Transmission Tower Research Articles

Evaluation of the transmission tower and frequency-dependent soil parameters influence on the grounding potential rise waveforms

In this paper, the influence of the transmission tower and the frequency-dependent soil parameters on the grounding potential rise (GPR) waveform is evaluated. This evaluation is performed using a physically consistent electromagnetic model that determines the transient behavior of the grounding system submitted by lightning, together with the Alternative Transients Program for the representation of aerial elements (tower, phase cables and shield wires). This model was developed in the frequency domain and, in this way, allows the inclusion of frequency-dependence of soil electrical parameters. In this sense, three formulations of the dependence in question are considered, widely disseminated in the literature, and determined through systematic measurement processes. The results illustrate that the concomitant inclusion of the tower and the frequency-dependence substantially modifies the GPR waveforms, when compared with those in which isolated grounding is considered, especially for soils with high resistivity values and for first return strokes. This is of most importance when evaluating personal safety criteria in the transmission tower vicinity. In these situations, the GPR waveforms should be determined by considering the presence of the tower and not only with the isolated grounding, since the transient step and touch voltages are directly associated with GPR.

The 3D model construction method of overhead transmission line based on GIM

With the continuous progress of power grid digitization, Building Information Model (building information modeling, BIM) technology can no longer meet the application display requirements of power grid engineering. Power grid information model (grid information model, GIM) technology uses parameterization to build a 3D model, which reduces redundancy and is conducive to the digital transfer of the project. This paper briefly analyzes the structure of the GIM data model. It carries out research on 3D parametric modeling of overhead transmission line ground wire, tower, foundation, and insulator string based on GIM. It uses a 3D graphics engine to realize the visual rendering of ontology 3D models. On this basis, a 3D scene construction method of overhead transmission line engineering based on GIM is proposed, which provides reliable technical support for digital power grid applications.

Load carrying capacity of star‐battened angle members made of S460 steel in compression

AbstractLattice towers are extensively built in Europe and worldwide to serve power transmission purposes. Their members mainly consist of single angle profiles, while built‐up sections, such as star‐battened ones, are usually preferred for the strengthening of individual members or in case of very high compression loads. Recent upwards developments of the power grid requests also lead to the need to use high strength steels (HSS) for the design and construction of higher and heavier loaded steel lattice transmission towers. Within the present paper, investigations conducted on the bearing capacity of a star‐battened member made of two S460 L250×250×28 angles are presented, even if the conclusions may be extended to any angle size and steel grade.Firstly, a critical review of the current European normative documents (EN 50341, EN1993‐1‐3, prEN1993‐3) is made and the buckling resistance of the above‐mentioned member is evaluated. Secondly, the results of an experimental compression test performed on the studied member are presented; these results are complemented by a full non‐linear finite element numerical simulation. All the obtained results are finally compared and discussed.

Wind induced coupling effects of transmission tower-line system at microtopography

The coupled and uncoupled Dynamic Finite Element Models (DFEMs) of the transmission tower-line system consisting of two towers and three spans of conductors and ground wires were built at the windward and crosswind slope of a cosinoidal hill. The acceleration ratios of mean wind profiles of cosinoidal mountains were summarized from previous studies, then the mean wind profile over the windward, crosswind and leeward slopes were revised. The wind loads acting on the transmission tower-line system were calculated based on the revised profile. The wind-induced dynamic responses of the coupled and uncoupled DFEMs were detected, and the coupling effects on reaction force of hanging points, displacements and accelerations at the tower top, axial forces of main rods and wind-induced vibration coefficients were analysed. The results show that due to the lack of the TMD-like effect, the uncoupled system is more sensitive to wind load and has significant wind-induced vibration compared to the coupled system, making the three-dimensional force of the hanging point, displacements and accelerations at the tower top, axial forces of main rods increasing, but the wind-induced vibration coefficients change little. Generally, the coupling effects of the tower-line system are significant. Ignoring it will make the structural design of transmission towers conservative.

