期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2019
卷号：15
期号：1
页码：1
DOI：10.1177/1550147719826843
出版社：Hindawi Publishing Corporation
摘要：This study presents a novel single-degree-of-freedom model of vortex-induced vertical force, which is based on supervised learning. There are three steps in the process of modeling. First, a hypothesis function based on the Taylor expansion is applied to describe the complicated of vortex-induced vertical force. Second, this hypothesis function is optimized by spectrum and correlation analysis. The terms in this function are deleted when they meet one of the following cases: the frequency amplitudes are close to 0; the correlation coefficients with the vortex-induced vertical force are less than 0.3; the correlation coefficients with other low-order terms are more than 0.8. Third, the validity and reliability of the optimized function are verified by comparative and residual analysis. The process of optimization makes the proposed model simple and well describes the main characteristics of vortex-induced vertical forces. Moreover, the maximum displacement is accurately predicted according to the proposed model. Simulation results show that the proposed model has a high coefficient of determination ( R 2 ) compared with Scanlan’s and Zhu’s models, which means that the proposed model is more suitable to describe vortex-induced vertical forces.
关键词：Correlation analysis; frequency analysis; long-span bridge; residual analysis; Taylor expansion; vortex-induced vibration
