A training sample reduction strategy for data-driven surrogate modeling of wind-induced structural responses

Structural vibration control of high-voltage transmission towers using a novel composite pendulum VTMD

Multi-degree-of-freedom energy-harvesting and monitoring-coupled triboelectric nanogenerator for vibration state perception of transmission towers

This thesis deals with the case study on the properties of GFRP (Glass Fiber Reinforced Polymer) In this Thesis we use the GFRP to find out the behaviour of the final product madeby this material which is line transmission tower. Due to the rapid population growth and rapid urbanization, the natural resources are depleting day by day. So, the natural aggregates are very hard to obtain. So many people are opting to use the GFRP (Glass Fiber Reinforced Polymer) instead of the conventional iron or steel channels. The cost of conventional iron or steel channels as compared to GFRP is also very high due to the high demand of it in construction works. GFRP will reduce the quarrying and mining of iron and steel ores thereby reducing the use of natural resources excessively. The land surface can be prevented from any unwanted excavation and hence ecological disturbances will be reduced to conserve the conventional natural iron ore for other important construction works. The compression and the tensile tests are carried out in the thesis to find out the behaviour of the different types of the joints and channel sections with different types of connections. And the result is carried out and accordingly the conclusion is given. This study focuses on the structural behaviour of bolted joints in Glass Fiber Reinforced Polymer (GFRP) transmission line towers, specifically investigating the use of GFRP for these structures as an alternative to traditional steel.

To accurately evaluate the electric and magnetic field distribution characteristics around transmission lines under different tower structures and operating conditions, this study systematically investigates the spatial electric and magnetic fields of transmission line towers based on Grid Information Model (GIM) file parsing and finite element simulation. First, key information, including tower geometric configuration, conductor suspension point locations, and voltage level, is extracted by parsing the GIM file. A unified transformation method from geographic coordinates to three-dimensional Cartesian coordinates is established, and a three-dimensional electric and magnetic field calculation model is constructed in the ANSYS Maxwell platform, incorporating a catenary conductor model and an equivalent representation of bundled conductors. Furthermore, the accuracy of the proposed calculation method is validated based on field measurement data. Second, under single-circuit operating conditions, the spatial electric and magnetic field distributions of the Goblet-shaped suspension tower and the Drum-type transmission tower are analyzed under different phase sequence arrangements and different conductor-to-ground heights, and the shielding effect of the tower structure on the local electric field is investigated. On this basis, an electric field fitting method based on a proportional polynomial model is proposed, enabling the prediction of electric field distribution under tower-present conditions using simulation results obtained without tower structures. Subsequently, the influence of different phase sequence combinations on the spatial electric field distribution is systematically examined. The fitting method is further extended to double-circuit transmission lines, and its accuracy and effectiveness in rapid electric field assessment are verified. Finally, from an engineering practice perspective, the effects of the presence of jumper conductors and variations in conductor turning angles on the spatial electric field distribution of double-circuit towers are analyzed, and an optimized estimation approach for electric fields under different turning angle conditions is proposed. The results demonstrate that tower structural configuration and conductor arrangement significantly affect the electric field distribution, and the proposed fitting method effectively reduces modeling complexity while maintaining computational accuracy. The findings of this study provide a theoretical basis and technical reference for electric and magnetic environment assessment and engineering design of transmission lines.

Introduction: With the sustainable growth in electricity demand, an increasing number of transmission lines must traverse high-seismic-intensity mountainous regions. Due to topographic heterogeneity, uneven horizontal span distribution, and elevation differences between transmission towers are common in mountainous areas. This paper investigates the dynamic response of a transmission tower-line system under seismic loads, focusing on the effects of the uneven distribution of horizontal spans and elevation variations. Finite element models of the transmission tower-- line system were developed utilizing ABAQUS software. Three ground motion records were selected from the PEER database and applied at the base of the tower legs in the direction perpendicular to the conductor. The span unevenness coefficient, Φ, and the elevation variation coefficient α, were then proposed. By comparing the stresses of four observed members and the displacements at observed points under different working conditions, this study investigates the effects of the uneven distribution of horizontal spans and elevation variations on the seismic responses of the transmission tower-line system. Methods: To investigate the influence of complex terrain on the dynamic characteristics of transmission tower-line systems, a series of nonlinear time-history analyses was conducted using three different seismic waves. A parametric study was implemented by varying the span unevenness coefficient (Φ) from 1.000 to 1.439 and the elevation variation coefficient (α) of the middle tower from 0 to 0.286. These parameters were utilized to evaluate the sensitivity of maximum member stresses and nodal displacements to topographic irregularities and span configurations. Results: When horizontal spans are unevenly distributed and elevations vary between adjacent transmission towers, the resulting alteration in the conductor sag profile leads to an uneven tension distribution, thereby increasing the seismic response. Discussion: Therefore, in the seismic design of transmission towers located in high mountainous regions, it is crucial to consider the amplification effects caused by both uneven horizontal span distribution and elevation variation. Conclusion: This research provides a reference for the seismic design of transmission towers in mountainous terrains, which can also contribute to the development of innovative engineering solutions with potential patent applications.

