【作者】 罗延忠；

【导师】 陈政清；

【作者基本信息】 湖南大学 ， 桥梁与隧道工程， 2008， 博士

【摘要】 气动导数是描述桥梁结构气动性能的重要参数。桥梁抗风研究的精细化,对桥梁结构气动导数的识别精度提出了更高的要求。如何准确有效地获得气动导数,已成为桥梁抗风研究的重要课题之一。本文针对这个问题进行了深入的理论和试验研究,主要研究内容与成果如下:1.在ILS法的基础上,本文提出了系统矩阵识别的分段扩阶最小二乘迭代算法(Subsection Extended Order Iterative Least Square Algorithm,简称SEO-ILS法)。SEO-ILS法能利用节段模型风洞试验的自由振动信号,直接识别系统矩阵,同时可得到复模态参数和实模态参数,可为自由振动法识别气动导数提供一种比较可靠的手段。2.对节段模型风振试验的信号预处理技术进行了研究。采用小波的信号分解和重构技术,先去除实测信号的高频噪声,再做无相位失真的低通滤波。无偏心节段模型参数的仿真识别表明,本文对信号的预处理技术能有效地提高识别精度。3.应用拉格朗日方程,建立了风洞中弹性悬挂的二自由度桥梁节段模型质心的竖向和扭转运动方程。所建立竖向和扭转运动方程,不仅考虑了质量中心与弹性中心的偏移,而且考虑了质量中心与竖向阻尼力中心的偏移,使桥梁节段模型振动的数学模型更加完善。4.给出了利用SEO-ILS法识别气动导数的方法。通过平板气动导数的识别结果与理论解的对比,验证了SEO-ILS法识别气动导数的可靠性。桥梁节段模型风洞试验表明,SEO-ILS法的识别精度高,重复性和稳定性好。对于有偏心的桥梁结构,考虑偏心影响有助于气动导数识别精度的进一步提高。5.探讨了几种比较典型的桥梁断面的气动导数特性。通过改变SEO-ILS法识别平板模型气动导数时的计算参数,对其识别精度和气动导数的变异性进行了尝试性研究。研究结果表明,SEO-ILS法识别气动导数稳定可靠,无量纲风速较高时气动导数识别的变异系数小。更多还原

【Abstract】 Aerodynamic derivatives are important parameters to characterize the aerodynamic property of bridge structures. Refined research concerning bridge wind-resistant analysis needs better identification precision in the aerodynamic derivatives of bridge deck. So how to obtain these parameters accurately and effectively is one of main concerns in wind-resistant study of long-span bridges. Motivated with this necessity, this dissertation focuses on theoretical and experimental approaches to the identification of aerodynamic derivatives. The main contents are as following:1. Based on Iterative Least Square (ILS) method, the Subsection Extended Order Iterative Least Square algorithm (SEO-ILS) for system identification in time domain is presented firstly. The SEO-ILS algorithm is able to directly identify system matrix from free vibration data of bridge deck sectional model via wind tunnel test. By using the SEO-ILS algorithm, complex and real mode parameters may also be obtained simultaneously. The numerical simulation results indicate that the proposed method performs comparably with the traditional ILS method in identifying stiffness coefficients while provides better performance in identifying damping coefficients. The SEO-ILS algorithm is finally applied to identify the stiffness and damping matrix of an elastically-suspended sectional model by using the wind tunnel testing data.2. The measurement noise in wind tunnel testing data is detrimental to achieve a better identification results. A technique based on wavelet technique and low-pass filter is examined to preprocess measurement data and eliminate the measurement noise in data. High-frequency noise is firstly eliminated from the testing data by using the wavelet reconstruction and decomposition technique, and a zero-phase low-pass filter is then applied to the reconstructed data. The numerical results show that the noise-elimination method effectively improves the identified accuracy when performed in conjunction with the SEO-ILS algorithm.3. The equations of motion for bridge deck section model elastically suspended in wind tunnel are formulated about mass center of the system using the Lagrangian approach, accommodating both the elasticity eccentricity and damping eccentricity in the formulation. With this formulation, the SEO-ILS algorithm is applied in the state space for direct identification of the system matrix from free vibration data of section model obtained from wind tunnel testing. This formulation complements the existing theory concerning the basic formulation of bridge flutter derivatives identification to consider the unexpected eccentricities in model testing.4. The SEO-ILS algorithm is applied to identify aerodynamic derivatives by using wind tunnel testing data. A thin plate model was tested in wind tunnel and the eight aerodynamic derivatives were estimated by SEO-ILS algorithm. The reliability and effectiveness of SEO-ILS method are demonstrated by comparing the experimentally obtained aerodynamic derivatives of thin plate with theoretical values. The test of bridge deck sections model in wind tunnel indicate that parameter identification of the SEO-ILS method has higher precision, stability and repeatability are better as well as. Considering eccentricities influence for bridge deck is shown to improve the identification precisions of aerodynamic derivatives.5. Aerodynamic derivatives characteristic of bridges both streamlined and bluff decks were discussed thoroughly. Identification precisions and variability of aerodynamic derivatives were investigated by changing hyper-parameters of SEO-ILS algorithm. The results indicate that obtained aerodynamic derivatives by SEO-ILS method are stability and reliability, and variability of aerodynamic derivatives are very small at higher reduced wind speed.更多还原