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A technique for autonomous structural damage detection with smart wireless sensor network

机译:智能无线传感器网络的自主结构损伤检测技术

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In this paper, a distributed structural damage detection approach is proposed for large size structures under limited input and output measurements. A large size structure is decomposed into small size substructures based on its finite element formulation. Interaction effect between adjacent substructures is considered as 'additional unknown inputs' to each substructure. By sequentially utilizing the extended Kalman estimator for the extended state vector and the least squares estimation for the unmeasured inputs, the approach can not only estimate the 'additional unknown inputs' based on their formulations but also identify structural dynamic parameters, such as the stiffness and damping of each substructure. Local structural damage in the large size structure can be detected by tracking the changes in the identified values of structural dynamic parameters at element level, e.g., the degrading of stiffness parameters. Numerical example of detecting structural local damages in a large-size plane truss bridge illustrates the efficiency of the proposed approach. A new smart wireless sensor network is developed by the authors to combine with the proposed approach for autonomous structural damage detection of large size structures. The distributed structural damage detection approach can be embedded into the smart wireless sensor network based on its two-level cluster-tree topology architecture and the distributed computation capacity of each cluster head.
机译:本文提出了一种在有限的输入和输出测量下针对大型结构的分布式结构损伤检测方法。基于其有限元公式,大尺寸结构可分解为小尺寸子结构。相邻子结构之间的交互作用被视为每个子结构的“其他未知输入”。通过对扩展状态向量顺序使用扩展卡尔曼估计器,对未测量输入使用最小二乘估计,该方法不仅可以基于其公式来估计“其他未知输入”,还可以识别结构动力学参数,例如刚度和刚度。每个子结构的阻尼。大尺寸结构中的局部结构损坏可以通过在元素级别上跟踪已确定的结构动力学参数值的变化(例如,刚度参数的下降)来检测。在大型平面桁架桥中检测结构局部损伤的数值示例说明了该方法的有效性。作者开发了一种新的智能无线传感器网络,该网络与所提出的用于大型结构的自主结构损伤检测的方法相结合。分布式结构损坏检测方法可以基于其二级群集树拓扑结构和每个群集头的分布式计算能力而嵌入到智能无线传感器网络中。

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