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.

在大跨度桥梁模型的风洞试验中，为确保模型的动力特性能够满足试验设计要求，准确识别模型的模态参数尤为重要。首先，在风洞试验中，采用随机子空间识别算法对模型的模态参数进行分析。然后，引入Grubbs准则以有效消除阻尼比矩阵中的离群值。采用Grubbs准则的随机子空间识别算法提高了模态参数识别的准确性，并提高了确定系统矩阵阶的能力，并避免了通过在稳定性图中确定阻尼比的稳定条件而引起的模态遗漏。最后，以江大桥为例，以Grubbs准则验证随机子空间识别算法，并与有限元方法的结果进行比较。算例表明，该改进方法可以有效地应用于桥梁的模态参数识别。