基于过桥车辆响应的遗传算法桥梁损伤识别
Bridge Damage Detection Using a Moving Vehicle Response on the Bridge with Genetic Algorithm

在考虑线路不平顺的基础上建立了移动车辆过桥的有限元模型，基于移动车辆动力响应采用遗传算法（genetic algorithm，简称GA）实现了桥梁结构不同损伤状态的识别。以桥梁损伤位置和损伤程度作为识别因子，首先，利用GA算法生成不同桥梁损伤状态；其次，采用有限元车桥模型分别计算不同状态下的车辆动力响应作为分析数据；最后，采用模拟实测数据与分析数据构建目标函数进行识别。针对不同损伤工况进行多次独立重复计算，选用成功率及首次出现最优解平均迭代代数分析GA算法识别效率。研究发现：GA算法能以较高效率实现桥梁单目标和多目标损伤的识别；识别过程中搜索空间大小对GA算法识别效率影响较大；GA算法对桥梁跨中及3/4跨位置的损伤识别结果较桥梁端部更为稳定。
With the consideration of railway irregularity, a finite element model of vehicle/bridge system is established in this study, and the damage detection of different bridge patterns is achieved using vehicle response with genetic algorithm (GA). The damage location and degree of bridge are taken as recognition factors. The objective function is constructed by comparing the simulated and measured vehicle response data with some vehicle-response-analysis data. For the assumed damage cases, every detection process is independently calculated for several times, and the successful rate and the average iterative number are used to evaluate the detection efficiency of GA when the first optimal solution appears. This study shows that GA can achieve the bridge damage detection with a high detection efficiency not only for single object detection but also for multi-object detection. The search space size has a great impact on the GA detection efficiency. Therefore, this method is much more stable for the damage located at the middle and 3/4 span than at the ends.