Damage identification based on topology optimization and Lasso regularization

IF 2.2 3区 工程技术 Q2 MECHANICS
Ryo Sugai, Akira Saito, Hidetaka Saomoto
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引用次数: 0

Abstract

In this paper, we present a damage identification method for small damages based on topology optimization and Lasso regularization. In particular, this work extends the applicability of the previously developed damage identification method using frequency response functions and topology optimization, by conducting rigorous parametric studies in terms of damping, measurement noise, and damage size. It is shown that the presented method successfully identifies small damaged regions with a reasonable accuracy. To evaluate the effectiveness of the proposed method, we applied the method to identify the damages in cantilevered plates that are subject to static or dynamic loads. The method succeeded in detecting the locations and shapes of damages more accurately than the method without Lasso regularization. Furthermore, in most cases we have considered, spurious damages generated during the optimization were successfully suppressed.

Abstract Image

基于拓扑优化和Lasso正则化的损伤识别
本文提出了一种基于拓扑优化和Lasso正则化的小损伤识别方法。特别是,这项工作通过在阻尼、测量噪声和损伤尺寸方面进行严格的参数研究,扩展了先前开发的使用频率响应函数和拓扑优化的损伤识别方法的适用性。结果表明,该方法以合理的精度成功地识别了小的损伤区域。为了评估所提出方法的有效性,我们将该方法应用于识别承受静态或动态载荷的悬臂板的损伤。该方法比没有Lasso正则化的方法更准确地检测出损伤的位置和形状。此外,在我们考虑的大多数情况下,在优化过程中产生的虚假损伤都得到了成功抑制。
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来源期刊
CiteScore
4.40
自引率
10.70%
发文量
234
审稿时长
4-8 weeks
期刊介绍: Archive of Applied Mechanics serves as a platform to communicate original research of scholarly value in all branches of theoretical and applied mechanics, i.e., in solid and fluid mechanics, dynamics and vibrations. It focuses on continuum mechanics in general, structural mechanics, biomechanics, micro- and nano-mechanics as well as hydrodynamics. In particular, the following topics are emphasised: thermodynamics of materials, material modeling, multi-physics, mechanical properties of materials, homogenisation, phase transitions, fracture and damage mechanics, vibration, wave propagation experimental mechanics as well as machine learning techniques in the context of applied mechanics.
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