Bayesian Operational Modal Analysis with Interactive Optimization for Model Updating of Large-Size UHV Transmission Towers
Yanming Zhu, Qing Sun, Chao Zhao, Hao Qi, Youhua Su
Abstract
Up to date, few studies on the dynamic characteristics analysis and model updating of large-size ultrahigh-voltage (UHV) transmission towers with long cross arms have been conducted due to the lack of onsite measurement data. In this paper, a framework for vibration test–based dynamic characteristics analysis and model updating of UHV transmission towers is proposed using a fast Bayesian fast Fourier transform (FFT) method with an interactive optimization approach. The dynamic response of a T-shaped ±800-kV UHV transmission tower is achieved by performing an ambient vibration test. The dynamic characteristic parameters (frequencies, damping ratios, and mode shapes) of the structure are obtained by using the fast Bayesian FFT method. Meanwhile, the relevant uncertainty of the identified parameters is also quantified. Then, an interactive optimization approach is presented to update the model using a set of automatic model correction schemes based on the particle swarm optimization algorithm. The interactive optimization approach is implemented by the continuous iteration process between the software MATLAB and ANSYS. The proposed interacting pattern could be well applied to the model updating of the transmission towers. This study could provide a reference for the field test, structural design, and safety evaluation of UHV transmission towers.