Transmission Tower Research Articles

Ultimate bearing capacity of T-shaped retrofitting diagonal members for angle steel transmission towers

Collapse of steel latticed transmission towers under strong winds is a significant safety concern for power systems. Attaching additional members to the tower members can enhance the wind resistance of transmission towers. To establish systematic retrofitting schemes and methods for predicting the ultimate bearing capacity of T-shaped retrofitting diagonal members, static experiments and finite element analysis on various cross-sectional dimensions and member lengths were utilized in this study. The experimental results indicate that retrofitting can effectively increase the bearing capacity of diagonal members. Finite element models are developed and verified based on the discussion of load-displacement curves and failure modes. The finite element analysis reveals that the increase in capacity achieved by reducing connector spacing is relatively small when compared to the ultimate bearing capacity obtained with the spacing of two connectors, and the arrangement of connectors at both ends meets the requirement of connector spacing. The relationship between the retrofitting bearing capacity and the slenderness ratio of diagonal members can be divided into two linear stages, which correspond to different failure modes. Furthermore, a λk coefficient method based on the axial compression equation is proposed to predict the ultimate bearing capacity of T-shaped retrofitting members. The bearing capacity based on the λk method shows agreement with finite element analysis results.

The Effect Of Human Resources Management On The Success Of Electricity Projects (Tower Transmission) In West Papua Province

<span>he development of electricity facilities and infrastructure plays a vital role in supporting the economic, social, and cultural activities of a nation. The success of construction projects, including transmission towers, can be measured based on the triple constraint, namely correct quality, timely and cost-effective. These three things can be achieved through human resource management. This study aims to measure the influence of human resource management which includes HR planning, project leadership support, organizational structure, and provision of training on the success of electricity projects (transmission towers) in West Papua Province. This study uses a cross-sectional approach to determine the relationship among the variables studied. The population of this study is all workers involved in the transmission construction project of the work tower SUTT Aimas – Sorong (AS) and SUTT Sorong – Rufey (SR). Data collection was carried out through interviews and questionnaires with a sample size of 35 respondents determined by purposive sampling. A partial disaggregation approach with Structure Equation Modeling - Partial Least Square using SmartPLS was carried out to measure the causal relationship among the observed variables. Based on hypothesis testing, it was identified that each variable influences the success of the electricity project, where the provision of training has the greatest influence, positive and significant where the t - <sub>value </sub>is 2.269 and </span><span>r</span><span>0.673; human resource planning has a moderate, positive and significant effect where the t - <sub>value </sub>is 0.374 and </span><span>r</span><span>0.389; project leadership support has a moderate effect, but positive and significant where the t - <sub>value </sub>is 0.182 and </span><span>r</span><span>0.354, while the organizational structure has an insignificant and non-unidirectional effect where the t- <sub>value is </sub>0.225 and </span><span>r</span><span>-0.393. Overall the goodness of the model in measuring the relationship between the four factors on project success is shown by the R2 value of 0.880 which is categorized as a strong influence</span>

A two-stage automated OMA framework for transmission towers based on clustering algorithms

Automated operational modal analysis (OMA) is a significant basis for structural health monitoring (SHM) of transmission towers. There have been many effective uses of automated OMA algorithms during the past decade. However, several unresolved issues still require further investigation, particularly in the following areas: i) Minimizing the number of parameters to achieve full automation; ii) Defining the optimal parameters to significantly reduce spurious modes; iii) Exploring an automated OMA framework for transmission towers. In this study, we propose an automated OMA method for transmission towers based on the clustering algorithms with the stochastic subspace identification (SSI) approach. The proposed method could be summarized in two stages: the “rough” and “enhanced” stages. In the “rough” stage, the modes identified by SSI are divided into possible physical modes and certain spurious modes by the k-means algorithm considering the physical meaning of the modal parameters. In the “enhanced” stage, similar physical modes are classified by data-driven hierarchical clustering, and the outliers of each cluster are eliminated. Then, the applicability and efficiency of the proposed method are verified by the numerical simulation. Finally, the method is applied to a ± 500 kV transmission tower to identify the modal parameters with the field ambient vibration test data. Identification results are compared with manual identification to demonstrate the improvement and contribution of the automated OMA. The results show that the proposed framework has the capacity to automatically eliminate spurious modes and discrimination in the case of the close modes. The proposed method could accurately and automatically identify modal parameters to avoid the dependence on the experience and the uncertainty of manual identification.

