识别桥梁断面18个颤振导数的梯度下降算法  

IDENTIFICATION OF 18 FLUTTER DERIVATIVES OF BRIDGE DECKS USING GRADIENT DECLINING ALGORITHM

作　　者：许福友[1] 陈艾荣[2] 张哲[1] 

机构地区：[1]大连理工大学土木水利学院,大连116024 [2]同济大学土木工程防灾国家重点实验室,上海200092

出　　处：《工程力学》2008年第6期81-87,共7页Engineering Mechanics

基　　金：国家自然科学基金资助项目(50708012,50478109);高等学校博士点专项科研基金(20040247026,20070141073)

摘　　要：桥梁断面颤振导数识别问题可转化为最小二乘优化问题,提出了梯度下降算法求解该优化问题,提取桥梁主梁断面18个颤振导数。梯度下降算法在随机搜索过程中引入反馈机制,能够快速搜索到最优解,可用于系统参数识别,并且能够保证精度。采用该算法识别了苏拉马都大桥主梁断面18个颤振导数,并且与随机子空间方法识别结果进行对比分析。给出了现有弹簧悬挂系统自由振动方法识别桥梁断面颤振导数高风速时稳定性较差、侧向颤振导数识别精度相对较低的原因。试验方法是影响颤振导数识别精度的决定性因素,识别方法是相对次要因素。The flutter-derivative identification of bridge decks can be converted into a least-square optimization problem. This problem is solved using the presented gradient declining algorithm （GDA）. The 18 flutter derivatives of bridge deck are extracted subsequently. For GDA, the feedback mechanism is introduced into the stochastic search progress, by which the optimum solution can be searched rapidly. The GDA is applicable to the system parameter identification, and the satisfactory precision can be ensured. The 18 flutter derivatives of Suramadu Bridge deck are identified using GDA, and compared with the results extracted by stochastic subspace identification （SSI） technique. The reasons for poor stability of flutter derivatives at higher wind speed and relative unsatisfactory precision of lateral flutter derivatives extracted from the free vibration method with the existent spring suspension system are offered. For the identification precision of flutter derivatives, experiment procedure is more important than the extraction approach.

关 键 词：桥梁 梯度下降算法 苏拉马都大桥 颤振导数 识别精度 

分 类 号：U448.213[建筑科学—桥梁与隧道工程]