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首页> 外文会议>International workshop on structural health monitoring >Identifications of Structural State Parameters of Concrete Columns with Self-sensing Basalt-fiber-reinforced Polymer Bars
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Identifications of Structural State Parameters of Concrete Columns with Self-sensing Basalt-fiber-reinforced Polymer Bars

机译：自感应玄武岩纤维增强聚合物筋混凝土柱结构状态参数的识别

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In general, for the implementation of structural health monitoring (SHM) based on strain monitoring, the directly measured strain is used as a structural parameter or index for damage location. However, often a critical range of strains of all the structural members is not enough to evaluate the service performance and safety of structures. Instead, critical ranges of global structural parameters, such as deformation, load and rotation, are provided in structural design codes and standards to define the required serviceability. Therefore, it is a need to derive structural parameters from measured strain distributions. A self-sensing basalt-fiber-reinforced polymer bar that uses internal embedded long-gage fiber optic sensors (FBGs) is designed to implement internal strain measurement of reinforced concrete (RC) columns. A fiber-model-based algorithm is presented that uses the internal strain distribution to identify the structural state parameters, such as stress distribution, curvature distribution, displacement, and load. To determine the most effective implantation method, two schemes with different anchorage lengths and sensor locations are compared. Base on the identification of fiber model-based analysis, the effective sensing unit number is discussed to determine the structural state parameters of the tested RC columns. The computational accuracy of the fiber-model-based algorithm is discussed and it is demonstrated that the measured strain distribution can be used to calculate the structural state parameters before and after flexural yielding.
机译：通常，对于基于应变监视的结构健康监视（SHM）的实施，直接测量的应变用作损坏位置的结构参数或指标。然而，通常所有结构构件的临界应变范围不足以评估结构的使用性能和安全性。取而代之的是，在结构设计规范和标准中提供了诸如变形，载荷和旋转之类的全局结构参数的关键范围，以定义所需的使用寿命。因此，需要从测得的应变分布中得出结构参数。一种使用内部嵌入式长规光纤传感器（FBG）的自感应玄武岩纤维增强聚合物棒，旨在实现钢筋混凝土（RC）柱的内部应变测量。提出了一种基于纤维模型的算法，该算法使用内部应变分布来识别结构状态参数，例如应力分布，曲率分布，位移和载荷。为了确定最有效的植入方法，比较了具有不同锚固长度和传感器位置的两种方案。在基于纤维模型的分析识别的基础上，讨论了有效的传感单元编号，以确定被测钢筋混凝土柱的结构状态参数。讨论了基于纤维模型的算法的计算精度，并证明了所测得的应变分布可用于计算弯曲屈服前后的结构状态参数。

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