EVALUATION OF CLOUD TO GROUND FLASH DENSITY OF 150 KV TRANSMISSION LINE BETWEEN PARIT BARU SUBSTATION AND SENGGIRING SUBSTATIO

SUTT is a high voltage overhead line with a power of 70 kV - 150 kV to distribute electric power from the generating center to the substation or from substation to substation. The purpose of this study was to obtain modeling of lightning strike density on the 150 kV transmission line between Parit Baru substation and Senggiring substation using geostatistical approaches, namely IDW methods (Inverse Distance Weighted). In identifying the level of vulnerability to lightning strikes, Cloud to Ground lightning event data (2018–2020) is used. The aim of this research is to obtain the density pattern of lightning strikes on the 150 kV transmission line between the Parit Baru substation and the Senggiring substation. The process in ArcGIS 10.8 software aims to obtain lightning strike density and display the results of the lightning strike density map. Based on the results of data processing for 3 years, the highest density of lightning strikes occurred in 2019 in Segedong District at 54.52 strikes/km². Meanwhile, the lowest density of lightning strikes occurred in 2018 in East Mempawah District, amounting to 2.86 strikes/km². Based on the lightning strike density map per grid on the 150 kV transmission line between Parit Baru substation and Senggiring substation for 3 years, the results obtained for the highest lightning strike were 36 strikes/km² while for the lowest strike it was 1 strike/km². From this research, it was found that there were 15 transmission towers that passed a high density of lightning strikes with a strike range of 25–36 strikes/km² and the highest lightning strike occurred at tower number 31, number 30, and number 29, amounted to 36 strikes/km².

Wind-Induced Response Analysis of the Transmission Tower-Line System Considering the Joint Effect

Wind load is one of the main control loads of transmission tower-line systems. Numerical simulation is the main method for studying the structural wind-induced response. The establishment of a refined transmission tower simulation model is the basis for accurately analyzing the dynamic response of a transmission tower-line system under a wind load. This paper first considered the mechanical properties of bolted joints under cyclic loading and established a transmission tower-line system model considering the joint effects. Then, the wind load was generated by the harmonic superposition method, and the wind dynamic time-history analysis of the tower-line system was conducted. The influence of the joint effect on the wind-induced response of the transmission tower-line system was studied, and the effects of turbulence intensity and wind attack angle on the bolted joint slip effect were discussed. The results showed that the joint effect significantly increased the displacement response of the transmission tower subjected to wind loads and affected the normal service performance of the tower-line system. When the turbulence intensity is 10%, the top displacement of the tower model considering the joint effect is approximately 2 times that of the ideal rigid frame model. After considering the joint effect, the additional [Formula: see text] effect caused by the increased displacement resulted in an increase in the stress of 75.6% members, and the maximum stress of the main member was located near the upper diaphragm of the tower leg. Therefore, considering the joint slip effect in angle steel transmission towers can improve the accuracy of the dynamic response analysis of transmission lines.

Geometric Nonlinear Analysis of Angle Section Elements Based on Updated Lagrangian Formulation and Rigid Body Rule

Angle cross-section members are widely used in various transmission towers owing to their convenient connections, easy availability, simple production processes, and high efficiency. Such members are very susceptible to nonlinear behavior when subjected to abnormal or extreme loads. In this work, a new geometric stiffness matrix for thin-walled steel members with an angle cross-section is derived based on the principle of virtual displacement, rigid body rule and updated Lagrangian equations. The generalized displacement control (GDC) method is employed to deal with the issues of non-convergence at the extreme value point and rebound point in the geometric nonlinear analysis, which offers clear physical meaning and can adjust the loading direction. The geometric and the traditional elastic stiffness matrices derived in this work are applied during the prediction phase, while only the traditional elastic stiffness matrix is used in the correction phase. The comparisons of the results obtained by the proposed method with those in the previous literature and ANSYS numerical solutions show that the proposed method is sufficient to ensure the accuracy and applicability for addressing the structural geometrically nonlinear issues.

