Statistical Analysis of Wind‐Induced Dynamic Response of Power Towers and Four‐Circuit Transmission Tower‐Line System

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.

PD-Based Iterative Learning Control for the Nonlinear Low-Speed-Jitter Vibration of a Wind Turbine in Yaw Motion

“…To achieve a greater reduction in the jitter, similar yaw system models as those used in the present study were investigated [33][34][35] by using the passive flutter suppression (PFS) method, with yaw vibration and low-speed buffeting discussed. The PFS technique was executed through methods, such as the structural stiffness adjustment design, friction torque matching, and driving-torque size adjustment, etc., and analyzed by using the finite element method.…”

“…Whether it is a tower mode or cabin mode, there is no subdivision here, but it is arranged in numerical order. The comparison is based on the PFS method, using the finite element method in reference [34,35], and the additional motor drive design, using the iterative algorithm in the present study, by directly analyzing the eigenvalues in Formula ( 12). It can be seen that, compared with the PFS system based on the finite element analysis [35], the dynamic system with active control in this study generally reduces the frequency of each order modal, which means that the vibration becomes gentle and even tends to stabilize.…”

“…In the traditional jitter control method, a performance balance method between worm gear self-locking and yaw braking mechanisms was also used to achieve limited LSJ suppression [32], which is a local and passive suppression method. The characteristics of this passive suppression method include stiffness adjustment design, finite element analysis method, and linear LSJ amplitude suppression based on the assumption of a constant yaw rate [33][34][35]. However, the active dynamic control method adopted in the present study not only achieves amplitude suppression, but also frequency suppression, and it can directly handle nonlinear systems, which has a positive significance for engineering applications.…”

Time Series Models and Expansion Optimal Linear Estimation for Time-Dependent Reliability Analysis

“…The works by Singh et al [2011a], Singh et al [2011b], Walls and Bendell [1987], Mignolet and Spanos [1989], Ho and Xie [1998], Billinton and Wangdee [2007] Sohn et al [2000], Fugate et al [2001], , , Owen et al [2001] Omenzetter andBrownjohn [2006], Carden and Brownjohn [2008], Zheng and Mita [2008], Drignei [2011], Bao et al [2013], Yao and Pakzad [2013], Goyal and Pabla [2016], Hu and Mahadevan [2017], Datteo et al [2018], Zhang et al [2018], Wang et al [2021], Samaras et al [1985] and Hu and Mahadevan [2017] employed Time Series models (i.e. AR, ARMA, among others) in the context of structural engineering and Time-dependent Reliability Analysis.…”

Study on Wind-Induced Dynamic Response and Statistical Parameters of Skeleton Supported Saddle Membrane Structure in Arching and Vertical Direction

“…At the same time, the introduction of appropriate statistical parameters is helpful to analyze the distribution law of the wind-induced displacement response of structures and then take effective measures and methods to reduce the displacement vibration. Zhang et al [30] established the finite element model of the transmission tower-line system by ANSYS software, and they statistically analyzed the wind-induced dynamic response.…”