摘要
为了识别桥梁交通振动试验中行走车辆的参数,提出基于遗传算法的参数识别方法.利用小波变换方法由车辆自由衰减振动响应获得车辆的模态参数,进一步联合应用遗传算法及复数特征值计算方法,由模态参数反算车辆的转动惯量性质、刚度以及阻尼系数等物理参数.通过3组模拟数据的计算分析,验证了遗传算法用于车辆参数识别的有效性.以实际车辆的振动试验实测结果为例,检验了遗传算法在车辆参数识别中的适用性.算例以及应用实例表明:应用遗传算法能精确识别出车辆的物理参数.
A parameter identification method based on genetic algorithms was proposed to identify the parameters of vehicle in bridge vibration test. First, the modal parameters of vehicle were identified from the damped free vibration response by wavelet transform. Then, the physical parameters such as inertia moment, stiffness and damping coefficients of the vehicle were inversely calculated from the modal parameters by the combined use of genetic algorithms and calculation of complex eigenvalue. The proposed method was validated by three groups of data from numerical simulation. Finally, the feasibility of the method was validated by field testing of a vehicle. Results show that the physical parameters of vehicle can be identified with high precision by genetic algorithms.
出处
《浙江大学学报（工学版）》
EI
CAS
CSCD
北大核心
2010年第9期1818-1824,共7页
Journal of Zhejiang University：Engineering Science
基金
国家自然科学基金资助项目(50778160).
关键词
遗传算法
参数识别
车辆参数
交通振动
genetic algorithm
parameter identification
vehicle parameter
traffic vibration
作者简介
谢旭（1963-），男，浙江慈溪人，教授，从事桥梁结构研究．E-mail：xiexu@zju．edu．cn
