论文部分内容阅读
在ERA(Eigensystem Realization Algorithm)的理论框架内建立了误差因子,评估桥梁节段模型风洞实验中气动导数的辨识质量。通过子空间能量分解,分别计算辨识过程中有效识别信号成分能量和未被识别信号成分能量与总信号能量的比值,并以此构造误差因子。将相同实验环境下自由衰减振动和尾流激励随机振动两组实验的误差因子相互比对,判断桥梁节段模型的气弹振动非线性是否对气动导数辨识结果产生影响。依据误差因子判断,在本文所使用的两种节段模型中,部分流线型箱梁断面具有较强的耦合非线性;而槽形开口型断面的模型具有较低的耦合非线性。
The error factor was established within the theoretical framework of ERA (Eigensystem Realization Algorithm) to evaluate the identification quality of aerodynamic derivatives in the wind tunnel test of bridge segment model. Through the subspace energy decomposition, the ratio of the energy of the effective identification signal component energy and the energy of the unidentified signal component to the total signal energy in the identification process is respectively calculated, and the error factor is constructed. The error factors of two groups of random vibration and random vibration under the same experimental environment are compared with each other to determine whether the aeroelastic vibration nonlinearity of the bridge segment model has an influence on the aerodynamic derivative identification results. According to the error factor, in the two segment models used in this paper, some of the streamlined box girder sections have strong coupling nonlinearity; while the slotted open section model has a lower coupling nonlinearity.