To investigate the variation law of the wind-resistant performance of transmission towers during their operation, this paper proposes an evaluation method for the wind resistance of the transmission tower considering corrosion, and a 220-kV transmission tower is analyzed as an example. Considering the uncertainty of the material and geometric parameters, the wind-induced collapse of the transmission tower was analyzed, and the collapse wind speeds were obtained via pushover and incremental dynamic analyses. In addition, the sensitivity of the transmission tower to various parameters was analyzed. Based on the existing meteorological and corrosion data, corrosion prediction models were established using a back-propagation (BP) artificial neural network, and the mean relative error between the predicted and measured values of the test samples was 8.91%. On this basis, the corrosion depth of the tower members in the four regions was predicted, and the fragility of the transmission tower was analyzed considering the effects of corrosion and strong winds. The results show that the collapse wind speed of the transmission tower is most significantly affected by the thickness of the angle steel, followed by the elastic modulus and yield strength, and is less affected by the width of the angle steel. When the exposure time was 25 years, the wind-resistant performance of transmission towers in regions with severe acid rain and coastal industrial regions decreased by 10% to 20%. With an increase in exposure time, the failure mode of the transmission tower tended to be brittle failure.
Transmission towers are prone to collapse under strong wind load, resulting in significant economic losses. In order to investigate the collapse mechanism and failure modes of the transmission tower under strong wind load and whether the wind vibration factor can greatly reflect the increasing effect of the fluctuating wind, the finite element method (FEM) is utilized to analyze the ultimate bearing capacity of a typical 220 kV transmission tower. The results show that the collapse of the tower under strong wind loads is usually due to the buckling of the leg members. When the reference wind speed is equal to 27 m/s, a small part of the main leg members reaches their yield strength, while the diagonal members are still in the elastic range, and the deformation of the transmission tower is unapparent at this wind speed. When reference wind speed is equal or greater than 30 m/s, the growing variety of main legs is totally into the plastic yield stage, and the overall deformation of this tower is visible. Therefore, the transmission tower is collapsed due to the large deformation caused by the elastic-plastic buckling of leg members. Based on the aforementioned study, a finite element model involving three transmission towers and four span transmission lines is established to analyze the dynamic response of the tower-line system below fluctuating wind. Results show that the wind-induced coefficients designed by current code not only notably satisfy the stress response of tower components subjected to fluctuating wind loads in the elastic phase but also accurately assess the collapse displacement of the transmission tower. The increasing effect of displacement on the top tower under fluctuating wind, unfortunately, could not considerably reply with the investigated factor, and the load-carrying capacity of the transmission tower in the plastic phase can be overestimated by static calculation results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.