Seismic Fragility of High Voltage Transmission Tower Due to Earthquake by Using Adaptive Pushover Method

Seismic Fragility of High Voltage Transmission Tower Due to Earthquake by Using Adaptive Pushover Method

Design and application of a UHF RFID tag for monitoring pollution in high voltage towers

Pollution diagnosis is difficult and costly for power grid operators. For the purpose of have an effective, low-cost and user-friendly pollution diagnosis, a Radio Frequency Identification prototype is proposed - an RFID tag for identifying and monitoring pollution in high voltage towers. For that, the following steps were performed: dielectric characterization of artificial pollution; project via simulation of RFID tags for application in metallic towers; manufacture, validation and testing of tags; sensitivity analysis of tag reach; and computational algorithm for signal treatment and subsequent identification. Pollution identification was based on variations of the Received Signal Intensity Indicator (RSSI) by the reader as a function of the amount of pollution deposited. The validation and testing of the tags were carried out in an external environment with an emulation of a de-energized high voltage tower. For all levels of deposited pollution analyzed, the average maximum reach of the signal reading, in an external environment, was 18 m. The RSSI data, obtained by reading the RFID tag, were processed and analyzed to identify the pollution deposited on the high voltage transmission towers. The results demonstrated the potential of the tags for identification and monitoring pollution levels in high voltage metal towers.

Lightning Current Measurement Form and Arrangement Scheme of Transmission Line Based on Point-Type Optical Current Transducer.

Lightning strikes are the main cause of transmission line faults, and the accurate lightning current number is an important basis to guide scientific lightning protection. The use of sensors with excellent sensing performance to carry out lightning current monitoring on transmission lines is beneficial to the accumulation of key parameters of original lightning strikes, so it is necessary to study the lightning current measurement structure of transmission lines. In this paper, an optical current-sensing unit is used to monitor the lightning current on transmission lines. A measuring structure that can monitor key parameters of the lightning current under different types of lightning strikes is proposed. First, establish the lightning current return channel model and the equivalent model of the tower, study the influence of the transmission tower on the current in the lightning channel, and analyze the direct measurement position of the lightning current on the tower; establish the multi-wave impedance model of the tower, and build a multi-base tower. The simulation model of the transmission system analyzes the transmission characteristics of the lightning current on the transmission line and the lightning protection line in the case of different types of faults; from the perspective of the measurement of key parameters of the lightning current, the lightning current measurement structure of the transmission system is constructed to analyze different lightning strikes. The measurement effect of each monitoring position in the case of a lightning strike and the waveform characteristics of the fault current in the case of insulator flashover are analyzed.

High-Accuracy Measurement of Three-Dimensional Inclinations of Power Transmission Towers Using Reconstruction Model of Stereo Images

The traditional inclination measurement method usually measures one-dimensional or two-dimensional inclinations of power transmission towers. This research proposed a method, which is feasible to measure three-dimensional (3D) inclinations using the stereo images of power transmission towers. The main work of this method is the 3D reconstruction of power transmission tower model using stereo images and the calculation of 3D inclinations. As for the 3D reconstruction, a method of calculating the matching cost using a combination of multichannel red–green–blue stereo pairs and Sobel edge detection stereo pairs is proposed to obtain accurate matching cost, and a method of invalid disparity judgment is proposed to detect the invalid disparities in small closed areas; as for the calculation of 3D inclinations, a 3D inclination calculation method is put forward to measure 3D inclinations by rotation and translation of different 3D reconstruction models. The experiment shows that the 3D reconstruction quality is good and the results of the 3D inclinations are accurate, which is of great value in the static or dynamic measurement of 3D inclinations of power transmission towers.

