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提出了基于有限元模型修正的单车通过多梁式桥梁的移动荷载识别方法。首先采用Butter-worth低通滤波器对现场采集到的24h内所有过桥车辆产生的桥梁动位移信号进行滤波处理,提取静力响应极值,并严格按照车型进行分类统计;其次,对观测桥梁进行基于静力试验的有限元模型修正,建立能够反映桥梁真实状态的基准有限元模型;最后将修正后的有限元模型输入至自行研发的BDANS软件中的多梁式车-桥耦合振动模块,以车型为单位,依据该车型车辆在桥面横向移动时各主梁竖向位移响应分配关系,结合多梁式车-桥耦合振动模块以及实测车辆过桥时各主梁静力极值响应,识别出车辆在桥面行驶的横向位置,然后根据识别出的车辆横向行驶位置和实测桥梁响应识别出车质量。结果表明:该识别方法较为可靠,识别精度较高,能按照车型批量进行识别,可大规模处理交通荷载数据。
A moving load identification method based on the finite element model is proposed to identify the bicycle passing through the multi-girder bridge. Firstly, the Butter-worth low-pass filter was used to filter the dynamic displacement signals of all the bridge vehicles collected in the scene within 24h, and the extreme value of the static response was extracted and classified strictly according to the model. Secondly, The finite element model based on the static test is amended to establish a baseline finite element model that can reflect the true state of the bridge. Finally, the modified finite element model is input to the multi-beam vehicle-bridge coupling vibration module developed by BDANS software, Based on the vehicle model, according to the vertical displacement response distribution relationship of the main girder when the vehicle moves laterally on the bridge deck, combined with the multi-girder vehicle-bridge coupling vibration module and the static extreme value response of each main girder when the vehicle crosses the bridge, The lateral position of the vehicle traveling on the deck, and then identify the vehicle mass based on the identified vehicle lateral travel position and the measured bridge response. The results show that this method is more reliable and has higher recognition accuracy. It can be identified according to the batch of vehicles and can be used to deal with traffic load data on a large scale.