Transmission towers, as critical infrastructure in power systems, are frequently threatened by multiple hazards such as strong winds and flood scour. Traditional structural health monitoring methods face limitations in data feedback timeliness and mechanical interpretation, making real-time condition awareness and early warning under disaster scenarios challenging. To address these issues, this paper proposes a digital twin framework for transmission tower structures, integrating Building Information Modeling (BIM), Internet of Things (IoT) technology, and the Finite Element Method (FEM) for structural health monitoring and visual warning under wind loads and flood scour effects. The framework achieves cross-platform collaboration through the FEM Open Application Programming Interface (OAPI) and Python scripts. In the physical domain, fluctuating wind loads are simulated based on the Davenport spectrum, flood scour depth is modeled using the HEC-18 formulation, and foundation constraint degradation is represented through nonlinear spring stiffness reduction. In the FEM domain, dynamic time-history analyses are conducted to obtain structural responses. In the BIM domain, a three-level warning mechanism based on stress change rate (ΔR) is established to achieve intuitive rendering and dynamic feedback of structural damage. A 44.4 m high latticed angle steel tower is employed as the case study for validation. Results demonstrate that the simulated wind spectrum closely matches the theoretical target spectrum, confirming the validity of the load input. A critical scour evolution threshold of 40% is identified, beyond which the first two natural frequencies exhibit nonlinear decay with a maximum reduction of 80.9%. Non-uniform scour induces significant load transfer, with axial forces at leeside nodes increasing from 27 kN to 54 kN. During the 0–60 s wind loading process, BIM visualization accurately captures the full stress evolution from the tower base to the upper structure, showing excellent agreement with FEM results. The proposed framework establishes a closed-loop interaction mechanism of “physical sensing–digital simulation–visual warning”, effectively enhancing the timeliness and interpretability of structural health monitoring for transmission towers under multiple hazards, providing an innovative approach for intelligent disaster prevention in power infrastructure.

ABSTRACT The inspection of power transmission towers, crucial for grid maintenance, has seen advances through unmanned aerial vehicles (UAVs) and neural networks. However, complex backgrounds, inaccurate semantic segmentation, and challenges in tilt calculation limit their practical use. This study introduces a non-contact tilt detection and quantification method based on an improved U-Net architecture. The model integrates Squeeze-Excitation (SE) and Convolutional Block Attention Module (CBAM) to enhance channel and spatial feature representation, addressing issues such as blurred edges and structural loss. Using the segmented binary mask, contour points are extracted, and Principal Component Analysis (PCA) determines the tower’s main orientation to compute its tilt relative to the vertical axis. Experimental results show that the proposed U-Net+SENet outperforms the baseline, increasing mean intersection over union (mIoU) and Dice coefficients by 1.08% and 4.57%, respectively. In complex cross-arm scenarios, exceeding those of both the baseline and CBAM-enhanced models. This approach improves segmentation accuracy and enables precise axis extraction and tilt estimation. Visualisation confirms the model’s superior detail extraction, verifying its effectiveness and reliability.

This paper presents a self-resonant multi-relay wireless power transfer (WPT) system specifically designed for transmission tower sensor applications. This study proposes a self-resonator based on the four-layer antisymmetric PCB architecture, where inter-turn and inter-layer parasitic capacitances replace discrete capacitances. A 5-coil WPT experimental platform with a transmission distance of 450 mm is built for validation, demonstrating that the proposed system maintains frequency stability and constant voltage (CV) outputs despite environmental dielectric variations. A quality factor (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i>)-value optimization strategy is introduced to enhance transmission efficiency without increasing system complexity, thereby achieving a peak DC-DC efficiency of 71.36%, outperforming conventional counterparts. Moreover, the proposed system maintains a kilohertz (kHz)-level resonant structure, which shows high robustness to environmental perturbations.

Wind-induced vibration calculation method for transmission towers considering tower-line coupling effect

AFENet: a real-time power line and transmission tower segmentation network with adaptive feature enhancement

Multi-scale structural analysis method for transmission towers considering the combined effects of multiple imperfections

FP-LD strong feedback fiber-optic stress system for high-voltage transmission towers

An angle steel transmission tower panel under torsion: A full-scale experimental and numerical study

Abstract Transmission towers are susceptible to corrosion after prolonged exposure to complex service environments, which can lead to structural degradation. Therefore, residual life prediction of the corroded towers is critical for risk mitigation and the prevention of related accidents. Residual Life prediction methods are inadequate for effectively detecting tower corrosion faults and often fail to account for multiple practical environmental factors, resulting in unreliable prediction outcomes. To address these issues, this paper proposes a novel prediction method for the residual life of corroded transmission towers based on multiple environmental factors. The basic theory and the method for detecting the corrosion of the towers are analyzed. A novel prediction method based on multiple environmental factors and the estimated corrosion rate of residual life is developed and validated through a case study. The results show that the proposed method can accurately predict the residual life of corroded transmission towers in the practical environment, which is significant for enhancing the reliability of power transmission systems.