Fragility Analysis of Transmission Towers Subjected to Downburst Winds

A downburst is a typical local highly intensive wind all over the world, which is attributed to be the main cause of wind damage to transmission lines in inland areas worldwide. The collapse accidents of transmission towers under the downburst still occur every year. Therefore, it is of great significance to assess the safety of the transmission towers under downbursts. The motivation of the present study is to propose a fragility assessment method for transmission towers under the action of a downburst considering the uncertainty of wind-resistance capacity and the stochastic wind load effect. First, the downburst wind field of the transmission tower with different wind attack angles and different radial distances is simulated according to the mixed stochastic model. Then, random material characteristic samples are generated by the Latin hypercube sampling technique and applied to establish uncertain finite element models for transmission towers. Next, the static nonlinear buckling analysis is carried out by numerical methods to determine the ultimate capacity under the downburst wind load. The parameter analysis of different wind attack angles and radial distances between the downburst and the tower is conducted to determine the most unfavorable location of the maximum response. The failure mode of the transmission tower and the probabilities of the initial failure main members are summarized. Finally, the fragility curves of the transmission tower under the downburst and the atmospheric boundary layer (ABL) wind are compared. The results show that the maximum response is located at R = 1.6D. Most of the initial buckling members are located close to the first section of the tower. The fragility curves of the tower under the downburst are more dangerous than the ABL wind with the attack angle increasing from 0° to 90°. Furthermore, considering the probability model of intensity and direction of the downburst and based on the previous fragility analysis, the collapse probability of the transmission tower caused by the downburst is obtained. By probability analysis of the parameters, including layout conditions, different directions, and different wind speeds, it is found that the most favorable arrangement is 157.5°, and the most unfavorable arrangement is 112.5°.

Fragility analysis of an ultra high voltage transmission tower in saline soil subjected to wind loads

The wind resistance of transmission towers is not only affected by wind load, but also by service environment. This study uses the world’s second Ultra High Voltage Direct Current transmission project – Xinjiang ±800 kV Tianzhong Line UHV DC transmission project – to develop a fragility analysis method for transmission towers in saline soil under wind loads to investigate the change of wind loads fragility of transmission towers in long-term service in the saline soil environment. It develops a tower-line-foundation (3 T-2L-F) system model considering soil-structure interaction. In addition, this research addresses the durability damage of the transmission tower using field investigation data and material degradation models and analyzes the influence of various durability damage components on the natural vibration mode of the basic of 3 T-2L-F model. Finally, it builds the structure-wind samples utilizing a Latin hypercube sampling method and explores the time histories analysis, the pushover analyses, and the time-varying fragility analyses considering the uncertainty of materials and wind loads. The findings indicate that the 3 T-2L-F model accurately simulates the actual situation of the transmission tower. The fragility of a transmission tower subjected to wind loads is proportional to the degree of material damage and the strength of wind loads.

Numerical analysis of insulated and conventional cross arms for transmission line tower

The development of the world power industry has led to studies focused on high-performance materials to enhance the durability and prolong the service life of existing structures. In this context, cross arm is one of the main components of an electricity-transmission structure. The application of composite units (insulated cross arm) on lattice transmission towers was evaluated using the software Ansys 2020 R2 in terms of efficiency, cost, and mechanical performance, compared to conventional transmission towers. Finite-element analysis results demonstrated reductions in internal forces, displacements, and support reactions when the insulated cross-arm (IC) tower structure was employed instead of the conventional cross-arm (CC) tower structure. This could lead to minor structural costs. The IC tower exhibited a better stability under free vibrations owing to its higher stiffness than that of the CC tower. The main reason for these results was the height reduction proportioned by IC structures.

Multi-Patch Hierarchical Transmission Channel Image Dehazing Network Based on Dual Attention Level Feature Fusion.

Unmanned Aerial Vehicle (UAV) inspection of transmission channels in mountainous areas is susceptible to non-homogeneous fog, such as up-slope fog and advection fog, which causes crucial portions of transmission lines or towers to become fuzzy or even wholly concealed. This paper presents a Dual Attention Level Feature Fusion Multi-Patch Hierarchical Network (DAMPHN) for single image defogging to address the bad quality of cross-level feature fusion in Fast Deep Multi-Patch Hierarchical Networks (FDMPHN). Compared with FDMPHN before improvement, the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) of DAMPHN are increased by 0.3 dB and 0.011 on average, and the Average Processing Time (APT) of a single picture is shortened by 11%. Additionally, compared with the other three excellent defogging methods, the PSNR and SSIM values DAMPHN are increased by 1.75 dB and 0.022 on average. Then, to mimic non-homogeneous fog, we combine the single picture depth information with 3D Berlin noise to create the UAV-HAZE dataset, which is used in the field of UAV power assessment. The experiment demonstrates that DAMPHN offers excellent defogging results and is competitive in no-reference and full-reference assessment indices.

