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Detection of defective pile geometries using a coupled FEM/SBFEM approach and an ant colony classification algorithm

机译:使用耦合FEM / SBFEM方法和蚁群分类算法检测缺陷桩的几何形状

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Piles are widely used to build a proper foundation for various buildings. The piles' quality in situ can be tested by a so-called pile integrity test. In order to apply this test, an impulse is given to the piles' head which generates a p-wave running through the pile. An acceleration sensor is attached to the piles' head, to measure the vertical movement. The major part of this wave is reflected from the piles' toe and is measured by the attached acceleration sensor on top of the pile. This yields an acceleration-time plot which has to be analysed in order to determine the piles' condition with respect to structural consistence and mostly radius defects. Since deviations in the cross section of the pile cause additional reflections, suitable post-processing can be used in order to detect these defects. In this paper, we propose an ant colony classification model to detect structural defects in piles by evaluating displacement-time plots to improve the reliability of pile monitoring. The data of these plots result to numerically performed pile integrity tests. To conduct these tests, a simulation of a combined finite element method and scaled boundary finite element methods has been carried out. These results are used for learning and training the ant colony classification model and to have different sets of data to validate the optimization algorithm. The position and the type of piles' defect can be identified by the applied algorithm.
机译:桩被广泛用于为各种建筑物建立适当的基础。可以通过所谓的桩完整性测试来测试桩的质量。为了进行此测试,向桩头施加了一个脉冲,该脉冲产生了穿过桩头的p波。加速度传感器连接到桩头,以测量垂直运动。该波的主要部分从桩的脚趾反射,并由桩顶上连接的加速度传感器测量。这将产生一个加速时间图,必须对其进行分析以便确定桩在结构一致性和主要是半径缺陷方面的状况。由于桩横截面的偏差会引起额外的反射,因此可以使用适当的后处理来检测这些缺陷。本文提出了一种蚁群分类模型,通过评估位移时间图来检测桩的结构缺陷,以提高桩监测的可靠性。这些图的数据得出数值进行桩完整性测试。为了进行这些测试,已经进行了组合有限元方法和比例边界有限元方法的模拟。这些结果用于学习和训练蚁群分类模型,并具有不同的数据集来验证优化算法。桩缺陷的位置和类型可以通过所应用的算法来识别。

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