameter-aluminum conductor, typically used in 500 kV HVdc transmission lines carrying a dc current of up to 1200 A, was used to conduct dc current tests for the fabricated sensor. The sensor was placed near the conductor such that the Hall effect device was close to the surface of the conductor, and readings were acquired by the RFID reader. The sensitivity of the entire RFID sensor was 30 mV/mT, with linear behavior over a magnetic flux density range from 0 mT to $4.5$ mT. Full article

The security of ultra-high-voltage (UHV) overhead transmission lines is frequently threatened by diverse external-force damages. As real-world transmission line scenarios are complex and external-force-damage objects exhibit varying scales, deep learning-based object detection methods necessitate the capture of multi-scale information. However, the downsampling and upsampling operations employed to learn multi-scale features work locally, resulting in the loss of details and boundaries, which makes it difficult to accurately locate external-force-damage objects. To address this issue, this paper proposes a content-aware method based on the generalized efficient layer aggregation network (GELAN) framework. A newly designed content-aware downsampling module (CADM) and content-aware upsampling module (CAUM) were integrated to optimize the operations with global receptive information. CADM and CAUM were embedded into the GELAN detection framework, providing a new content-aware method with improved cost accuracy trade-off. To validate the method, a large-scale dataset of external-force damages on transmission lines with complex backgrounds and diverse lighting was constructed. The experimental results demonstrate the proposed method’s superior performance, achieving 96.50% mean average precision (mAP) on the transmission line dataset and 91.20% mAP on the pattern analysis, statical modeling and computational learning visual object classes (PASCAL VOC) dataset. Full article

UHV (ultra-high voltage) by instant AC transmission system is accompanied by huge reactive power transmission. When the load drops sharply, it is easy to produce serious power frequency overvoltage, which is also defined as load rejection overvoltage. This paper makes an in-depth analysis from the perspective of voltage increase caused by instantaneous load unloading, and obtains the causes and key influencing factors of load rejection overvoltage. Taking the UHV AC transmission line of a practical project as an example, the suppression effect of the suppression strategy represented by the installation of opening resistance and shunt reactor on the load rejection overvoltage is analyzed. The simulation results show that the above method has an obvious inhibitory effect on load rejection overvoltage. Based on the optimal suppression principle, the optional interval range of the opening resistance and shunt reactor parameters are designed. Full article

The electric field of transmission lines has serious negative impacts on residents’ production and life with the expansion of high voltage engineering. In order to study the influence of trees on the electric field of ultra-high voltage transmission lines, this paper conducted three-dimensional simulation calculations of the power frequency electric field of transmission lines based on the tree quantity and distribution. Firstly, in order to study the pattern of electric field strength distribution in transmission lines, the electric field strengths of transmission lines of different voltage levels were compared; the maximum-power-frequency electric field intensity of ultra-high voltage transmission lines occurs below the edge conductor. Secondly, by changing the number of trees, it was concluded that the electric field strength below the edge conductor gradually decreases with the number of trees. Finally, the maximum electric field strength value at 1.5 m below the edge conductor and the width of the transmission corridor decreased by changing the layout of the trees. The results show that studying the impact of a tree’s electromagnetic parameters on the power frequency electric field strength under transmission lines can help reduce the electric field strength and decrease the width of transmission corridors, which is of great significance for line design and cost savings. Full article

The high-speed railway project and the ultra-high-voltage transmission project represent two crucial components of China’s “new infrastructure”. As the construction of these two projects progresses rapidly, it is inevitable that instances of intersections will occur. Extreme conditions may cause damage to ultra-high voltage transmission cables. When a high-speed train passes by an ultra-high voltage transmission line, it poses a serious safety hazard. To address this issue, engineering examples were utilized to examine the protection structure scheme, protection distance, protection load, and construction procedures when a high-speed railway intersects a 1000 KV ultra-high voltage transmission line. A shed structure form and construction method for the electric power protection were proposed to ensure the safe operation of the high-speed railway while also achieving the safe and rapid construction of the high-speed railway protection structure in the safety zone of the approaching 1000 kV ultra-high voltage transmission line. The results indicated that the protection of high-speed railway crossings and 1000 kV ultra-high voltage transmission lines primarily focuses on line-break protection. The concrete shed structure with a straight wall and a flat roof was designed to meet the requirements of high-speed railway crossings. The line-break protection method enables the construction of an automatic warning protection corridor and a complete movable trolley quickly and safely within the safety zone near the transmission line. The implementation effect is, therefore, positive. It can be used as a reference point for other projects of a similar nature. Full article