Full-scale evaluation of creep coefficients and viscoelastic moduli in honeycomb sandwich pultruded GFRP composite cross-arms: Experimental and numerical study

The utilization of pultruded glass fibre-reinforced polymer composites (PGFRPC) to replace traditional wooden cross-arms in high transmission towers is a relatively recent development. While there have been numerous investigations into enhancing cross-arm structures, there remains a notable absence of research focused on the elastic characteristics of a full-scale PGFRPC cross-arm, particularly one enhanced with a honeycomb sandwich structure. To full-fill the gap, this paper presents an experimental and numerical study through cantilever beam flexural tests on assembled cross-arm condition to examine deflection behavior and the flexural creep response. For deflection behavior, the load was applied up to actual working load. For creep behavior, the hanging load was applied for 1000 h in open area condition followed ASTM D2990 standards. By using Findley's power law, confirming the ability of this empirical approach to simulate the viscoelastic response of the cross-arm. The results obtained prove that the addition of a honeycomb sandwich structure reduced deflection and improved resilience against bending forces, enhancing specific points' elastic modulus slightly. Long-term creep tests revealed Point Y3 had the highest strain, but the enhanced cross-arm displayed superior resistance and a shorter viscoelastic transition period, indicating increased stability. Besides that, the Findley's Power Law Model effectively represented creep behavior for both cross-arm types, with low errors. Over 50 years, both versions showed a significant reduction in average elastic modulus, with the enhanced variant 20 % stronger due to the honeycomb structure. In conclusion, this study validates the superior creep properties of the enhanced PGFRPC cross-arm and demonstrates the honeycomb sandwich structure's substantial role in increasing strength and extending the cross-arm's lifespan, making it a valuable enhancement for such applications.

Flexible resource optimal allocation strategy for distribution system resilience improvement under failure uncertainty

Extreme disasters have led to huge economical losses to the power system and posed a huge threat to the stable supply of electric energy. Especially for traditional passive distribution network systems, failures of transmission lines, towers, and other equipment will cause large-scale power outages and huge economic losses. In order to improve the ability of the power system to deal with extreme weather disasters, this paper proposes an optimal configuration strategy for the distribution network backup power resource oriented to resilience improvement, considering the uncertainty of equipment failure caused by disasters in the case of a known disaster range. The location and capacity of backup resources can be properly configured to reduce the load shedding of the power distribution network during the disaster process, thereby improving the resilience of the distribution network. The method proposed in this paper is modeled as a two-stage stochastic programming, which includes mix-integer constraints. In the first stage, the optimization problem confirms the capacity and location of the flexible resources. In the second stage, the operational constraints and costs of load shedding are considered. The resilience enhancement method is verified on the improved IEEE-33 node system, and the result shows that the method proposed in this paper can effectively enhance the resilience of the urban power network.

RCDAM-Net: A Foreign Object Detection Algorithm for Transmission Tower Lines Based on RevCol Network