Evaluation of Power Transmission Lines Hardening Scenarios Using a Machine Learning Approach

Abstract The power transmission infrastructure is vulnerable to extreme weather events, particularly hurricanes and tropical storms. A recent example is the damage caused by Hurricane Maria (H-Maria) in the archipelago of Puerto Rico in September 2017, where major failures in the transmission infrastructure led to a total blackout. Numerous studies have been conducted to examine strategies to strengthen the transmission system, including burying the power lines underground or increasing the frequency of tree trimming. However, few studies focus on the direct hardening of the transmission towers to accomplish an increase in resiliency. This machine learning-based study fills this need by analyzing three direct hardening scenarios and determining the effectiveness of these changes in the context of H-Maria. A methodology for estimating transmission tower damage is presented here as well as an analysis of impact of replacing structures with a high failure rate with more resilient ones. We found the steel self-support-pole to be the best replacement option for the towers with high failure rate. Furthermore, the third hardening scenario, where all wooden poles were replaced, exhibited a maximum reduction in damaged towers in a single line of 66% while lowering the mean number of damaged towers per line by 10%.

Numerical Investigation of Uplift Failure Mode and Capacity Estimation for Deep Helical Anchors in Sand

The uplift capacity of helical anchors is generally taken as the control condition for design in different applications, including transmission tower foundations and offshore structures. However, it is difficult to identify the failure surface for a deep helical anchor, which may result in an incorrect assessment of uplift capability. This research proposes a new unified method to estimate the uplift capacity of deep single-helix and multi-helix anchors based on the investigation of failure mechanisms. The deep failure mode was identified by FEM analysis using a modified Mohr–Coulomb model considering the strain softening of sand, along with the coupled Eulerian–Lagrangian technique. Thereby, a simplified rupture surface is proposed, and the equations estimating the uplift capacity are presented by the limit equilibrium method. Two important factors—the lateral earth pressure coefficient and the average internal friction angle included in the equations—are discussed and determined. The comparisons with centrifugal tests verify the reasonability of the proposed method.

A simplified analytical method for lateral dynamic responses of a transmission tower due to rockfall impact

Transmission tower structures support high-voltage power lines that carry electricity over long distance and rockfall is one of critical disasters during its safe operation. This paper presented a simplified analytical methodology for lateral dynamic responses of a transmission tower structure due to rockfall impact. At first, the lateral dynamic displacement of a lattice transmission tower structure can be represented by a second-order partial differential equation and half sine wave was used for rockfall impact. Then, the solution can be approximated by a set of specified shape functions multiplied by time-dependent generalized coordinates. And the partial differential equation is discretized into a set of single degree of freedom system. And then the shape function can be determined by solved an eigenvalue function and the fundamental frequency of a transmission tower can was derived based on the energy method and combination synthesis method. Finally, the lateral dynamic displacements can be approximately obtained. A numerical study of a transmission tower was conducted. Parametric study of the effect of impact location height, impact duration, peak impact force, as well as the distribution of cross-arms on dynamic responses were also carried out. And the results show that the discrepancy between the analytical and the computed of fundamental frequency is less than 3%, the error of dynamic displacement is within 10%, and the fundamental frequency of the structure decreases with the increase of the tower top additional mass ratio.

Damage detection in power transmission towers using machine learning algorithms

The purpose of this study is to utilize machine learning techniques to detect any damages that occurred in power transmission towers. In the first step, various machine learning algorithms were employed for a structural model with a small number of members so that the most efficient algorithm was selected based on the accuracy criterion. Then, the selected method was evaluated using acceleration responses obtained from larger power transmission towers in various states. It is worth mentioning that the parameters of the learning algorithms have been optimized by the Bayesian Optimization (BO) algorithm. Responses of three case studies, including 25-, 36-, and 160-member structures, under environmental vibrations, were polluted to 10% noise to simulate the field condition. Studies conducted on selecting the best classifier in detecting damages in these structures indicate that the Support Vector Machine (SVM) algorithm, with an approximate average of 96%, has the highest accuracy among different utilized algorithms. Moreover, the Linear Discriminant Analysis (LDA) algorithm, with an approximate average of 94%, is the second most accurate algorithm, and its computational cost is lower than the SVM algorithm. The results stemming from investigations of case studies show that the chosen features and method seem appropriate for identifying power transmission towers’ damages. Finally, a study was conducted to investigate the impact of the number of input records on accuracy.

