Statistical Analysis of Wind-Induced Dynamic Response of Power Towers and Four-Circuit Transmission Tower-Line System
Author(s): |
Xiaolei Zhang
Yanzhong Ju Fuwang Wang |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Shock and Vibration, 2018, v. 2018 |
Page(s): | 1-18 |
DOI: | 10.1155/2018/5064930 |
Abstract: |
Only one wind field model loading the transmission tower or the tower-line system was investigated in the previous studies, while the influence of two different wind field models was not considered. In addition, only one sample of the wind speed random process was used in the past numerical simulations, and the multiple dynamic response statistical analysis should be carried out. In this paper, statistical analysis of the wind-induced dynamic response of single towers and the transmission tower-line system is performed with the improved accuracy. A finite element model of the transmission tower-line system (the tower consisted of both steel tubes and angel steels) is established by ANSYS software. The analysis was performed by three statistical methods. The effects of the length of the time history and of the number of samples were investigated. The frequency histograms of samples follow the Gaussian distribution. The characteristic statistical parameters of samples were random. The displacements and the axial forces of the low tower are larger than those of the high tower. Two wind field models were applied to simulate the wind speed time history. In field 1 model, Davenport wind speed spectrum and Shiotani coherence function were applied, while in field 2 model Kaimal wind speed spectrum and Davenport coherence function were used. The results indicate that wind field 1 is calmer than wind field 2. The displacements and the axial forces of the tower-line system are less than those of single towers, which indicate damping of wind-induced vibrations by the transmission line. An extended dynamic response statistical analysis should be carried out for the transmission tower-line system. |
Copyright: | © 2018 Xiaolei Zhang, Yanzhong Ju, Fuwang Wang |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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28/05/2022 - Last updated on:
01/06/2022