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首页> 外文会议>NDE/NDT for Highways and Bridges >Acceleration Time Series Based Model Free Linkage Damage Detection for a Steel-Concrete Composite Girder
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Acceleration Time Series Based Model Free Linkage Damage Detection for a Steel-Concrete Composite Girder

机译：基于加速时间序列的钢混凝土复合梁的基于模型自由联动损伤检测

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Steel-concrete composite structures have been widely used in highway and bridge engineering. In a composite girder, efficient shear connectors are the key to ensure the transfer of longitudinal shear forces across the steel-concrete interface. The mechanical behavior of the composite structural members heavily depends on the performance of the shear connections because damage or failure of the connectors will decrease the load carrying capacity of the composite members. In this paper, an acceleration-based shear connector interfacial bonding performance evaluation methodology with neural network where no finite element model of the composite structural member is needed was proposed. Vibration tests on the composite girder before and after loosening or removing some connectors were implemented and the corresponding acceleration responses were acquired. Using acceleration time series at certain location of a substructure of the intact composite girder, a nonparametric base-line model based on neural network were established. The acceleration response measurements of the structure after connectors are loosened or removed were recorded. The nonparametric model was employed to forecast the acceleration response of the damaged composite girder and it was found that the acceleration response of the damaged structural member could not meet the forecasted acceleration response of the damage composite girder. The difference between the output and the measurement provides an index for damage detection of the shear connector. Results show that the proposed nonparametric method is effective to detect the loosening and removal damage of the shear connectors for composite structures solely using acceleration time series from a substructure.
机译：钢 - 混凝土组合结构已被广泛应用于高速公路和桥梁工程。在复合梁，高效剪切连接器，以确保纵向剪切力的跨钢 - 混凝土界面转移的关键。复合结构件的机械性能很大程度上取决于剪切连接的性能，因为连接器的损坏或失效会降低复合部件的承载能力。在本文中，基于加速度剪切连接器的界面粘结性能的评价方法与其中所需要的复合结构构件的没有有限元模型，提出了神经网络。振动试验前和旋松或移除一些连接器得以实施，被收购相应加速度响应后的复合梁上。在完整的组合梁的一个子结构的某些位置使用加速度时间序列，基于神经网络的非参数的基线模型来建立。连接器之后的结构的加速度响应测量被松开或移除的记录。非参数模型用于预测损伤复合梁的加速度响应，并将其结果发现，受损结构构件的加速度响应不能满足损害复合梁的预测加速响应。输出和测量值之间的差异提供了一种用于损伤检测的剪力连接器的索引。结果表明，所提出的非参数方法是有效的，以检测抗剪切连接件的松动和移动损伤全权使用来自子加速时间系列复合结构。

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