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

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Abstract

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.

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Authors and Affiliations

  1. School of Production Engineering and Management, Technical University of Crete, 73100, Chania, Greece

    Iraklis Dimitrios Psychas, Magdalene Marinaki, Yannis Marinakis & Georgios E. Stavroulakis

  2. Institut für Statik, Technische Universität Braunschweig, 38106, Braunschweig, Germany

    Marco Schauer

  3. Technische Universität Braunschweig, Institut für Konstruktionstechnik (IK), Arbeitsgruppe Vibroakustik, 38106, Braunschweig, Germany

    Jens-Uwe Böhrnsen & Sabine C. Langer

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  1. Iraklis Dimitrios Psychas
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  2. Marco Schauer
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  3. Jens-Uwe Böhrnsen
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  4. Magdalene Marinaki
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  5. Yannis Marinakis
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  6. Sabine C. Langer
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  7. Georgios E. Stavroulakis
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Correspondence to Yannis Marinakis.

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Psychas, I.D., Schauer, M., Böhrnsen, JU. et al. Detection of defective pile geometries using a coupled FEM/SBFEM approach and an ant colony classification algorithm. Acta Mech 227, 1279–1291 (2016). https://doi.org/10.1007/s00707-015-1548-3

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  • DOI: https://doi.org/10.1007/s00707-015-1548-3

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