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Closed-form solution based genetic algorithm software: Application to multiple cracks detection on beam structures by static tests

机译:基于闭合液的遗传算法软件:通过静态测试应用于梁结构的多个裂缝检测

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摘要

In this paper a procedure for the static identification and reconstruction of concentrated damage distribution in beam-like structures, implemented in a dedicated software, is presented. The proposed damage identification strategy relies on the solution of an optimisation problem, by means of a genetic algorithm, which exploits the closed form solution based on the distribution theory of multi-cracked beams subjected to static loads. Precisely, the adoption of the closed-form solution allows a straightforward evolution of an initial random population of chromosomes, representing different damage distributions along the beam axis, towards the fittest and selected as the sought solution. This method allows the identification of the position and intensity of an arbitrary number of cracks and is limited only by the amount of data experimentally measured. The proposed procedure, which has the great advantage of being robust and very fast, has been implemented in the powerful agent based software environment NetLogo, and is here presented and validated with reference to several benchmark cases of single and multi-cracked beams considering different load scenarios and boundary conditions. Sensitivity analyses to assess the influence of instrumental errors are also included in the study. (C) 2017 Elsevier B.V. All rights reserved.
机译:本文提出了一种在专用软件中实现的光束结构中静态识别和重建集中损伤分布的过程。通过遗传算法,所提出的损害识别策略依赖于优化问题的解决方案,该遗传算法基于经受静载荷的多裂纹光束的分布理论利用闭合形式解决方案。精确地,采用封闭式溶液允许染色体初始随机群的直接演变,沿着梁轴表示不同的损伤分布,朝向最适合并且选择作为所寻求的解决方案。该方法允许识别任意数量的裂缝的位置和强度,并且仅受到实验测量的数据量的限制。具有强大且非常快速的拟议程序,它已经在基于强大的基于代理的软件环境NetLogo中实现,并参考考虑不同负载的单个和多破裂光束的多个基准情况来呈现和验证场景和边界条件。评估仪器误差影响的敏感性分析也包括在研究中。 (c)2017 Elsevier B.v.保留所有权利。

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