Damage Identification Using Static and Dynamic Responses Based on Topology Optimization and Lasso Regularization

Ryo Sugai, A. Saito, H. Saomoto
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引用次数: 1

Abstract

This paper presents a damage identification method based on topology optimization and Lasso regularization. The method uses static displacements or dynamic responses to identify damages of structures. The method has the potential to identify damages with high fidelity, in comparison with ordinary damage identification method based on optimization with parameterized geometry of the damages. However, it is difficult to precisely detect damage using topology optimization due mostly to the large number of design variables. Therefore, supposing that the damage is sufficiently small, we propose a method adding Lasso regularization to the objective functions to suppress active design variables during topology optimization process. To verify the effectiveness of the proposed method, we conducted a set of numerical experiments for static and dynamic problems. We have succeeded in suppressing active design variables and delete artificially generated damages and the location and shape of damage have been precisely identified.
基于拓扑优化和Lasso正则化的静态和动态损伤识别
提出了一种基于拓扑优化和Lasso正则化的损伤识别方法。该方法利用静力位移或动力响应来识别结构的损伤。与基于参数化损伤几何参数优化的普通损伤识别方法相比,该方法具有高保真度的损伤识别潜力。然而,由于设计变量过多,使用拓扑优化方法难以精确检测损伤。因此,假设损伤足够小,我们提出了一种在目标函数中加入Lasso正则化来抑制拓扑优化过程中的主动设计变量的方法。为了验证所提方法的有效性,我们进行了一组静态和动态问题的数值实验。我们已经成功地抑制了主动设计变量,删除了人为产生的损伤,并且精确地识别了损伤的位置和形状。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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