移动车辆载荷作用下的桥梁结构损伤分布式识别方法研究

Bridge structures are subject to continuous degradation due to the environmental factors of ageing and excessive vehicular loading. The delegation will be accumulated and even a fatal bridge accident is induced. Monitoring of bridges is a key part of any maintenance strategies as it can give early warning to avoid the bridge accident if a bridge structure becomes unsafe. And it can also monitor and control the overloaded moving vehicles. The main objective of this research is to develop a substructural condition assessment approach for bridge structures subject to moving vehicles, and the moving vehicular loads and the bridge structural damage can be identified simultaneously. The dynamic degradation behaviour of the bridge in the local-micro and meso-scale level and the global macro-scale level will be modelled in the substructural domain. The dynamic behaviour of the damaged bridge subjected to moving vehicles in the operational environment is analyzed by the substructural technique. The substructural identification will be combined with the wireless sensory network to implement the decentralized damage detection for large-scale structures. The statistical analysis will be utilized to consider the effect of the uncertainties in modeling and measurements. Through this study, the accuracy and efficiency for the simultaneous identification of moving vehicular loads and structural damage of bridges are improved and it will provide some techniques for bridge structural health monitoring.

桥梁结构在时变环境因素和超载移动车辆载荷的反复作用下，不可避免地导致结构系统的损伤并使损伤逐步累积扩大，极端情况下极易诱发灾难性的事故。实时监控桥梁的超载移动车辆载荷、准确对结构进行损伤识别并评估其安全性的研究工作迫在眉睫。本课题基于无线传感器网络与动力子结构技术，研究桥梁结构的动力劣化行为，构建整体结构宏观与局部结构微-细观尺度的子结构，确立损伤结构在时变环境因素和移动车辆载荷共同作用下的动力学模型，提出时变环境下桥梁移动车辆载荷与结构损伤的分布式并行同步识别新方法；考虑环境、模型与测量误差等不确定因素，研究各种不确定因素对桥梁移动车辆载荷与结构损伤识别的影响，并提出对应的统计识别方法，重点融合新型传感器技术和结构损伤识别的最新成果，研究损伤结构宏观与微-细观尺度不同子结构域的描述，以期提高桥梁移动车辆载荷与结构损伤分布式同步识别技术的精度与效率，为桥梁结构健康监测提供技术支持。

交通荷载作用下桥梁动力特性的研究是桥梁结构健康监测的重要组成部分。在车桥相互作用框架下桥的动力响应是一个时变过程。辨识目标结构的时变动力特性是准确评估目标结构性能和状态的关键。本项目研究了移动车辆作用下基于经验小波变换提取脊线的桥梁时变参数识别以及移动荷载下基于参数优化变分模态分解的损伤桥梁的非线性特性。数值和实验研究证明了所提方法在瞬时频率估计方面的可行性和有效性。所确定的影响因子揭示了桥梁动力学的重要时变特征，这对评估实际运行桥梁的实际性能具有重要意义，并可用于结构健康评估。通过车辆荷载下混凝土桥梁模型的室内试验结果，成功识别了不同损伤情景下桥梁模型的非平稳非线性动力特性。提取的瞬时频率清晰地揭示了呼吸裂缝的行为，可以作为桥梁损伤的潜在指标。在此基础上，开展了基于连续变分模态分解从移动检测车响应识别桥梁模态的研究以及基于双卡尔曼滤波和奇异谱分析从车桥接触点响应识别桥梁模态研究。多次试验的平均值，可以准确识别桥梁的模态参数。阻尼比识别比频率识别对运营荷载更敏感，多次试验可提高桥梁随机运行荷载下阻尼比识别的准确性。该方法能显著抑制车辆响应分量，减小路面不平度的影响，提高桥梁模态识别能力。本项目的研究对桥梁等大型结构损伤识别理论研究和工程实践有重要的理论意义和应用价值。