As an important part of the power system, it is necessary to ensure the safe and stable operation of transmission lines. Due to long-term exposure to the outdoors, the lines face many insecurity factors, and foreign object intrusion is one of them. Traditional foreign object (bird’s nest, kite, balloon, trash bag) detection algorithms suffer from low efficiency, poor accuracy, and small coverage, etc. To address the above problems, this paper introduces the RCDAM-Net. In order to prevent feature loss or useful feature compression, the RevCol (Reversible Column Networks) is used as the backbone network to ensure that the total information remains unchanged during feature decoupling. DySnakeConv (Dynamic Snake Convolution) is adopted and embedded into the C2f structure, which is named C2D and integrates low-level features and high-level features. Compared to the original BottleNeck structure of C2f, the DySnakeConv enhances the feature extraction ability for elongated and weak targets. In addition, MPDIoU (Maximum Performance Diagonal Intersection over Union) is used to improve the regression performance of model bounding boxes, solving the problem of predicted bounding boxes having the same aspect ratio as true bounding boxes, but with different values. Further, we adopt Decoupled Head for detection and add additional auxiliary training heads to improve the detection accuracy of the model. The experimental results show that the model achieves mAP50, Precision, and Recall of 97.98%, 98.15%, and 95.16% on the transmission tower line foreign object dataset, which is better to existing multi-target detection algorithms.

In-situ measurements of temperature and strain fields of large-diameter concrete-filled steel tube columns and the refined finite element modeling

Concrete-filled steel tube (CFST) columns are prevalent in transmission towers and arch bridges due to their cost-effectiveness and superior mechanical performance. The growing megastructures lead to large-diameter CFST components, which are exposed to the risk of early-age thermal concrete cracking. In this study, temperature and strain fields of two 2.1 m-dia. CFST columns were monitored in-situ. Within 30 h, the peak temperature and tensile strain at the centroid reached 97.0°C and 400 με, respectively. Meanwhile, temperature fields of eight scaled CFST columns were also monitored and compared. In addition, ultrasonic pulse velocity test was performed to detect the early-age thermal cracking. To predict the temperature and strain evolutions accurately, a refined numerical model is proposed, considering coupled mechanical, hydration and thermal processes. It is revealed that the model could accurately predict the temperature and strain evolutions of CFST columns. Furthermore, experiments and numerical simulations illustrate that thermal cracking would likely be triggered in CFST components with diameter greater than 1.2 m.

Research on loose bolt localization technology for transmission towers

Research on loose bolt fault in transmission towers is difficult to detect, and the localization of the loose bolts has always been a challenge in the field of structural health monitoring. This article investigates the relationship between the modal frequencies and modal shapes at different levels and finds that when bolts in transmission towers become loose, the order of modal frequency changes is consistent with the order of the mode shape at the location of the loosening. Based on this, a new method for locating loose bolts in transmission towers is proposed. In the identification of mode parameters, an improved variational mode decomposition is used to extract the mode components at different orders. A modal frequency identification method based on feature set signal reconstruction is proposed, which is based on the modal correlation between the signal components from different sensors, effectively preserving and extracting the structural modal characteristics from the vibration response. At the same time, the identification of modal shapes in transmission towers is achieved through feature-level fusion based on adaptive multi-sequence signals, greatly reducing identification errors. The effectiveness of this method is validated in the finite element analysis of transmission towers, and its superiority is demonstrated through comparison with more advanced methods. The results of a 110 kV transmission tower bolt loosening test also show that this method can accurately identify the area where the bolts are loose, with high identification accuracy, providing a new approach for the localization of loose bolts in transmission towers.

Vibration feature extraction and fault detection method for transmission towers

AbstractThis paper presents a novel bolt looseness detection method for power transmission towers based on vibration signal analysis. The proposed method utilizes pulse excitation to extract the vibration signal of the tower, which is then adaptively decomposed using the Variational Mode Decomposition of Spider Wasp optimizer (SWVMD). This overcomes limitations of traditional Variational Mode Decomposition methods by leveraging bio‐inspired optimization to improve signal decomposition. Simulated signals processed with different optimization methods verify the superiority of the SWO approach. Field tests on a 110‐kV transmission tower further demonstrate the effectiveness of the proposed SWVMD technique for analyzing on‐site vibration data. A new improved intrinsic multiscale sample entropy feature is also introduced for bolt state characterization. A Spider Wasp Support Vector Machine classifier is developed to realize accurate bolt loosening monitoring using the extracted features. Dynamic response tests under varying bolt conditions show that the method can identify early loosening and reduce tower damage risks compared to conventional techniques. This novel vibration‐based detection framework presents an innovative application of nature‐inspired computing for power infrastructure health monitoring.