Transmission lines are affected by external environmental factors such as strong winds and ice cover. In recent years, extreme weather events have increased, leading to recurrent disturbances in transmission lines because of wind deflection. These incidents have resulted in significant financial losses and have disrupted regular industrial and domestic activities. In this paper, the ANSYS Workbench 2020 R2 finite element analysis platform was used to establish a transmission line-hanging insulator string system model. Calculations on transmission lines were conducted considering variations in different stall spacing, height differences, wind speed, and the wind attack angle. The impact of these diverse factors on the wind deflection of insulators was scrutinized, leading to the derivation of patterns describing how the wind deflection angle shifts in response to changes in stall spacing, height differences, wind speed, and the wind attack angle. Based on the generalized linear regression network and particle swarm improved support vector machine algorithm, a meteorological prediction-based early warning method for wind deflection of transmission lines was proposed, a transmission line wind deflection early warning model was established, and the practical effect of the model was evaluated. The outcomes of this study provide crucial data for the formulation and development of ultra-high voltage (UHV) and extra-high voltage (EHV) transmission networks. Furthermore, they can contribute to the advanced detection of wind deflection issues. Full article

Yunnan plays a pivotal role in transmitting electricity from west to east within China’s Southern Power Grid. During 7–13 January 2021, a large-scale continuous ice-covering event of ultra-high voltage (UHV) transmission lines occurred in the Qujing area of eastern Yunnan Province. Based on ERA5 reanalysis data and meteorological observation data of UHV transmission line icing in China’s Southern Power Grid, the synoptic causes of the icing are comprehensively analyzed from various perspectives, including weather situations, vertical stratification of temperature and humidity, local meteorological elements, and atmospheric circulation indices. The results indicate a strong East Asian trough and a blocking high directing northern airflow southward ahead of the ridge. Cold air enters the Qujing area and combines with warm and moist air from the subtropical high pressure of 50–110° E. As warm and cold air masses form a quasi-stationary front over the northern mountainous area of Qujing due to topographic uplift, the mechanism of “supercooling and warm rain” caused by the “warm–cold” temperature profile structure leads to freezing rain events. Large-scale circulation indices in the Siberian High, East Asian Trough, and 50–110° E Subtropical High regions provided clear precursor signals within 0–2 days before the icing events. Full article

To enhance the performance of ultra-high voltage power fittings in severe weather conditions without altering their current structure, the high-strength and toughness aluminum alloys were rationally selected to study the optimization of the die-casting process. This approach aims to improve the overall longevity and function of the power fittings in extreme climates. First of all, the propose of this study is to use the material’s strength–toughness product (STP) concept to evaluate the material stability of the power fitting impact resistance and fatigue toughness in order to determine the appropriate material selection. Secondly, the location of the mold’s sprue and gate was optimized through finite element simulation to prevent gas volume and flow defects during the casting process. This improves the material’s toughness and anti-fatigue failure characteristics of the product. Then, vacuum equipment and a vacuum valve auxiliary system were added based on the existing die-casting machine, and the mold structure was optimized to enable the vacuum die-casting process. Finally, a water-based boron nitride environmentally friendly mold release agent was used to solve demolding difficulties with an A356 aluminum alloy and improve mold lubrication and surface quality. The production of quad-bundled spacers using A356 and vacuum die casting has resulted in parts with a tensile strength of at least 250 MPa and an elongation of no less than 7%. This improvement has laid a foundation for enhancing the operational reliability of existing overhead transmission line fittings. Full article

The advanced Gas Insulated Switchgear/Gas Insulated Lines (GIS/GIL) transmission equipment serves as an essential physical infrastructure for establishing a new energy power system. An analysis spanning nearly a decade on faults arising from extra/ultra-high voltage discharges reveals that over 60% of such faults are attributed to the discharge of metal particles and dust. While existing technical means, such as ultra-high frequency and ultrasonic sensing, exhibit effectiveness in online monitoring of particles larger than sub-millimeter dimensions, the inherent randomness and elusive nature of micron-nano dust pose challenges for effective characterization through current technology. This elusive micron-nano dust, likely concealed as a latent threat, necessitates special attention due to its potential as a “safety killer”. To address the challenges associated with detecting micron-nano dust and comprehending its intricate mechanisms, this paper introduces a micron-nano dust adsorption experimental platform tailored for observation and practical application in GIS/GIL operations. The findings highlight that micron-nano dust’s adsorption state in the electric field predominantly involves agglomerative adsorption along the insulator surface and diffusive adsorption along the direction of the ground electrode. The pivotal factors influencing dust movement include the micron-nano dust’s initial position, mass, material composition, and applied voltage. Further elucidation emphasizes the potential of micron-nano dust as a concealed safety hazard. The study reveals specific physical phenomena during the adsorption process. Agglomerative adsorption results in micron-nano dust speckles forming on the epoxy resin insulator’s surface. With increasing voltage, these speckles undergo an “explosion”, forming an annular dust halo with deepening contours. This phenomenon, distinct from the initial adsorption, is considered a contributing factor to flashovers along the insulator’s surface. The physical mechanism behind flashovers triggered by micron-nano dust is uncovered, highlighting the formation of a localized short circuit area and intense electric field distortion constituted by dust speckles. These findings establish a theoretical foundation and technical support for enhancing the safe operational performance of AC and DC transmission pipelines’ insulation. Full article