Identification of Flutter Derivatives of Bridge Decks in Wind Tunnel Test by Stochastic Subspace Identification

In this paper, the covariance-driven stochastic subspace identification technique (SSI-COV) was presented to extract the flutter derivatives of bridge decks from the buffeting test results. An advantage of this method is that it considers the buffeting forces and responses as inputs rather than as noises. Numerical simulations and wind tunnel tests of a streamlined thin plate model conducted under smooth flows by the free decay and the buffeting tests were used to validate the applicability of the SSI-COV method. Then, the wind tunnel tests of a two-edge girder blunt type of industrial-ring-road (IRR) bridge deck were conducted under smooth and turbulence flows. The flutter derivatives of the thin plate model identified by the SSI-COV technique agree well with those obtained theoretically. The results obtained for the thin plate and the IRR bridge deck are used to validate the reliability and applicability of the SSI-COV technique to various wind tunnel tests and conditions of wind flows. The results also show that for the blunt-type IRR bridge deck, the turbulence wind will delay the onset of flutter, compared with the smooth wind.

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Data-driven stochastic subspace identification of flutter derivatives of bridge decks

Journal of Wind Engineering and Industrial Aerodynamics ◽

10.1016/j.jweia.2010.07.003 ◽

2010 ◽

Vol 98 (12) ◽

pp. 784-799 ◽

Cited By ~ 24

Author(s):

Virote Boonyapinyo ◽

Tharach Janesupasaeree

Keyword(s):

Bridge Decks ◽

Data Driven ◽

Subspace Identification ◽

Stochastic Subspace Identification ◽

Derivatives Of ◽

Flutter Derivatives

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Modal parameters identification of bridge by improved stochastic subspace identification method with Grubbs criterion

Measurement and Control ◽

10.1177/0020294021993831 ◽

2021 ◽

Vol 54 (3-4) ◽

pp. 457-464

Author(s):

Yulin Zhou ◽

Xulei Jiang ◽

Mingjin Zhang ◽

Jinxiang Zhang ◽

Hao Sun ◽

...

Keyword(s):

Wind Tunnel ◽

Parameter Identification ◽

Damping Ratio ◽

Wind Tunnel Test ◽

Modal Parameters ◽

Subspace Identification ◽

Identification Algorithm ◽

Modal Parameter ◽

Modal Parameter Identification ◽

Stochastic Subspace Identification

In the wind tunnel test of a long-span bridge model, to ensure that the dynamic characteristics of the model can satisfy the test design requirements, it is particularly important to accurately identify the modal parameters of the model. First, the stochastic subspace identification algorithm was used to analyze the modal parameters of the model in the wind tunnel test; then, Grubbs criterion was introduced to effectively eliminate outliers in the damping ratio matrix. Stochastic subspace identification algorithm with Grubbs criterion improved the accuracy of the modal parameter identification and the ability to determine system matrix order and prevented the modal omissions caused by determining the stable condition of the damping ratio in the stability diagram. Finally, Oujiang Bridge was used as an example to verify the stochastic subspace identification algorithm with Grubbs criterion and compare with the results of the finite element method. The example shows that the improved method can be effectively applied to the modal parameter identification of bridges.

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