Overvoltages caused by direct lightning strokes to a hybrid overhead line

This paper presents an analysis of the overvoltages caused by direct lightning strokes to a hybrid overhead line with 138 kV, 13.8 kV, and 220 V circuits. The primary focus is on medium voltage line overvoltages and their dependence on key parameters, including ground impedance, soil resistivity, stroke current front time, conductor characteristics, lightning channel impedance, insulator capacitance, conductors' sags, and tower surge impedance. Using specific models for the transmission tower and high-voltage insulators, validated through laboratory tests and EMTP simulations, critical currents are determined for varying soil resistivity and impulse impedances. The analysis confirms the line robust performance against stroke-induced backflashovers.

Looseness Monitoring of Transmission Tower Based on MIMU

Looseness Monitoring of Transmission Tower Based on MIMU

Flexural creep response of honeycomb sandwich pultruded GFRP composite cross-arm: Obtaining full-scale viscoelastic moduli and creep coefficients

The application of pultruded glass fibre-reinforced polymer composites (PGFRPC) as a replacement material for conventional wooden cross-arm in high transmission towers is relatively new. Although there are several studies on enhancement of the cross-arm structure, there is still a lack of study on the elastic properties of a full-scale PGFRPC cross-arm enhanced with honeycomb sandwich structure. To full-fill the gap, this paper describes an experimental methodology used to obtain the elastic properties of the cross-arm using a three-point bending (3-PB) flexural test by following ASTM D790 standard for deflection behaviour and flexural creep response. The investigation involved several cross-arm members subjected to loading across different span lengths by propose two methods in order to measure the effective cross-arm member section flexural modulus (Ec) and shear modulus (Gc). The creep behaviour of the panels was successfully modeled using Findley's power law, confirming the ability of this empirical approach to simulate the viscoelastic response of the cross-arm. Next predictions were made for up to 50 years of service and the results shows the elastic modulus reduction for the enhanced cross-arm with the honeycomb sandwich structure was approximately reduce to 70 % compare with existing cross-arm which reduce almost 75 % at 50 years of application. The enhanced cross-arm exhibited lower deflection and better creep resistance and increased the bending strength of the cross-arm as well as extended its potential lifespan. Predictions indicated that the enhanced cross-arm maintained better mechanical properties over time compared to the existing one.

Probabilistic assessment of anchor foundation for transmission tower using multivariate adaptive regression splines

ABSTRACT This paper pertains to the reliability analysis of transmission tower foundations under variable wind loads. The reliability analysis of the anchor foundation, frequently employed for transmission towers due to their huge uplift capacity at shallow depth, is presented using a systematic probabilistic approach. The paper presents the design of an anchor foundation for a typical transmission tower based on loads obtained by applying lateral wind velocity on the tower. The Multivariate Adaptive Regression Splines (MARS) surrogate model is first developed to construct a deterministic prediction model for the anchor uplift capacity. The developed model is further used in the reliability analysis of the anchor foundation considering variabilities in the soil properties and the uplift load, and the results of the probabilistic analysis are reported in the paper. The results indicate the importance of incorporating variability in design variables for the proper safety of the structure. Soil cohesion is found to be the most sensitive parameter in the uplift capacity of the tower foundation. The comparison of the deterministic factor of safety and failure probability of the foundation brings out the importance of the reliability-based design methodology.