A moment-matching method for fragility analysis of transmission towers under straight line winds

A moment-matching method for fragility analysis of transmission towers under straight line winds

Application of BPNN Optimized by Fireworks Algorithm on Structural Bearing Capacity Analysis of Transmission Tower under Icing Conditions

With the increasing power demand in city development, the construction and application of transmission towers need to meet higher requirements. Icing is an extreme meteorological condition in the world, and icing disasters cause various accidents such as tower collapse and line disconnection of large-area lines every year. Therefore, it is of great significance to study the ultimate bearing capacity of transmission towers under icing conditions. The structural bearing capacity under icing is greatly affected by meteorological conditions and environmental factors, which has strong randomness and complexity, and brings a series of urgent problems to the structural stability of transmission towers. In the paper, the ultimate bearing capacity analysis and failure path research are conducted on the 500 kV linear cathead tower structure, and a structural bearing capacity prediction model based on the fireworks algorithm (FWA) is established. In order to accurately predict the structural bearing capacity, reduce the adverse effects of line icing, and ensure the structural stability of the transmission tower, the FWA is introduced into the neural network model. The self-adjusting mechanism of the local search ability and global search ability of the FWA is used to optimize the optimization process of weights and thresholds in the neural network, and a structural bearing capacity prediction model based on the FWA improved backpropagation neural network (BPNN) is proposed. Through the analysis and calculation of the measured data of the transmission tower in a certain area, and the comparative study with the traditional BPNN and the BPNN optimized by other common algorithms, the analysis and calculation results of the FWA-BPNN model used in this paper are closer to the actual value, the multiple indicators are more superior, and the model is more stable, which can realize the rapid and accurate analysis of the axial stress of tower members and maximum displacement between member nodes of the transmission tower under the icing condition.

Feature Enhancement Using Multi-Baseline SAR Interferometry-Correlated Synthesis Images for Power Transmission Tower Detection in Mountain Layover Area

The detection performance of power transmission towers in mountainous areas using SAR amplitude images is obviously influenced by the strong layover background (mainly including vegetation and soil) clutter interference around the towers. In this paper, power transmission tower detection in a mountainous layover area, using single-baseline SAR interferometry coherence images, which show better feature enhancement effectiveness compared to SAR amplitude images, is presented. Moreover, a novel feature enhancement method, that of generating multi-baseline SAR interferometry-correlated synthesis images for power transmission tower detection in a mountain layover area, is proposed. It demonstrates better feature enhancement (layover background cluster suppression) than that using single-baseline SAR interferometry coherence images. Theoretical analysis illustrates that the mountainous layover background clutter interference can be suppressed in the proposed single-baseline/multi-baseline SAR interferometry-correlated synthesis image. Experiments including over 12 repeat-pass TerraSAR-X staring spotlight mode acquisitions were conducted, and the results demonstrate that the detection performance with the use of multi-baseline SAR interferometry-correlated synthesis images showed an improvement of more than 43.6%, compared with the traditional method of using SAR amplitude images when benchmark deep learning-based detectors are used, i.e., Faster RCNN and YOLOv7.

Experimental study on structural damage identification of multi-sensor separated channel network

Structural damage identification, the core driver of structural health monitoring (SHM), has gradually shifted to data-driven models in recent years. For the characteristics of multi-sensors in the SHM system of buildings, this paper proposes a neural network structure for damage identification called multi-sensor separated channel network (MSSCN). It is dedicated to extracting damage sensitive features from a single measurement channel while maintaining the spatial information of the sensor, thus completely decoupling intra-channel time and inter-channel spatial features. The proposed framework is validated by applying to the Qatar University Grandstand Simulator (QUGS) with a decentralized sensor arrangement. Further, we study vertical structures with strong channel correlation via experiments simulating linear and nonlinear multiple complex operating conditions to identify damage in transmission tower. Based on the above, it is demonstrated that the proposed model exhibits good diagnostic capability and performs competitive in noise immunity and small sample tests.