Bayesian inference based parametric identification of vortex-excited force using on-site measured vibration data on a long-span bridge

Liu P.; Chu X.; Cui W.Zhao L.Ge Y.

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Bayesian inference based parametric identification of vortex-excited force using on-site measured vibration data on a long-span bridge

机译：Bayesian inference based parametric identification of vortex-excited force using on-site measured vibration data on a long-span bridge

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? 2022 Elsevier LtdIn recent years, vortex-induced vibration (VIV) events have occurred on several long-span suspension bridges around the world. Normally, the VIV of a long-span bridge is investigated in wind tunnel tests or computational fluid dynamics. However, examination of bridge VIV through full-scale field test data has rarely been conducted. Because of the rapid development of high precision sensors and high-frequency data transmission devices, the acquisition of structural modal information utilizing field test data from structural health monitoring systems is emerging as a powerful tool to explore the structural dynamic status and locate potential damage. Therefore, it is possible and necessary to inspect the bridge VEF (vortex-excited force) parameters from full-scale field test data and then to simulate and estimate the structural VIV response based on VEF parameters. Existing VEF parametric identification techniques allow structures (sectional model or full-scale bridges) to be tested under laminar flow in wind tunnel tests with known dynamic properties (inertial frequency and damping ratio), requiring measurement of responsive signals and VEF signals synchronously. However, for the actual field test of the full-scale bridge, the flow field is turbulent, and the structural responsive signal is unavoidably contaminated by measuring noises. Furthermore, it is impractical to synchronously record the aerodynamic force applied on the bridge deck during the field test. In this study, a Bayesian inference approach is introduced for the identification of VEF parameters using field vibration data. Using the fast Fourier transform (FFT) of field vibration data, a frequency domain formulation is proposed focusing on the structural vibration mode excited during VIV events. This method fully considers the influence of random vibration induced by ambient excitation and instrument measurement error on the field vibration data, and only the responsive data are needed without measuring the aerodynamic force information.

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《Engineering structures》 |2022年第1期|114597.1-114597.13|共13页
作者
Liu P.; Chu X.; Cui W.Zhao L.Ge Y.;
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作者单位

State Key Lab of Disaster Reduction in Civil Engineering Tongji University||Department of Bridge Engineering College of Civil Engineering Tongji University;

State Key Lab of Disaster Reduction in Civil Engineering Tongji University||Tongji UniversityTongji UniversityTongji University||Department of Bridge Engineering College of Civil Engineering Tongji University;

|Key Laboratory of Transport Industry of Win;

State Key Lab of Disaster Reduction in Civil Engineering Tongji University||Department of Bridge Engineering College of Civil Engineering Tongji University||Key Laboratory of Transport Industry of Wind Resistant Technology for Bridge Structures Tongji Uni;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
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关键词
Bayesian inference; Field monitoring; Parametric identification; Vortex-induced vibration;

Bayesian inference based parametric identification of vortex-excited force using on-site measured vibration data on a long-span bridge

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