The use of S460 steel grade in the construction of OHL transmission towers

AbstractThe article describes structural solutions and specialised testing of innovative steel lattice towers intended for 400 kV overhead line (OHL). A unique aspect of the preformed research is the use of S460 steel grade in the structure of such transmission towers. This new series of towers was developed in reference to current EN 50341‐2‐22:2016 standard that introduces higher safety standards for OHL towers. A full‐scale prototype was developed and analysed, where the verification of the standard load‐bearing capacity was done and proceeded by the destructive test in order to determine the ultimate capacity of the new tower typology. The article presents the obtained results, the justification for the use of S460 steel grade and a comparative analysis with the classical engineering procedures. A good agreement between a theoretical model and the test results is demonstrated.

Transmission Tower Re-Identification Algorithm Based on Machine Vision

Transmission tower re-identification refers to the recognition of the location and identity of transmission towers, facilitating the rapid localization of transmission towers during power system inspection. Although there are established methods for the defect detection of transmission towers and accessories (such as crossarms and insulators), there is a lack of automated methods for transmission tower identity matching. This paper proposes an identity-matching method for transmission towers that integrates machine vision and deep learning. Initially, the method requires the creation of a template library. Firstly, the YOLOv8 object detection algorithm is employed to extract the transmission tower images, which are then mapped into a d-dimensional feature vector through a matching network. During the training process of the matching network, a strategy for the online generation of triplet samples is introduced. Secondly, a template library is built upon these d-dimensional feature vectors, which forms the basis of transmission tower re-identification. Subsequently, our method re-identifies the input images. Firstly, we propose that the YOLOv5n-conv head detects and crops the transmission towers in images. Secondly, images without transmission towers are skipped; for those with transmission towers, The matching network maps transmission tower instances into feature vectors. Ultimately, transmission tower re-identification is realized by comparing feature vectors with those in the template library using Euclidean distance. Concurrently, it can be combined with GPS information to narrow down the comparison range. Experiments show that the YOLOv5n-conv head model achieved a mean Average Precision at an Intersection Over Union threshold of 0.5 (mAP@0.5) score of 0.974 in transmission tower detection, reducing the detection speed by 2.4 ms compared to the original YOLOv5n. Integrating the online triplet sample generation into the matching network training with Inception-ResNet-v1 (d = 128) as the backbone enhanced the network’s rank-1 performance by 3.86%.

Joint distribution of lightning and wind speed and its impact on the transmission system

Distribution of lightning plays a key role in lightning protection of transmission lines. The design of wind deviation under lightning overvoltage of the transmission tower is an empirical parameter in the transmission line design code. Meteorological data from Hong Kong are investigated to analyze the joint distribution of lightning and wind speed. It has been uncovered that daily cloud-to-ground (CG) flashes follow the Burr distribution, which is highly skewed toward a few days with notable lightning. The lightning and wind follow a Gumbel copula joint distribution. According to empirical and theoretical distribution, there are 239 days with more than 1,000 CG lightning flashes per day, and approximately 20% of these days have a maximum wind speed of approximately or over 15 m/s. In 5 days with the number of CG lightning flashes above 30,000, 3 days have a maximum wind speed of over 15 m/s and the other 2 days have a maximum wind speed of over 10 m/s, which suggests that the severe convection with a squall line contributes much to the likelihood of the days with high wind and lightning storms.

Analysis and Design of Transmission Tower using Staad-Pro

A transmission tower, also known as an electrical power tower or utility pole, is a tall structure used to support overhead power lines for the transmission of electrical energy. Transmission towers play a critical role in the reliable and efficient transmission of electricity from power generation plants to distribution networks and ultimately to consumers. This abstract provides an overview of transmission towers, including their purpose, types, components, and key considerations in their design and construction. Transmission towers are designed to withstand various environmental and loading conditions, such as wind, ice, and seismic forces while maintaining the integrity and stability of the overhead power lines. Different types of transmission towers, such as lattice towers, tubular towers, and pole towers, are used based on factors such as voltage level, span length, and terrain conditions. Analysis of this transmission tower is administered using STAAD PRO The present work describes the analysis and design of a transmission line tower of 31 meters in height and 220KV double circuit viz. various parameters. The components of a transmission tower typically include tower legs, cross-arms, insulators, and hardware for attaching conductors and ground wires