The reliance on manual teaching in high-mix low-volume (HMLV) transmission tower base joints manufacturing leads to inefficiencies, inconsistent weld quality, and high labor costs. This study presents a robotic flexible welding path planning approach to automatically generate welding paths for customized fabrication. The proposed method begins with arbitrary positioning of the workpiece on the turntable, followed by point cloud acquisition and weld seam extraction. Based on the extracted seam information, a turntable rotation strategy is implemented to determine the optimal welding position for each seam relative to the robot. A path planning algorithm incorporating Cartesian space constraints during sampling is then used to generate feasible welding paths. Finally, the resulting welding paths are transmitted to the robot for execution. To validate this approach, a path planning work platform integrated with a modular communication mechanism was established. The experimental results show that, compared to other algorithms, the method reduces average search time by up to 26.8% and average path length by up to 18.7%.

This study presents a specific analytical solution procedure to the local-buckling problem in angle steels using a two-dimensional improved Fourier-series method (2D-IFSM). The effect of coupling between the sub-plates of an angle steel on its local-buckling behaviour is studied by incorporating rotational spring constraints between them. The proposed solution procedure enables one to convert the local-buckling problem of angle steels into solving sets of linear algebraic equations, thereby effectively simplifying its solution process. The critical load and related buckling-mode results obtained in this study are in good agreement with the existing analytical solutions and finite-element-method numerical data, verifying the effectiveness of the proposed method. Based on the derived solutions, a quantitative analysis is conducted to investigate the influences of aspect ratio, width–thickness ratio, and rotational constraint degree on the local-buckling behaviour of angle steels.

Introduction Research on vibration mitigation for transmission towers is critical to enhancing the seismic resilience of power grids and ensuring power supply safety. Methods This study investigates the effectiveness of a vibration isolation trench installed around a tower foundation. The trench is backfilled with a composite material consisting of rubber particles and enzyme-induced carbonate precipitation (EICP)-treated loess. The reliability of a finite element model was first validated against shaking table test results. Subsequently, parametric studies were conducted using numerical simulation to analyze the effects of key design parameters—including trench depth, width, and distance from the foundation—on the seismic response of the tower system. Results The optimized trench effectively reduces the transmission of seismic energy to the foundation-structure system, mitigates soil-structure interaction, and significantly decreases the tower’s acceleration and displacement responses. The isolation performance improves with increasing trench width and depth; however, the enhancement plateaus when the depth exceeds 8 meters. Furthermore, a closer proximity to the foundation combined with a greater trench width leads to more pronounced vibration reduction. Discussion This study provides practical guidance for the seismic design of transmission towers in loess regions.

During the construction and subsequent operation of the Zhiguli hydroelectric power station, part of the island of Telyachy, located in the lower reaches of the hydroelectric complex, was severely deformed. To date, only the lower part of the island has been preserved, and the part of the island directly adjacent to the earthen dam of the Zhiguli hydroelectric power station, and the processes of erosion of the coastline continue. These processes pose a danger to the transmission towers, the route of which is located along the lower slope of the dam, and a possible negative impact on the floodplain of the earthen dam. The purpose of this work is to analyze the deformation processes, identify the causes contributing to the erosion of the coastline of the island of Telyachy and develop recommendations for strengthening the coastline. The methods of static analysis, analytical methods of river hydraulics and numerical modeling methods were used in the performance of the work. The results of this work are intended for use in the development of project documentation

The paper presents a comprehensive deep learning-based framework for automated visual inspection of overhead power line infrastructure using unmanned aerial vehicles. Traditional manual and helicopter inspections are costly, time-consuming, and hazardous for maintenance personnel. The proposed approach integrates UAV imaging with advanced computer vision models such as YOLOv8, EfficientDet-D2, and Faster R-CNN to automatically detect defects in critical components, including insulators, conductors, and transmission towers. Several open datasets (InsPLAD, TTPLA, MPID) were used for training and validation, ensuring robustness under diverse lighting and environmental conditions. Experimental results demonstrate that YOLOv8 achieved the best performance, reaching 88.5% mAP@0.5 with real-time inference capabilities (over 50 FPS on GPU). The system significantly enhances inspection efficiency, allowing for a threefold increase in coverage capacity and an up to 70% reduction in defect remediation time. The integration of AI-powered visual analytics with maintenance and SCADA systems enables a shift from reactive to predictive maintenance, improving the safety, reliability, and resilience of power transmission infrastructure.