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Damage identification on spatial Timoshenko arches by means of genetic algorithms

机译:季莫申科拱门空间损伤的遗传算法识别

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HighlightsA procedure for the dynamic damage identification in spatial arches is presented.Both small and large extents of damage and possible losses of mass are considered.An eigen-properties based objective function is used in a genetic algorithm procedure.Applications with different number and extents of damaged parts are presented.The procedure is tested also in presence of instrumental errors on the measured data.AbstractIn this paper a procedure for the dynamic identification of damage in spatial Timoshenko arches is presented. The proposed approach is based on the calculation of an arbitrary number of exact eigen-properties of a damaged spatial arch by means of the Wittrick and Williams algorithm. The proposed damage model considers a reduction of the volume in a part of the arch, and is therefore suitable, differently than what is commonly proposed in the main part of the dedicated literature, not only for concentrated cracks but also for diffused damaged zones which may involve a loss of mass. Different damage scenarios can be taken into account with variable location, intensity and extension of the damage as well as number of damaged segments. An optimization procedure, aiming at identifying which damage configuration minimizes the difference between its eigen-properties and a set of measured modal quantities for the structure, is implemented making use of genetic algorithms. In this context, an initial random population of chromosomes, representing different damage distributions along the arch, is forced to evolve towards the fittest solution. Several applications with different, single or multiple, damaged zones and boundary conditions confirm the validity and the applicability of the proposed procedure even in presence of instrumental errors on the measured data.
机译: 突出显示 介绍了一种用于空间拱门中动态损伤识别的过程。 无论大小范围的破坏以及可能造成的损失 在遗传算法过程中使用了基于特征属性的目标函数。 编号和编号不同的应用 在所测数据存在仪器错误的情况下,也对该程序进行了测试。 摘要 本文提供了一种动态识别损害的程序在空间季莫申科拱门提出了。所提出的方法基于借助Wittrick和Williams算法计算任意数量的受损空间拱的精确本征特性。拟议的损伤模型考虑减小拱形部分的体积,因此与专用文献主要部分中通常提出的模型不同,它不仅适用于集中裂缝,而且适用于可能会扩散的损坏区域,因此是合适的。涉及质量损失。可以考虑到不同的损坏场景,其中损坏的位置,强度和范围以及损坏段的数量会有所不同。利用遗传算法实现了旨在识别哪种损伤构型将其本征特性与一组测量到的模态量之间的差异最小化的优化程序。在这种情况下,代表沿弓的不同损伤分布的初始染色体随机种群被迫向最适解发展。几个具有不同,单个或多个损坏区域和边界条件的应用程序甚至在测量数据存在仪器错误的情况下,也证实了所提出程序的有效性和适用性。

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